IRENA Web Map Service

Global power lines, sub stations and generators OpenStreetMap 2016 (irena:osm_global_power_network_2016)

This map shows the power lines, substations and power generators for the whole world. The power lines have been reviewed for positional accuracy using google satellite maps. Most of the lines checked on the map, seem to correspond with the actual location lines as confirmed by high resolution aerial images from google satellite maps. Limitations on the dataset include incompleteness in certain areas, and less information on the voltage capacity of some of the lines. This dataset was extracted from the OpenStreetMap initiative. OpenStreetMap® is open data, licensed under the Open Data Commons Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF). © OpenStreetMap contributors http://www.openstreetmap.org/copyright

3 year daily average solar exposure map Mali 3Km GRAS February 2008-2011 (mali:02_Februar_MSG_DSSF)

This map contains the 3 year (2008-2011) daily average solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for February. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

3 year daily average solar exposure map Mali 3Km GRAS April 2008-2011 (mali:04_April_MSG_DSSF)

This map contains the 3 year (2008-2011) daily average solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for April. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

3 year daily average solar exposure map Mali 3Km GRAS June 2008-2011 (mali:06_June_MSG_DSSF)

This map contains the 3 year (2008-2011) daily average solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for June. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

3 year daily average solar exposure map Mali 3Km GRAS August 2008-2011 (mali:08_August_MSG_DSSF)

This map contains the 3 year (2008-2011) daily average solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for August. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

3 year daily average solar exposure map Mali 3Km GRAS October 2008-2011 (mali:10_October_MSG_DSSF)

This map contains the 3 year (2008-2011) daily average solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for October. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

3 year daily average solar exposure map Mali 3Km GRAS December 2008-2011 (mali:12_December_MSG_DSSF)

This map contains the 3 year (2008-2011) daily average solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for December. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

daily average solar exposure map Mali 3Km GRAS June2008-July2011 (mali:200807_201106_avg_MSG_DSSF)

This map contains the 3 year (June2008-July2011) solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS August 2008 (mali:200808_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for August 2008. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS October 2008 (mali:200810_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for October 2008. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS December 2008 (mali:200812_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for December 2008. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS February 2009 (mali:200902_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for February 2009. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS April 2009 (mali:200904_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for April 2009. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS June 2009 (mali:200906_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for June 2009. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS July 2009 (mali:200907_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for July 2009. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS September 2009 (mali:200909_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for September 2009. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS November 2009 (mali:200911_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for November 2009. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS January 2010 (mali:201001_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for January 2010. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS March 2010 (mali:201003_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for March 2010. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS May 2010 (mali:201005_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for May 2010. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

daily average solar exposure map Mali 3Km GRAS July2010-June2011 (mali:201007_201106_avg_cut)

This map contains the daily average for July2010-June2011 solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS August 2010 (mali:201008_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for August 2010. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS October 2010 (mali:201010_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for October 2010. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS December 2010 (mali:201012_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for December 2010. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS January 2010 (mali:201101_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for January 2011. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS March 2011 (mali:201103_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for March 2011. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Solar exposure map Mali 3Km GRAS May 2011 (mali:201105_avg_cut)

This map contains the monthly solar exposure (in KWh/m2/day) with a resolution of 3Km for Mali for May 2011. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Alliance for Zero Extinction sites world point AZE 2010 (AZE:AZEpoly_2010_16March2012_allData)

This dataset shows the Alliance for Zero Extinction (AZE) 2010 sites

Generalize annual mean wind speed at 50m Mali 7.5Km RISOE 1977-2006 (mali:Atlas_MBS75_50_latwa_z50_7_5_wam_u_tiff)

This map contains the generalize annual mean wind speed [m/s] at 50 m a.g.l. over the flat terrain and uniform roughness of 0.03 m. References: 1. Estimation of wind and solar resources in Mali Jake Badger, Famakan Kamissoko, Mads Olander Rasmussen, Søren Larsen, Nicolas Guidon, Lars Boye Hansen, Luc Dewilde, Maiga Alhousseini, Per Nørgaard, Ivan Nygaard November 2012 ISBN 978-87-92706-55-3 Available at: http://www.frsemali.org/reports/0%20a%20a%20a%20rapporter%20til%20Mali/solar%20wind%20report%20version%20english%20final%2027.11.12%20frontpage.pdf 2. Nygaard, I, Rasmussen, K., Badger, J., Nielsen, T.T. , Hansen, L.B. , Stisen, S. , Larsen, S. , Mariko, A. , Togola, I. (2010) Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: the case of Mali. Renewable and Sustainable Energy Reviews, vol 14, Issue 8, October 2010, Pages 2359-2371 3. official webpage: http://frsemali.org

Mozambique - Land use map of 2010 in BAU scenario (mozambique_bioenergy:BlandUse2010)

The Business as Usual (BAU) scenario projects a future in which historical trends in yield levels and livestock productivity are continued, resulting in a low agricultural productivity. The progressive scenario assumes the implementation of improved agricultural management resulting in a high agricultural productivity. The land use changes for each year towards 2030 were modelled on high resolution by allocating land to a land use class based on the suitability for the specific land use classes. Areas that are not suitable (such as steep slopes) or not allowed (such as conservation areas) to be converted to agricultural land, were excluded. Based on the allocation of land use classes and the maps of excluded areas for bioenergy production (such as forest areas), the land availability for bioenergy crops is determined. Reference van der Hilst et al, 2012 and Verstegen et al 2012 Contacts Dr. F. van der Hilst, Copernicus Institute of Sustainable Development, Utrecht University, Section Energy & Resources.

Mozambique - Land use map of 2030 in BAU scenario (mozambique_bioenergy:BlandUse2030)

The Business as Usual (BAU) scenario projects a future in which historical trends in yield levels and livestock productivity are continued, resulting in a low agricultural productivity. The progressive scenario assumes the implementation of improved agricultural management resulting in a high agricultural productivity. The land use changes for each year towards 2030 were modelled on high resolution by allocating land to a land use class based on the suitability for the specific land use classes. Areas that are not suitable (such as steep slopes) or not allowed (such as conservation areas) to be converted to agricultural land, were excluded. Based on the allocation of land use classes and the maps of excluded areas for bioenergy production (such as forest areas), the land availability for bioenergy crops is determined. Reference van der Hilst et al, 2012 and Verstegen et al 2012 Contacts Dr. F. van der Hilst, Copernicus Institute of Sustainable Development, Utrecht University, Section Energy & Resources.

Mozambique - Land availability map of 2020 in BAU scenario (mozambique_bioenergy:Blandavailable2020)

The Business as Usual (BAU) scenario projects a future in which historical trends in yield levels and livestock productivity are continued, resulting in a low agricultural productivity. The progressive scenario assumes the implementation of improved agricultural management resulting in a high agricultural productivity. The land use changes for each year towards 2030 were modelled on high resolution by allocating land to a land use class based on the suitability for the specific land use classes. Areas that are not suitable (such as steep slopes) or not allowed (such as conservation areas) to be converted to agricultural land, were excluded. Based on the allocation of land use classes and the maps of excluded areas for bioenergy production (such as forest areas), the land availability for bioenergy crops is determined. Reference van der Hilst et al, 2012 and Verstegen et al 2012 Contacts Dr. F. van der Hilst, Copernicus Institute of Sustainable Development, Utrecht University, Section Energy & Resources.

Detailed Exploration Zone (kenya:Detailed_Exploration_Zone)

The Dewhurst Group used its SPAN (Spectral Space Analysis) technique as part of a “fairway play” geothermal exploration analysis of previously unexplored areas of Kenya. The analysis takes into account data from: - Publicly available and proprietary aeromagnetic and gravity data. - Regional Geology. - Mineral concentrations from existing publicly available geochemical data. - Geological model comparisons from previously unpublished but completed geothermal SPAN exploration efforts. The geothermal areas identified here are based exclusively on these SPAN results and are expected, in certain regions, to show a high probability of having temperatures of up to 400°C at a depth of 4km to 5km and a sizable regional reservoir at depths of 2km to 6km. The priority areas are also expected to contain deep, 10km or deeper, fluid connections to magma and mantel zones. These are important characteristics for any successful geothermal power development. The Dewhurst Group is currently undertaking similar geothermal exploration efforts in Uganda, Rwanda, Ethiopia and Djibouti. Detailed SPAN analysis information from Kenya, including magnetic and gravity profiles is available at www. SPANgeoKenya.com or for more information please contact the Dewhurst Group at information@dewhurstgroup.us.

Dominant Terrain (tanzania:DominantTerrain)

Mean Power Density South Africa East Cape 250m WASA May 2013 (southAfrica:EC_250m_PD_2013_130)

Mean power density P [Wm−2] @ 100 m above ground level for East Cape. Purpose This data set was created for the WASA project and the Department of Energy, South Africa. The wind resource maps were designed specifically for inclusion in GIS-based strategic environmental assessments (SEA) for wind power in Western Cape and parts of Northern and Eastern Cape. Methodology Reference is made to the information and documentation available from http://www.wasaproject.info Limitations The data set is limited by the operational envelopes of the wind atlas methodology and the WAsP models. The accuracy depends on a) the accuracy of the VNWA, which has been verified against the data from 10 WASA measurement masts, b) the WAsP microscale modelling and c) the input topographical data. In complex terrain (RIX > 5%), the wind resources may be significantly over-estimated by the WAsP microscale modelling. Above and close to built-up areas like cities, towns and villages, the results are less reliable. Close to and above forested areas, the results are also less reliable and should be interpreted and used accordingly. The data set was designed specifically for planning purposes and should be used with utmost care for design, development and detailed assessments of actual wind farms; where local, on-site meas-urements are strongly recommended. The wind resource maps are subject to change without notice if and when more accurate and reliable data, models and procedures become available. Available documentation The wind atlas methodology is described in the European Wind Atlas (1989); the application of WAsP in the program documentation, see www.wasp.dk. The First Verified Numerical Wind Atlas for South Africa is a product of the Wind Atlas for South Africa project and is described further on the WASA download pages http://wasadata.csir.co.za/wasa1/WASAData Acknowledgements SANEDI (South African National Energy Development Institute) for managing WASA CSIR Environmental Management Services for providing height contour data for Eastern Cape and Northern Cape. MetroGIS (Pty) Ltd. for providing height contour data for Western Cape in WAsP-compatible format. WASA Implementation team: UCT (CSAG), CSIR, SAWS, DTU Wind Energy and World in a Box Oy for Frogfoot development. Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=2031. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Mean wind speed South Africa East Cape 250m WASA May 2013 (southAfrica:EC_250m_U)

Mean wind speed U [ms−1] @ 100 m above ground level for East Cape. Purpose This data set was created for the WASA project and the Department of Energy, South Africa. The wind resource maps were designed specifically for inclusion in GIS-based strategic environmental assessments (SEA) for wind power in Western Cape and parts of Northern and Eastern Cape. Methodology Reference is made to the information and documentation available from http://www.wasaproject.info Limitations The data set is limited by the operational envelopes of the wind atlas methodology and the WAsP models. The accuracy depends on a) the accuracy of the VNWA, which has been verified against the data from 10 WASA measurement masts, b) the WAsP microscale modelling and c) the input topographical data. In complex terrain (RIX > 5%), the wind resources may be significantly over-estimated by the WAsP microscale modelling. Above and close to built-up areas like cities, towns and villages, the results are less reliable. Close to and above forested areas, the results are also less reliable and should be interpreted and used accordingly. The data set was designed specifically for planning purposes and should be used with utmost care for design, development and detailed assessments of actual wind farms; where local, on-site meas-urements are strongly recommended. The wind resource maps are subject to change without notice if and when more accurate and reliable data, models and procedures become available. Available documentation The wind atlas methodology is described in the European Wind Atlas (1989); the application of WAsP in the program documentation, see www.wasp.dk. The First Verified Numerical Wind Atlas for South Africa is a product of the Wind Atlas for South Africa project and is described further on the WASA download pages http://wasadata.csir.co.za/wasa1/WASAData Acknowledgements SANEDI (South African National Energy Development Institute) for managing WASA CSIR Environmental Management Services for providing height contour data for Eastern Cape and Northern Cape. MetroGIS (Pty) Ltd. for providing height contour data for Western Cape in WAsP-compatible format. WASA Implementation team: UCT (CSAG), CSIR, SAWS, DTU Wind Energy and World in a Box Oy for Frogfoot development. Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=2031. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Expected_out_ha_multiple_cropping_rainfed_cereals_high (biotest:Expected_out_ha_multiple_cropping_rainfed_cereals_high)

Expected_out_ha_single_cropping_rainfed_cereals_high_land_dormin_forest (biotest:Expected_out_ha_single_cropping_rainfed_cereals_high_land_dormin_forest)

Expected_out_multiple_cropping_rainfed_cereals_high_excluding_forest (biotest:Expected_out_multiple_cropping_rainfed_cereals_high_excluding_forest)

VAISALA Global Solar Dataset 3km with units in W/m²/day (_3tier:GHI_Global_3km_3TIER)

VAISALA Global Solar Dataset 3km with units in W/m²/day VAISALA Global Solar Dataset provides average annual GHI at a 3km spatial resolution. Average values are based on more than 10 years of hourly GHI data and derived from actual, half-hourly, high-resolution visible satellite imagery observations via the broadband visible wavelength channel at a 2 arc minute resolution. VAISALA processed this information using on a combination of in-house research and algorithms published in peer-reviewed scientific literature. The dataset validated well when compared with observations from 120 geographically distributed surface stations around the globe (validation paper available here: http://www.vaisala.com/en/energy/Documents/WEA-ERG-3TIER-Global%20Wind%20Dataset.pdf). The information provided in the Global Atlas is meant to inform high-level policy debate (identification of opportunity areas for further prospection, preliminary assessment of technical potentials), or to perform market screening (cross referencing the resource information with policy information). It is suitable for decision-making activities, excluding financial commitments. It is a subset of a more detailed, long-term dataset, which includes hourly values of GHI, DNI, and other weather variables. VAISALA can provide this information and other customized services to facilitate project-specific or regional development, financial planning, and energy scheduling. By using this dataset, the user accepts VAISALA Terms and Conditions shown here: http://globalatlas.irena.org/VAISALA-terms-conditions.aspx Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=3033. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Geothermal Temperature at 1000m Ireland SEAI (ireland:GeothermalCalculated1000m)

This study was performed by the CSA Group in cooperation with Conodate Geology, Cork Institute of Technology and the Geological Survey of Ireland. The study surveyed/compiled data on warm springs and groundwater temperature trends. In order to map the subsurface temperatures, all available borehole data in the Republic of Ireland were gathered. Temperature data from 19 mineral and oil exploration holes ranging in depth from 300m to 2,500m (deepest borehole Drumkeeran (No. 1), Co Leitrim) were retrieved from previously monitored boreholes. In addition to this, CSA surveyed 32 existing, open boreholes to obtain their temperature profiles. This survey examined holes ranging in depth from 40m – 810m (deepest borehole 01-541-03, Co. Galway). A preliminary review of data from Northern Ireland was also included. All survey data were added to the existing temperature data compiled for earlier studies. These data are presented in the Final Report which can be accessed via the below website link. Geothermal maps have been produced for surface, 100m, 500m, 1,000m, 2,500m and 5,000m depths. For further information please visit: http://www.seai.ie/Grants/Renewable_Energy_RD_D/Projects_funded_to_date/Geothermal_Energy/

Geothermal Temperature at 10m Ireland SEAI (ireland:GeothermalCalculated10m)

This study was performed by the CSA Group in cooperation with Conodate Geology, Cork Institute of Technology and the Geological Survey of Ireland. The study surveyed/compiled data on warm springs and groundwater temperature trends. In order to map the subsurface temperatures, all available borehole data in the Republic of Ireland were gathered. Temperature data from 19 mineral and oil exploration holes ranging in depth from 300m to 2,500m (deepest borehole Drumkeeran (No. 1), Co Leitrim) were retrieved from previously monitored boreholes. In addition to this, CSA surveyed 32 existing, open boreholes to obtain their temperature profiles. This survey examined holes ranging in depth from 40m – 810m (deepest borehole 01-541-03, Co. Galway). A preliminary review of data from Northern Ireland was also included. All survey data were added to the existing temperature data compiled for earlier studies. These data are presented in the Final Report which can be accessed via the below website link. Geothermal maps have been produced for surface, 100m, 500m, 1,000m, 2,500m and 5,000m depths. For further information please visit: http://www.seai.ie/Grants/Renewable_Energy_RD_D/Projects_funded_to_date/Geothermal_Energy/

Geothermal Temperature at 5000m Ireland SEAI (ireland:GeothermalCalculated5000m)

This study was performed by the CSA Group in cooperation with Conodate Geology, Cork Institute of Technology and the Geological Survey of Ireland. The study surveyed/compiled data on warm springs and groundwater temperature trends. In order to map the subsurface temperatures, all available borehole data in the Republic of Ireland were gathered. Temperature data from 19 mineral and oil exploration holes ranging in depth from 300m to 2,500m (deepest borehole Drumkeeran (No. 1), Co Leitrim) were retrieved from previously monitored boreholes. In addition to this, CSA surveyed 32 existing, open boreholes to obtain their temperature profiles. This survey examined holes ranging in depth from 40m – 810m (deepest borehole 01-541-03, Co. Galway). A preliminary review of data from Northern Ireland was also included. All survey data were added to the existing temperature data compiled for earlier studies. These data are presented in the Final Report which can be accessed via the below website link. Geothermal maps have been produced for surface, 100m, 500m, 1,000m, 2,500m and 5,000m depths. For further information please visit: http://www.seai.ie/Grants/Renewable_Energy_RD_D/Projects_funded_to_date/Geothermal_Energy/

Kuwait Monthly Average Temperature 2012-2013 (kuwait:Kuwait_average_monthly_temp)

Data supplied by the Kuwait Institute for Scientific Research. Monthly average values for five measurement stations in Kuwait for temperature. Measurements cover the period Sept. 2012 - Aug. 2013.

Kuwait Monthly Average Wind Speed 2012-2013 (kuwait:Kuwait_average_wind_speed)

Data supplied by the Kuwait Institute for Scientific Research. Monthly average values for five measurement stations in Kuwait for wind speed. Measurements cover the period Sept. 2012 - Aug. 2013.

Kuwait Monthly Average DNI 2012-2013 (kuwait:Kuwait_dni)

Data supplied by the Kuwait Institute for Scientific Research. Monthly average values for five measurement stations in Kuwait for solar irradiation. Measurements cover the period Sept. 2012 - Aug. 2013.

Kuwait Maximum Monthly Temperature 2012-2013 (kuwait:Kuwait_max_monthly_temp)

Data supplied by the Kuwait Institute for Scientific Research. Monthly average values for five measurement stations in Kuwait for temperature. Measurements cover the period Sept. 2012 - Aug. 2013.

Kuwait Monthly Average Relative Humidity 2012-2013 (kuwait:Kuwait_relative_humidity)

Data supplied by the Kuwait Institute for Scientific Research. Monthly average values for five measurement stations in Kuwait for humidity. Measurements cover the period Sept. 2012 - Aug. 2013.

LGP Stations with two Growing Seasons (tanzania:LGP_stations_with_two_growing_seasons)

Elevation South Africa North Cape 250m WASA May 2013 (southAfrica:NC_250m_Elevation)

Elevation of modelling site in [m] above mean sea level for North Cape. Purpose This data set was created for the WASA project and the Department of Energy, South Africa. The wind resource maps were designed specifically for inclusion in GIS-based strategic environmental assessments (SEA) for wind power in Western Cape and parts of Northern and Eastern Cape. Methodology Reference is made to the information and documentation available from http://www.wasaproject.info Limitations The data set is limited by the operational envelopes of the wind atlas methodology and the WAsP models. The accuracy depends on a) the accuracy of the VNWA, which has been verified against the data from 10 WASA measurement masts, b) the WAsP microscale modelling and c) the input topographical data. In complex terrain (RIX > 5%), the wind resources may be significantly over-estimated by the WAsP microscale modelling. Above and close to built-up areas like cities, towns and villages, the results are less reliable. Close to and above forested areas, the results are also less reliable and should be interpreted and used accordingly. The data set was designed specifically for planning purposes and should be used with utmost care for design, development and detailed assessments of actual wind farms; where local, on-site meas-urements are strongly recommended. The wind resource maps are subject to change without notice if and when more accurate and reliable data, models and procedures become available. Available documentation The wind atlas methodology is described in the European Wind Atlas (1989); the application of WAsP in the program documentation, see www.wasp.dk. The First Verified Numerical Wind Atlas for South Africa is a product of the Wind Atlas for South Africa project and is described further on the WASA download pages http://wasadata.csir.co.za/wasa1/WASAData Acknowledgements SANEDI (South African National Energy Development Institute) for managing WASA CSIR Environmental Management Services for providing height contour data for Eastern Cape and Northern Cape. MetroGIS (Pty) Ltd. for providing height contour data for Western Cape in WAsP-compatible format. WASA Implementation team: UCT (CSAG), CSIR, SAWS, DTU Wind Energy and World in a Box Oy for Frogfoot development. Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=2031. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Site RIX value South Africa North Cape 250m WASA May 2013 (southAfrica:NC_250m_RIX)

Site RIX value calculated by WAsP (standard parameter setup) for North Cape . Purpose This data set was created for the WASA project and the Department of Energy, South Africa. The wind resource maps were designed specifically for inclusion in GIS-based strategic environmental assessments (SEA) for wind power in Western Cape and parts of Northern and Eastern Cape. Methodology Reference is made to the information and documentation available from http://www.wasaproject.info Limitations The data set is limited by the operational envelopes of the wind atlas methodology and the WAsP models. The accuracy depends on a) the accuracy of the VNWA, which has been verified against the data from 10 WASA measurement masts, b) the WAsP microscale modelling and c) the input topographical data. In complex terrain (RIX > 5%), the wind resources may be significantly over-estimated by the WAsP microscale modelling. Above and close to built-up areas like cities, towns and villages, the results are less reliable. Close to and above forested areas, the results are also less reliable and should be interpreted and used accordingly. The data set was designed specifically for planning purposes and should be used with utmost care for design, development and detailed assessments of actual wind farms; where local, on-site meas-urements are strongly recommended. The wind resource maps are subject to change without notice if and when more accurate and reliable data, models and procedures become available. Available documentation The wind atlas methodology is described in the European Wind Atlas (1989); the application of WAsP in the program documentation, see www.wasp.dk. The First Verified Numerical Wind Atlas for South Africa is a product of the Wind Atlas for South Africa project and is described further on the WASA download pages http://wasadata.csir.co.za/wasa1/WASAData Acknowledgements CSIR Environmental Management Services for providing height contour data for Eastern Cape and Northern Cape. MetroGIS (Pty) Ltd. for providing height contour data for Western Cape in WAsP-compatible format. WASA Implementation team: UCT (CSAG), CSIR, SAWS, DTU Wind Energy and World in a Box Oy for Frogfoot development. Acknowledgements SANEDI (South African National Energy Development Institute) for managing WASA CSIR Environmental Management Services for providing height contour data for Eastern Cape and Northern Cape. MetroGIS (Pty) Ltd. for providing height contour data for Western Cape in WAsP-compatible format. WASA Implementation team: UCT (CSAG), CSIR, SAWS, DTU Wind Energy and World in a Box Oy for Frogfoot development. Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=2031. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Percent of stunted children under five (tanzania:Percent_stunted_children_under_five)

Mozambique - Land use map of 2020 in progressive scenario (mozambique_bioenergy:PlandUse2020)

The Business as Usual (BAU) scenario projects a future in which historical trends in yield levels and livestock productivity are continued, resulting in a low agricultural productivity. The progressive scenario assumes the implementation of improved agricultural management resulting in a high agricultural productivity. The land use changes for each year towards 2030 were modelled on high resolution by allocating land to a land use class based on the suitability for the specific land use classes. Areas that are not suitable (such as steep slopes) or not allowed (such as conservation areas) to be converted to agricultural land, were excluded. Based on the allocation of land use classes and the maps of excluded areas for bioenergy production (such as forest areas), the land availability for bioenergy crops is determined. Reference van der Hilst et al, 2012 and Verstegen et al 2012 Contacts Dr. F. van der Hilst, Copernicus Institute of Sustainable Development, Utrecht University, Section Energy & Resources.

Mozambique - Land availability map of 2010 in progressive scenario (mozambique_bioenergy:Plandavailable2010)

The Business as Usual (BAU) scenario projects a future in which historical trends in yield levels and livestock productivity are continued, resulting in a low agricultural productivity. The progressive scenario assumes the implementation of improved agricultural management resulting in a high agricultural productivity. The land use changes for each year towards 2030 were modelled on high resolution by allocating land to a land use class based on the suitability for the specific land use classes. Areas that are not suitable (such as steep slopes) or not allowed (such as conservation areas) to be converted to agricultural land, were excluded. Based on the allocation of land use classes and the maps of excluded areas for bioenergy production (such as forest areas), the land availability for bioenergy crops is determined. Reference van der Hilst et al, 2012 and Verstegen et al 2012 Contacts Dr. F. van der Hilst, Copernicus Institute of Sustainable Development, Utrecht University, Section Energy & Resources.

Mozambique - Land availability map of 2030 in progressive scenario (mozambique_bioenergy:Plandavailable2030)

The Business as Usual (BAU) scenario projects a future in which historical trends in yield levels and livestock productivity are continued, resulting in a low agricultural productivity. The progressive scenario assumes the implementation of improved agricultural management resulting in a high agricultural productivity. The land use changes for each year towards 2030 were modelled on high resolution by allocating land to a land use class based on the suitability for the specific land use classes. Areas that are not suitable (such as steep slopes) or not allowed (such as conservation areas) to be converted to agricultural land, were excluded. Based on the allocation of land use classes and the maps of excluded areas for bioenergy production (such as forest areas), the land availability for bioenergy crops is determined. Reference van der Hilst et al, 2012 and Verstegen et al 2012 Contacts Dr. F. van der Hilst, Copernicus Institute of Sustainable Development, Utrecht University, Section Energy & Resources.

Generalized annual mean wind speed at 100m South Africa 5Km RISOE 1980-2009 (southAfrica:SAFSA2050_02_z100.51_U_layer)

This map contains the generalize annual mean wind speed [m/s] at 100 m a.g.l. over the flat terrain and uniform roughness of 0.03 m. The Wind Atlas for South Africa (WASA) Project is an initiative of the South African Dept of Energy (DoE) with the South African National Energy Development Institute (SANEDI) executing, managing WASA and contracting the Implementation Partners: The South African Council for Scientific and Industrial Research (CSIR), University of Cape Town (Climate Systems Analysis Group) (UCT CSAG), South African Weather Services (SAWS) and Department of Wind Energy, Technical University of Denmark (DTU Wind Energy). The main objective of WASA through capacity development and research cooperation is to develop and employ numerical (modelled) wind atlas methods and to develop capacity to enable long term planning of large-scale exploitation of wind power in South Africa, including dedicated wind resource assessment and siting tools for planning purposes, i.e. a Verified with physical wind measurements Numerical (modelled) Wind Atlas and database for South Africa. More information can be found following the link: http://www.wasaproject.info/. Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=2031. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

SPAN Extended Exploration Areas (kenya:SPAN_Extended_Exploration_Areas)

The Dewhurst Group used its SPAN (Spectral Space Analysis) technique as part of a “fairway play” geothermal exploration analysis of previously unexplored areas of Kenya. The analysis takes into account data from: - Publicly available and proprietary aeromagnetic and gravity data. - Regional Geology. - Mineral concentrations from existing publicly available geochemical data. - Geological model comparisons from previously unpublished but completed geothermal SPAN exploration efforts. The geothermal areas identified here are based exclusively on these SPAN results and are expected, in certain regions, to show a high probability of having temperatures of up to 400°C at a depth of 4km to 5km and a sizable regional reservoir at depths of 2km to 6km. The priority areas are also expected to contain deep, 10km or deeper, fluid connections to magma and mantel zones. These are important characteristics for any successful geothermal power development. The Dewhurst Group is currently undertaking similar geothermal exploration efforts in Uganda, Rwanda, Ethiopia and Djibouti. Detailed SPAN analysis information from Kenya, including magnetic and gravity profiles is available at www. SPANgeoKenya.com or for more information please contact the Dewhurst Group at information@dewhurstgroup.us.

South_Pacific_Communities_Chuuk_DNI_Apr (south_pacific_com:South_Pacific_Communities_Chuuk_DNI_Apr)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_DNI_Dec (south_pacific_com:South_Pacific_Communities_Chuuk_DNI_Dec)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_DNI_Jan (south_pacific_com:South_Pacific_Communities_Chuuk_DNI_Jan)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_DNI_Jun (south_pacific_com:South_Pacific_Communities_Chuuk_DNI_Jun)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_DNI_May (south_pacific_com:South_Pacific_Communities_Chuuk_DNI_May)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_DNI_Oct (south_pacific_com:South_Pacific_Communities_Chuuk_DNI_Oct)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_Elevation (south_pacific_com:South_Pacific_Communities_Chuuk_Elevation)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_GHI_Aug (south_pacific_com:South_Pacific_Communities_Chuuk_GHI_Aug)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_GHI_Feb (south_pacific_com:South_Pacific_Communities_Chuuk_GHI_Feb)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_GHI_Jul (south_pacific_com:South_Pacific_Communities_Chuuk_GHI_Jul)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_GHI_Mar (south_pacific_com:South_Pacific_Communities_Chuuk_GHI_Mar)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_GHI_Nov (south_pacific_com:South_Pacific_Communities_Chuuk_GHI_Nov)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Chuuk_GHI_Sep (south_pacific_com:South_Pacific_Communities_Chuuk_GHI_Sep)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_Aspect (south_pacific_com:South_Pacific_Communities_Pohnpei_Aspect)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_DNI_Aug (south_pacific_com:South_Pacific_Communities_Pohnpei_DNI_Aug)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_DNI_Feb (south_pacific_com:South_Pacific_Communities_Pohnpei_DNI_Feb)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_DNI_Jul (south_pacific_com:South_Pacific_Communities_Pohnpei_DNI_Jul)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_DNI_Mar (south_pacific_com:South_Pacific_Communities_Pohnpei_DNI_Mar)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_DNI_Nov (south_pacific_com:South_Pacific_Communities_Pohnpei_DNI_Nov)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_DNI_Sep (south_pacific_com:South_Pacific_Communities_Pohnpei_DNI_Sep)

South_Pacific_Communities_Pohnpei_GHI_Apr (south_pacific_com:South_Pacific_Communities_Pohnpei_GHI_Apr)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_GHI_Dec (south_pacific_com:South_Pacific_Communities_Pohnpei_GHI_Dec)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_GHI_Jan (south_pacific_com:South_Pacific_Communities_Pohnpei_GHI_Jan)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_GHI_Jun (south_pacific_com:South_Pacific_Communities_Pohnpei_GHI_Jun)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_GHI_May (south_pacific_com:South_Pacific_Communities_Pohnpei_GHI_May)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_GHI_Oct (south_pacific_com:South_Pacific_Communities_Pohnpei_GHI_Oct)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Pohnpei_Slope (south_pacific_com:South_Pacific_Communities_Pohnpei_Slope)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_DNI_Apr (south_pacific_com:South_Pacific_Communities_Yap_DNI_Apr)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_DNI_Dec (south_pacific_com:South_Pacific_Communities_Yap_DNI_Dec)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_DNI_Jan (south_pacific_com:South_Pacific_Communities_Yap_DNI_Jan)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_DNI_Jun (south_pacific_com:South_Pacific_Communities_Yap_DNI_Jun)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_DNI_May (south_pacific_com:South_Pacific_Communities_Yap_DNI_May)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_DNI_Oct (south_pacific_com:South_Pacific_Communities_Yap_DNI_Oct)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_Elevation (south_pacific_com:South_Pacific_Communities_Yap_Elevation)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_GHI_Aug (south_pacific_com:South_Pacific_Communities_Yap_GHI_Aug)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_GHI_Feb (south_pacific_com:South_Pacific_Communities_Yap_GHI_Feb)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_GHI_Jul (south_pacific_com:South_Pacific_Communities_Yap_GHI_Jul)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_GHI_Mar (south_pacific_com:South_Pacific_Communities_Yap_GHI_Mar)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_GHI_Nov (south_pacific_com:South_Pacific_Communities_Yap_GHI_Nov)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_Yap_GHI_Sep (south_pacific_com:South_Pacific_Communities_Yap_GHI_Sep)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_Aspect (south_pacific_com:South_Pacific_Communities_kosrae_Aspect)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_DNI_Aug (south_pacific_com:South_Pacific_Communities_kosrae_DNI_Aug)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_DNI_Feb (south_pacific_com:South_Pacific_Communities_kosrae_DNI_Feb)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_DNI_Jul (south_pacific_com:South_Pacific_Communities_kosrae_DNI_Jul)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_DNI_Mar (south_pacific_com:South_Pacific_Communities_kosrae_DNI_Mar)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_DNI_Nov (south_pacific_com:South_Pacific_Communities_kosrae_DNI_Nov)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_DNI_Sep (south_pacific_com:South_Pacific_Communities_kosrae_DNI_Sep)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_GHI_Apr (south_pacific_com:South_Pacific_Communities_kosrae_GHI_Apr)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_GHI_Dec (south_pacific_com:South_Pacific_Communities_kosrae_GHI_Dec)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_GHI_Jan (south_pacific_com:South_Pacific_Communities_kosrae_GHI_Jan)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_GHI_Jun (south_pacific_com:South_Pacific_Communities_kosrae_GHI_Jun)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_GHI_May (south_pacific_com:South_Pacific_Communities_kosrae_GHI_May)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_GHI_Oct (south_pacific_com:South_Pacific_Communities_kosrae_GHI_Oct)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

South_Pacific_Communities_kosrae_Slope (south_pacific_com:South_Pacific_Communities_kosrae_Slope)

The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

Suitability_rainfed_cereals_intermediate (biotest:Suitability_rainfed_cereals_intermediate)

Suitability_rainfed_irrigated_cereals_High (biotest:Suitability_rainfed_irrigated_cereals_High)

Suitability_rainfed_irrigated_pulses_high_inputs (biotest:Suitability_rainfed_irrigated_pulses_high_inputs)

Suitability_rainfed_irrigated_sugar_crops_High (biotest:Suitability_rainfed_irrigated_sugar_crops_High)

Suitability_rainfed_oil_crops_intermediate (biotest:Suitability_rainfed_oil_crops_intermediate)

Suitability_rainfed_roots_tubers_intermediate (biotest:Suitability_rainfed_roots_tubers_intermediate)

Suitability_rainfed_wheat_intermediate (biotest:Suitability_rainfed_wheat_intermediate)

Uruguay Daily Average GHI April (uruguay:Uruguay_ghi_april)

The second version of Uruguay's Solar Map provides annual and monthly averages of daily global irradiation at an horizontal surface. A statistical satellite based model is used to obtain hourly solar irradiation from GOES-East's visible channel imagery. This hourly information is used to compute the monthly and annual averages using a 14 years' local database of satellite images. The coeficients of the statistical model are tunned using the data from the National Solar Measurements' Network administrated by the National Public University's Solar Energy Laboratory (LES/UdelaR, Uruguay). The network is equipped with first class field pyranometers according to ISO 9060:1990 (Kipp & Zonen CMP6 or higher quality). Pyranometers are regularly calibrated against a secondary standard Kipp & Zonen CMP22 that the Solar Energy Laboratory keeps calibrated against the primary standard in the World Radiation Center in Davos, Switzerland. For more information check the website: http://les.edu.uy. Resume of the metadata: Name: Uruguay's Solar Map Version 2.0. Component: Solar Global irradiation at an horizontal plane. Temporal resolution: annual and monthly averages of daily irradiation in kWh/m2. Spatial resolution: about 1 km. Origin: satellite irradiation data based on GOES-East imagery. Satellite Statistic: GOES-East images from 01/01/2000 to 31/13/2013. Credits: Laboratorio de Energía Solar, Universidad de la República, Uruguay (http://les.edu.uy). Citation and methodology: ALONSO SUÁREZ, R.; ABAL, G.; SIRI, R.; MUSÉ, P. Brightness-dependent Tarpley model for global solar radiation estimation using GOES satellite images: application to Uruguay. Solar Energy 86, pag. 3205-3215, 2012.

Uruguay Daily Average GHI December (uruguay:Uruguay_ghi_december)

The second version of Uruguay's Solar Map provides annual and monthly averages of daily global irradiation at an horizontal surface. A statistical satellite based model is used to obtain hourly solar irradiation from GOES-East's visible channel imagery. This hourly information is used to compute the monthly and annual averages using a 14 years' local database of satellite images. The coeficients of the statistical model are tunned using the data from the National Solar Measurements' Network administrated by the National Public University's Solar Energy Laboratory (LES/UdelaR, Uruguay). The network is equipped with first class field pyranometers according to ISO 9060:1990 (Kipp & Zonen CMP6 or higher quality). Pyranometers are regularly calibrated against a secondary standard Kipp & Zonen CMP22 that the Solar Energy Laboratory keeps calibrated against the primary standard in the World Radiation Center in Davos, Switzerland. For more information check the website: http://les.edu.uy. Resume of the metadata: Name: Uruguay's Solar Map Version 2.0. Component: Solar Global irradiation at an horizontal plane. Temporal resolution: annual and monthly averages of daily irradiation in kWh/m2. Spatial resolution: about 1 km. Origin: satellite irradiation data based on GOES-East imagery. Satellite Statistic: GOES-East images from 01/01/2000 to 31/13/2013. Credits: Laboratorio de Energía Solar, Universidad de la República, Uruguay (http://les.edu.uy). Citation and methodology: ALONSO SUÁREZ, R.; ABAL, G.; SIRI, R.; MUSÉ, P. Brightness-dependent Tarpley model for global solar radiation estimation using GOES satellite images: application to Uruguay. Solar Energy 86, pag. 3205-3215, 2012.

Uruguay Daily Average GHI January (uruguay:Uruguay_ghi_january)

The second version of Uruguay's Solar Map provides annual and monthly averages of daily global irradiation at an horizontal surface. A statistical satellite based model is used to obtain hourly solar irradiation from GOES-East's visible channel imagery. This hourly information is used to compute the monthly and annual averages using a 14 years' local database of satellite images. The coeficients of the statistical model are tunned using the data from the National Solar Measurements' Network administrated by the National Public University's Solar Energy Laboratory (LES/UdelaR, Uruguay). The network is equipped with first class field pyranometers according to ISO 9060:1990 (Kipp & Zonen CMP6 or higher quality). Pyranometers are regularly calibrated against a secondary standard Kipp & Zonen CMP22 that the Solar Energy Laboratory keeps calibrated against the primary standard in the World Radiation Center in Davos, Switzerland. For more information check the website: http://les.edu.uy. Resume of the metadata: Name: Uruguay's Solar Map Version 2.0. Component: Solar Global irradiation at an horizontal plane. Temporal resolution: annual and monthly averages of daily irradiation in kWh/m2. Spatial resolution: about 1 km. Origin: satellite irradiation data based on GOES-East imagery. Satellite Statistic: GOES-East images from 01/01/2000 to 31/13/2013. Credits: Laboratorio de Energía Solar, Universidad de la República, Uruguay (http://les.edu.uy). Citation and methodology: ALONSO SUÁREZ, R.; ABAL, G.; SIRI, R.; MUSÉ, P. Brightness-dependent Tarpley model for global solar radiation estimation using GOES satellite images: application to Uruguay. Solar Energy 86, pag. 3205-3215, 2012.

Uruguay Daily Average GHI June (uruguay:Uruguay_ghi_june)

The second version of Uruguay's Solar Map provides annual and monthly averages of daily global irradiation at an horizontal surface. A statistical satellite based model is used to obtain hourly solar irradiation from GOES-East's visible channel imagery. This hourly information is used to compute the monthly and annual averages using a 14 years' local database of satellite images. The coeficients of the statistical model are tunned using the data from the National Solar Measurements' Network administrated by the National Public University's Solar Energy Laboratory (LES/UdelaR, Uruguay). The network is equipped with first class field pyranometers according to ISO 9060:1990 (Kipp & Zonen CMP6 or higher quality). Pyranometers are regularly calibrated against a secondary standard Kipp & Zonen CMP22 that the Solar Energy Laboratory keeps calibrated against the primary standard in the World Radiation Center in Davos, Switzerland. For more information check the website: http://les.edu.uy. Resume of the metadata: Name: Uruguay's Solar Map Version 2.0. Component: Solar Global irradiation at an horizontal plane. Temporal resolution: annual and monthly averages of daily irradiation in kWh/m2. Spatial resolution: about 1 km. Origin: satellite irradiation data based on GOES-East imagery. Satellite Statistic: GOES-East images from 01/01/2000 to 31/13/2013. Credits: Laboratorio de Energía Solar, Universidad de la República, Uruguay (http://les.edu.uy). Citation and methodology: ALONSO SUÁREZ, R.; ABAL, G.; SIRI, R.; MUSÉ, P. Brightness-dependent Tarpley model for global solar radiation estimation using GOES satellite images: application to Uruguay. Solar Energy 86, pag. 3205-3215, 2012.

Uruguay Daily Average GHI May (uruguay:Uruguay_ghi_may)

The second version of Uruguay's Solar Map provides annual and monthly averages of daily global irradiation at an horizontal surface. A statistical satellite based model is used to obtain hourly solar irradiation from GOES-East's visible channel imagery. This hourly information is used to compute the monthly and annual averages using a 14 years' local database of satellite images. The coeficients of the statistical model are tunned using the data from the National Solar Measurements' Network administrated by the National Public University's Solar Energy Laboratory (LES/UdelaR, Uruguay). The network is equipped with first class field pyranometers according to ISO 9060:1990 (Kipp & Zonen CMP6 or higher quality). Pyranometers are regularly calibrated against a secondary standard Kipp & Zonen CMP22 that the Solar Energy Laboratory keeps calibrated against the primary standard in the World Radiation Center in Davos, Switzerland. For more information check the website: http://les.edu.uy. Resume of the metadata: Name: Uruguay's Solar Map Version 2.0. Component: Solar Global irradiation at an horizontal plane. Temporal resolution: annual and monthly averages of daily irradiation in kWh/m2. Spatial resolution: about 1 km. Origin: satellite irradiation data based on GOES-East imagery. Satellite Statistic: GOES-East images from 01/01/2000 to 31/13/2013. Credits: Laboratorio de Energía Solar, Universidad de la República, Uruguay (http://les.edu.uy). Citation and methodology: ALONSO SUÁREZ, R.; ABAL, G.; SIRI, R.; MUSÉ, P. Brightness-dependent Tarpley model for global solar radiation estimation using GOES satellite images: application to Uruguay. Solar Energy 86, pag. 3205-3215, 2012.

Uruguay Daily Average GHI October (uruguay:Uruguay_ghi_october)

The second version of Uruguay's Solar Map provides annual and monthly averages of daily global irradiation at an horizontal surface. A statistical satellite based model is used to obtain hourly solar irradiation from GOES-East's visible channel imagery. This hourly information is used to compute the monthly and annual averages using a 14 years' local database of satellite images. The coeficients of the statistical model are tunned using the data from the National Solar Measurements' Network administrated by the National Public University's Solar Energy Laboratory (LES/UdelaR, Uruguay). The network is equipped with first class field pyranometers according to ISO 9060:1990 (Kipp & Zonen CMP6 or higher quality). Pyranometers are regularly calibrated against a secondary standard Kipp & Zonen CMP22 that the Solar Energy Laboratory keeps calibrated against the primary standard in the World Radiation Center in Davos, Switzerland. For more information check the website: http://les.edu.uy. Resume of the metadata: Name: Uruguay's Solar Map Version 2.0. Component: Solar Global irradiation at an horizontal plane. Temporal resolution: annual and monthly averages of daily irradiation in kWh/m2. Spatial resolution: about 1 km. Origin: satellite irradiation data based on GOES-East imagery. Satellite Statistic: GOES-East images from 01/01/2000 to 31/13/2013. Credits: Laboratorio de Energía Solar, Universidad de la República, Uruguay (http://les.edu.uy). Citation and methodology: ALONSO SUÁREZ, R.; ABAL, G.; SIRI, R.; MUSÉ, P. Brightness-dependent Tarpley model for global solar radiation estimation using GOES satellite images: application to Uruguay. Solar Energy 86, pag. 3205-3215, 2012.

Annual Mean Wind Speed Mexico at 80m (mexico:VelocidadAnualMexico80m)

Preliminary wind resource maps for Mexico were made by using hourly wind speed data for the year 2005, obtained by means of the MM5 program at 50 meters height every 9 kilometers. Extrapolation of wind speed at 80 meters was performed by using the power law with an exponent of 1/7. Subsequently, the velocity values obtained every 9 kilometers were interpolated each 1 kilometer. The wind resource maps are available on the IIE's website at 50 and 80 meters height on a monthly and yearly basis, for wind speed and power density. Detailed description: http://sag01.iie.org.mx/metadatos.htm Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=2032. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Mean Power Density South Africa West Cape 250m WASA May 2013 (southAfrica:WC_250m_PD_2013_130)

Mean power density P [Wm−2] @ 100 m above ground level for West Cape. Purpose This data set was created for the WASA project and the Department of Energy, South Africa. The wind resource maps were designed specifically for inclusion in GIS-based strategic environmental assessments (SEA) for wind power in Western Cape and parts of Northern and Eastern Cape. Methodology Reference is made to the information and documentation available from http://www.wasaproject.info Limitations The data set is limited by the operational envelopes of the wind atlas methodology and the WAsP models. The accuracy depends on a) the accuracy of the VNWA, which has been verified against the data from 10 WASA measurement masts, b) the WAsP microscale modelling and c) the input topographical data. In complex terrain (RIX > 5%), the wind resources may be significantly over-estimated by the WAsP microscale modelling. Above and close to built-up areas like cities, towns and villages, the results are less reliable. Close to and above forested areas, the results are also less reliable and should be interpreted and used accordingly. The data set was designed specifically for planning purposes and should be used with utmost care for design, development and detailed assessments of actual wind farms; where local, on-site meas-urements are strongly recommended. The wind resource maps are subject to change without notice if and when more accurate and reliable data, models and procedures become available. Available documentation The wind atlas methodology is described in the European Wind Atlas (1989); the application of WAsP in the program documentation, see www.wasp.dk. The First Verified Numerical Wind Atlas for South Africa is a product of the Wind Atlas for South Africa project and is described further on the WASA download pages http://wasadata.csir.co.za/wasa1/WASAData Acknowledgements SANEDI (South African National Energy Development Institute) for managing WASA CSIR Environmental Management Services for providing height contour data for Eastern Cape and Northern Cape. MetroGIS (Pty) Ltd. for providing height contour data for Western Cape in WAsP-compatible format. WASA Implementation team: UCT (CSAG), CSIR, SAWS, DTU Wind Energy and World in a Box Oy for Frogfoot development. Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=2031. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Mean wind speed South Africa West Cape 250m WASA May 2013 (southAfrica:WC_250m_U)

Mean wind speed U [ms−1] @ 100 m above ground level for West Cape. Purpose This data set was created for the WASA project and the Department of Energy, South Africa. The wind resource maps were designed specifically for inclusion in GIS-based strategic environmental assessments (SEA) for wind power in Western Cape and parts of Northern and Eastern Cape. Methodology Reference is made to the information and documentation available from http://www.wasaproject.info Limitations The data set is limited by the operational envelopes of the wind atlas methodology and the WAsP models. The accuracy depends on a) the accuracy of the VNWA, which has been verified against the data from 10 WASA measurement masts, b) the WAsP microscale modelling and c) the input topographical data. In complex terrain (RIX > 5%), the wind resources may be significantly over-estimated by the WAsP microscale modelling. Above and close to built-up areas like cities, towns and villages, the results are less reliable. Close to and above forested areas, the results are also less reliable and should be interpreted and used accordingly. The data set was designed specifically for planning purposes and should be used with utmost care for design, development and detailed assessments of actual wind farms; where local, on-site meas-urements are strongly recommended. The wind resource maps are subject to change without notice if and when more accurate and reliable data, models and procedures become available. Available documentation The wind atlas methodology is described in the European Wind Atlas (1989); the application of WAsP in the program documentation, see www.wasp.dk. The First Verified Numerical Wind Atlas for South Africa is a product of the Wind Atlas for South Africa project and is described further on the WASA download pages http://wasadata.csir.co.za/wasa1/WASAData Acknowledgements SANEDI (South African National Energy Development Institute) for managing WASA CSIR Environmental Management Services for providing height contour data for Eastern Cape and Northern Cape. MetroGIS (Pty) Ltd. for providing height contour data for Western Cape in WAsP-compatible format. WASA Implementation team: UCT (CSAG), CSIR, SAWS, DTU Wind Energy and World in a Box Oy for Frogfoot development. Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=2031. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

World Database on Protected Areas World polygon UNEP 2012 (IUCN:WDPA_polygon)

The World Database on Protected Areas (WDPA) is the most comprehensive spatial dataset on the world's marine and terrestrial protected areas, produced through a joint initiative of the International Union for the Conservation of Nature (IUCN) and the United National Environment Programme (UNEP). The WDPA contains the UN List of protected areas (official national data) as well as authoritative information sourced by non-governmental organizations, academic institutions, international convention secretariats and many others. The WDPA is used for reporting on global indicators and trends, ecological gap analysis, environmental impact analysis and is increasingly used for private sector decision-making. The WDPA is hosted and managed at the UNEP World Conservation Monitoring Centre.

VAISALA Global Wind Dataset 5km onshore wind speed at 80m height units in m/s (_3tier:Wind_Speed_Global_5km_80m_3TIER)

VAISALA Global Wind Dataset 5km onshore wind speed at 80m height units in m/s. VAISALA Global Wind Dataset provides average annual wind speed at 80 meters above ground. Average values are based on over 10 years of hourly data created through advanced computer model simulations. VAISALA created this dataset using a combination of statistical methods and physics-based numerical weather prediction models, which create realistic wind fields throughout the world by simulating the interaction between the entire atmosphere and the Earth’s surface. The wind speed dataset validated well when compared with more than 4000 NCEP-ADP networks stations (validation paper available here: http://www.vaisala.com/en/energy/Documents/WEA-ERG-3TIER-Global%20Wind%20Dataset.pdf). The information provided in the Global Atlas is meant to inform high-level policy debate (identification of opportunity areas for further prospection, preliminary assessment of technical potentials), or to perform market screening (cross referencing the resource information with policy information). It is suitable for decision-making activities, excluding financial commitments. It is a subset of a more detailed, long-term dataset, which includes additional hourly wind information such as wind direction, power density, and wind distribution. VAISALA can provide this information as well as information at higher spatial and temporal resolutions in addition to other customized energy services to facilitate project-specific or regional development, financial planning, and energy trading and scheduling. By using this dataset, the user accepts VAISALA Terms and Conditions shown here: http://globalatlas.irena.org/VAISALA-terms-conditions.aspx Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=3032. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

3TIER’s Global Solar Dataset 3km with units in W/m² (training:_3tier_global_ghi)

3TIER’s Global Solar Dataset 3km with units in W/m² 3TIER’s Global Solar Dataset provides average annual GHI at a 3km spatial resolution. Average values are based on more than 10 years of hourly GHI data and derived from actual, half-hourly, high-resolution visible satellite imagery observations via the broadband visible wavelength channel at a 2 arc minute resolution. 3TIER processed this information using on a combination of in-house research and algorithms published in peer-reviewed scientific literature. The dataset validated well when compared with observations from 120 geographically distributed surface stations around the globe (validation paper available here: http://www.3tier.com/static/ttcms/us/documents/publications/validations/3TIER_Global_Solar_Validation.pdf). The information provided in the Global Atlas is meant to inform high-level policy debate (identification of opportunity areas for further prospection, preliminary assessment of technical potentials), or to perform market screening (cross referencing the resource information with policy information). It is suitable for decision-making activities, excluding financial commitments. It is a subset of a more detailed, long-term dataset, which includes hourly values of GHI, DNI, and other weather variables. 3TIER can provide this information and other customized services to facilitate project-specific or regional development, financial planning, and energy scheduling. By using this dataset, the user accepts 3TIER's Terms and Conditions shown here: http://irena.org/globalatlas/demo/3TIER-terms-conditions.aspx.

Accessible Potential High Temperature Spain (spain:accessible_potential_high_temperature)

This layer shows potential areas for medium temperature geothermal systems with temperatures greater than 150 degrees Celsius. The map highlights several areas and estimates the accessible potential for each area in GWh The full details for this map and the methodology with which they have been developed is contained in the report: Evaluacion Del Potencial De Energia Geothermica, Estudio Technico Per 2011 – 2020 (p 167). http://www.idae.es/uploads/documentos/documentos_11227_e9_geotermia_A_db72b0ac.pdf

Accessible Potential Medium Temperature Spain (spain:accessible_potential_medium_temperature)

This layer shows potential areas for medium temperature geothermal systems with temperatures between 100 and 150 degrees Celsius. The map highlights several areas and estimates the accessible potential for each area in GWh The full details for this map and the methodology with which they have been developed is contained in the report: Evaluacion Del Potencial De Energia Geothermica, Estudio Technico Per 2011 – 2020 (p 167). http://www.idae.es/uploads/documentos/documentos_11227_e9_geotermia_A_db72b0ac.pdf

active_volcanoes (chile_geothermal:active_volcanoes)

Alberta Geothermal Landuse Dataset (canada:alberta_geothermal_landuse_dataset)

Alberta Geothermal Favourability Map The ‘geothermal favourability rating’ is based on geothermal gradients and ambient temperatures. This rating provides a geothermal assessment based on temperature requirements of current technology, and is consistent with geothermal favourability mapping projects completed by Northwest Territories Environment and Natural Resources. This dataset was developed by: Canadian Geothermal Energy Association P. O. Box 1462 St. M, Calgary, Alberta, T2P 2L6, Canada Phone: (403) 801 6805, info@cangea.ca -­‐ www.cangea.ca For the complete report please visit: http://irena.masdar.ac.ae/docs/Geothermal_Favourability_Map_of_Alberta_following_a_Global_Protocol_Methods_and_Data_Sources.pdf

areas_not_feasible_for_agriculture (tanzania:areas_not_feasible_for_agriculture)

australia_geothermal_10000m (wcs_test:australia_geothermal_10000m)

Geothermal_Basement temperature at 3500m m Australia HotDryRocks (australia:australia_geothermal_3500m)

These maps show the average predicted temperature of Australian basement rocks at one kilometer intervals between 3-10 kilometers depth. The maps are direct indicators of the potential for Engineered Geothermal Systems development. A description of the methodology underpinning the maps is detailed in a Global Protocol for estimating and mapping global EGS potential, accessible here: http://pubs.geothermal-library.org/lib/grc/1028662.pdf The specific data sets and assumptions that have been employed in developing these maps may be obtained by directly contacting the data owner: graeme.beardsmore@hotdryrocks.com

Geothermal_Basement temperature at 5500m m Australia HotDryRocks (australia:australia_geothermal_5500m)

These maps show the average predicted temperature of Australian basement rocks at one kilometer intervals between 3-10 kilometers depth. The maps are direct indicators of the potential for Engineered Geothermal Systems development. A description of the methodology underpinning the maps is detailed in a Global Protocol for estimating and mapping global EGS potential, accessible here: http://pubs.geothermal-library.org/lib/grc/1028662.pdf The specific data sets and assumptions that have been employed in developing these maps may be obtained by directly contacting the data owner: graeme.beardsmore@hotdryrocks.com

Geothermal_Basement temperature at 7500m m Australia HotDryRocks (australia:australia_geothermal_7500m)

These maps show the average predicted temperature of Australian basement rocks at one kilometer intervals between 3-10 kilometers depth. The maps are direct indicators of the potential for Engineered Geothermal Systems development. A description of the methodology underpinning the maps is detailed in a Global Protocol for estimating and mapping global EGS potential, accessible here: http://pubs.geothermal-library.org/lib/grc/1028662.pdf The specific data sets and assumptions that have been employed in developing these maps may be obtained by directly contacting the data owner: graeme.beardsmore@hotdryrocks.com

Geothermal_Basement temperature at 9500m m Australia HotDryRocks (australia:australia_geothermal_9500m)

These maps show the average predicted temperature of Australian basement rocks at one kilometer intervals between 3-10 kilometers depth. The maps are direct indicators of the potential for Engineered Geothermal Systems development. A description of the methodology underpinning the maps is detailed in a Global Protocol for estimating and mapping global EGS potential, accessible here: http://pubs.geothermal-library.org/lib/grc/1028662.pdf The specific data sets and assumptions that have been employed in developing these maps may be obtained by directly contacting the data owner: graeme.beardsmore@hotdryrocks.com

Available Potential High Temperature Spain (spain:available_potential_high_temperature)

This layer shows potential areas for medium temperature geothermal systems with temperatures greater than 150 degrees Celsius. The map highlights several areas and estimates the available potential for each area in GWh The full details for this map and the methodology with which they have been developed is contained in the report: Evaluacion Del Potencial De Energia Geothermica, Estudio Technico Per 2011 – 2020 (p 167). http://www.idae.es/uploads/documentos/documentos_11227_e9_geotermia_A_db72b0ac.pdf

Available Potential Medium Temperature Spain (spain:available_potential_medium_temperature)

This layer shows potential areas for medium temperature geothermal systems with temperatures between 100 and 150 degrees Celsius. The map highlights several areas and estimates the available potential for each area in GWh The full details for this map and the methodology with which they have been developed is contained in the report: Evaluacion Del Potencial De Energia Geothermica, Estudio Technico Per 2011 – 2020 (p 167). http://www.idae.es/uploads/documentos/documentos_11227_e9_geotermia_A_db72b0ac.pdf

Average wind speed in fall at 100m in Peru (peru:average_wind_speed_at_100_m_fall)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Average wind speed in summer at 100m in Peru (peru:average_wind_speed_at_100_m_summer)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Annual Average Wind Speed at 100m in Peru (peru:average_wind_speed_at_100_m_year)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Average wind speed in spring at 50m in Peru (peru:average_wind_speed_at_50_m_spring)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Average wind speed in winter at 50m in Peru (peru:average_wind_speed_at_50_m_winter)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Average wind speed in fall at 80m in Peru (peru:average_wind_speed_at_80_m_fall)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Average wind speed in summer at 80m in Peru (peru:average_wind_speed_at_80_m_summer)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Annual Average Wind Speed at 80m in Peru (peru:average_wind_speed_at_80_m_year)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

cassava_cons_agriculture_high_input_agro_climatic_suitability (tanzania:cassava_cons_agriculture_high_input_agro_climatic_suitability)

cassava_cons_agriculture_low_input_agro_climatic_suitability (tanzania:cassava_cons_agriculture_low_input_agro_climatic_suitability)

cassava_tillage_high_input_agro_climatic_suitability (tanzania:cassava_tillage_high_input_agro_climatic_suitability)

cassava_tillage_low_input_agro_climatic_suitability (tanzania:cassava_tillage_low_input_agro_climatic_suitability)

crop_zones (tanzania:crop_zones)

Crop suitability index (class) for high input level rain-fed cassava (gaez:csindex_high_input_level_rain-fed_cassava)

Crop suitability index (class) estimated for high input level rain-fed cassava. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for high input level rain-fed jatropha (gaez:csindex_high_input_level_rain-fed_jatropha)

Crop suitability index (class) estimated for high input level rain-fed jatropha. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for high input level rain-fed miscanthus (gaez:csindex_high_input_level_rain-fed_miscanthus)

Crop suitability index (class) estimated for high input level rain-fed miscanthus. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for high input level rain-fed rape (gaez:csindex_high_input_level_rain-fed_rape)

Crop suitability index (class) estimated for high input level rain-fed rape. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for high input level rain-fed sorghum (gaez:csindex_high_input_level_rain-fed_sorghum)

Crop suitability index (class) estimated for high input level rain-fed sorghum. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for high input level rain-fed sugarbeet (gaez:csindex_high_input_level_rain-fed_sugarbeet)

Crop suitability index (class) estimated for high input level rain-fed sugarbeet. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Referencia FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for high input level rain-fed sunflower (gaez:csindex_high_input_level_rain-fed_sunflower)

Crop suitability index (class) estimated for high input level rain-fed sunflower. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for high input level rain-fed wheat (gaez:csindex_high_input_level_rain-fed_wheat)

Crop suitability index (class) estimated for high input level rain-fed wheat. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for low input level rain-fed cassava (gaez:csindex_low_input_level_rain-fed_cassava)

Crop suitability index (class) estimated for low input level rain-fed cassava. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for low input level rain-fed jatropha (gaez:csindex_low_input_level_rain-fed_jatropha)

Crop suitability index (class) estimated for low input level rain-fed jatropha. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for low input level rain-fed miscanthus (gaez:csindex_low_input_level_rain-fed_miscanthus)

Crop suitability index (class) estimated for low input level rain-fed miscanthus. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for low input level rain-fed rape (gaez:csindex_low_input_level_rain-fed_rape)

Crop suitability index (class) estimated for low input level rain-fed rape. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for low input level rain-fed sorghum (gaez:csindex_low_input_level_rain-fed_sorghum)

Crop suitability index (class) estimated for low input level rain-fed sorghum. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for low input level rain-fed sugarbeet (gaez:csindex_low_input_level_rain-fed_sugarbeet)

Crop suitability index (class) estimated for low input level rain-fed sugarbeet. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for low input level rain-fed sunflower (gaez:csindex_low_input_level_rain-fed_sunflower)

Crop suitability index (class) estimated for low input level rain-fed sunflower. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Crop suitability index (class) for low input level rain-fed wheat (gaez:csindex_low_input_level_rain-fed_wheat)

Crop suitability index (class) estimated for low input level rain-fed wheat. The model has been applied considering the average climate of baseline period 1961-1990 Crop suitability index (SI) reflects suitability levels and distributions within grid cells by classes based on SI values between 0 and 100. Reference FAO/IIASA, 2010. Global Agro-ecological Zones (GAEZ v3.0). FAO, Rome, Italy and IIASA, Laxenburg, Austria. www.fao.org/nr/gaez Contacts FAO-UN John Latham - Senior Environment Officer - GAEZ@fao.org Renato Cumani - Environment Officer - GAEZ@fao.org IIASA Guenther Fischer - Senior Research Scholar - fisher@iiasa.ac.at Harrij van Velthuizen - Senior Research Scholar - velt@iiasa.ac.at

Mozambique Solar BHI Average August [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_bhi_aug)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct. Aug. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar BHI Average February [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_bhi_feb)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct. Feb. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar BHI Average July [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_bhi_jul)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct. Jul. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar BHI Average March [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_bhi_mar)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct. Mar. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar BHI Average November [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_bhi_nov)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct. Nov. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar BHI Average September [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_bhi_sep)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct. Sep. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DHI Average April [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dhi_apr)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Diffuse. Apr. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DHI Average December [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dhi_dec)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Diffuse. Dec. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DHI Average January [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dhi_jan)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Diffuse. Jan. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DHI Average June [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dhi_jun)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Diffuse. Jun. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DHI Average May [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dhi_may)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Diffuse. May. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DHI Average October [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dhi_oct)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Diffuse. Oct. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DHI 10 Years Daily Average [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dhi_year)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Diffuse. Average year. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DNI Average August [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dni_aug)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct Normal (DNI). Aug. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DNI Average February [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dni_feb)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct Normal (DNI). Feb. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DNI Average July [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dni_jul)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct Normal (DNI). Jul. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DNI Average March [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dni_mar)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct Normal (DNI). Mar. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DNI Average November [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dni_nov)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct Normal (DNI). Nov. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar DNI Average September [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_dni_sep)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Direct Normal (DNI). Sep. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar GHI Average April [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_ghi_apr)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Global. Apr. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar GHI Average December [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_ghi_dec)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Global. Dec. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar GHI Average January [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_ghi_jan)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Global. Jan. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar GHI Average June [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_ghi_jun)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Global. Jun. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar GHI Average May [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_ghi_may)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Global. May. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar GHI Average October [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_ghi_oct)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Global. Oct. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Mozambique Solar GHI 10 Years Daily Average [2004-2013] 3km Eduardo Mondlane University (mozambique_solar:daily_irradiation_ghi_year)

Surface solar irradiation, or daily solar exposure in Mozambique in Wh/m2. Global. Average year. 10-years average (2004-2013) of monthly mean of daily irradiation received on a horizontal plane (or a plane always facing the sun if DNI). Copyright 2014 MINES ParisTech, University Eduardo Mondlane, Mozambique Meteorological Institute MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim-3 database. The HelioClim-3 irradiations are combined with estimates of the irradiation that should be observed if the sky were clear at these instants.The estimates of clear-sky irradiation are provided by the McClear model. A monthly irradiation is computed only if at least 25 daily irradiations are valid in the month. To complete the month, the irradiation of a missing day is computed by taking into account the mean value of the valid days and the daily irradiation at the top of atmosphere for this missing day. A day is valid if the database contains at least one 15-min irradiation for this day. Gaps in a day are filled by taking into account the available 15-min irradiation and the 15-min irradiation at the top of atmosphere. The other irradiation components (direct, diffuse) received on an horizontal or plane normal to sun rays are then computed using a published empirical model. HelioClim-3 data and diffuse and direct components on any plane are provided on the Web via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2004. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production.The French company Transvalor is in charge of the SoDa Service and provides also a series of user-tailored services, such as maps similar to those for Mozambique. MINES ParisTech and Transvalor have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear model is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/free-web-services/radiation/mcclear MACC projects: http://www.gmes-atmosphere.eu/

Comparison between estimated PV and diesel minigrid costs (Euro/kWh) Africa JRC (JRC:diffdipv2012_wgs84)

The map/data illustrates an economic comparison of the two off-grid options (diesel generator or PV). Negative values indicate the location where diesel is more economically advantageous, while positive values indicate where PV options are cheaper. The different policies prevailing in the various African countries on the fuel taxation/fuel subsidies are remarkable. The diesel versus PV map/data reveals that the effects of fuel subsidies play a crucial role: they change the picture of the most economically viable option dramatically. Relevant publications: Szabó, S., Bódis, K., Huld, T., Moner-Girona, M., 2013, Sustainable energy planning: Leapfrogging the energy poverty gap in Africa, Renewable and Sustainable Energy Reviews, 28 (2013) 500-509. URL: http://dx.doi.org/10.1016/j.rser.2013.08.044 Huld, T., Müller, R., Gambardella, A., 2012, A new solar radiation database for estimating PV performance in Europe and Africa. Solar Energy, 86, 1803-1815. URL: http://dx.doi.org/10.1016/j.solener.2012.03.006 Szabó, S., Bódis, K., Huld, T., Moner-Girona, M., 2011, Energy solutions in rural Africa: mapping electrification costs of distributed solar and diesel generation versus grid extension, Environmental Research Letters, Volume 6, Issue 3, July 2011, Article number034002, DOI: 10.1088/1748-9326/6/3/034002. URL: http://iopscience.iop.org/1748-9326/6/3/034002/ Wagner, A., Becker, D., Dicke, B., S. Ebert, S., Ragab, A., International Fuel Prices 2010/2011, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Sector Project "Transport Policy Advisory Services", Division 44 - Water, Energy, Transport, (2012). http://www.giz.de/Themen/en/dokumente/giz-en-IFP2010.pdf Nelson, A., 2008, Estimated travel time to the nearest city of 50,000 or more people in year 2000. Global Environment Monitoring Unit, Joint Research Centre of the European Commission (Ispra, Italy), http://bioval.jrc.ec.europa.eu/products/gam/index.htm

Dry Spell Zone (tanzania:dry_spell_zone)

Estimated costs of electricity (Euro/kWh) delivered by a diesel generator using the diesel price for each country and taking into account the cost of diesel transportation Africa JRC (JRC:eurdikwh2012_wgs84)

Diesel generators have been the traditional solution to decentralized electrification needs. For off-grid applications, they present lower up-front capital costs per kilowatt installed; however, the dramatic increase of fuel costs in recent years and the cost of transport to remote areas greatly diminish the low capital cost advantage of the diesel option. In Africa the transport infrastructure is underdeveloped which has a severe consequence: the transport costs faced by African countries are almost twice as high as the world average. A global map of accessibility developed by the JRC formed this second component for the genset electricity cost calculations. To estimate the location specific operating costs for diesel gensets, the country-based diesel prices have been combined with the travel time data (derived from the accessibility map) integrating the transport costs. Relevant publications: Szabó, S., Bódis, K., Huld, T., Moner-Girona, M., 2013, Sustainable energy planning: Leapfrogging the energy poverty gap in Africa, Renewable and Sustainable Energy Reviews, 28 (2013) 500-509. URL: http://dx.doi.org/10.1016/j.rser.2013.08.044 Szabó, S., Bódis, K., Huld, T., Moner-Girona, M., 2011, Energy solutions in rural Africa: mapping electrification costs of distributed solar and diesel generation versus grid extension, Environmental Research Letters, Volume 6, Issue 3, July 2011, Article number034002, DOI: 10.1088/1748-9326/6/3/034002. URL: http://iopscience.iop.org/1748-9326/6/3/034002/ Wagner, A., Becker, D., Dicke, B., S. Ebert, S., Ragab, A., International Fuel Prices 2010/2011, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Sector Project "Transport Policy Advisory Services", Division 44 - Water, Energy, Transport, (2012). http://www.giz.de/Themen/en/dokumente/giz-en-IFP2010.pdf Ebert, S., Metschies, D. G. P., Schmid, D., Wagner, A., 2009, International Fuel Prices 2009, In: Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ) GmbH (Ed.), Federal Ministry for Economic Cooperation and Development (BMZ), Eschborn, Germany, 2009. Nelson, A., 2008, Estimated travel time to the nearest city of 50,000 or more people in year 2000. Global Environment Monitoring Unit, Joint Research Centre of the European Commission (Ispra, Italy), http://bioval.jrc.ec.europa.eu/products/gam/index.htm United Nations University, 2007, The Significance of Transport Costs in Africa Policy Brief n.5 URL: http://archive.unu.edu/publications/briefs/policy-briefs/2007/pb05-07.pdf

Excluded Areas (tanzania:excluded_areas)

exploration_concession_may2015 (chile_geothermal:exploration_concession_may2015)

World country borders GADM (irena:gadm_country_borders)

The global country boundaries layer has been produced using the Global Administrative Boundaries (GADM) database which is a comprehensive collection of spatial information on administrative areas all over the world. http://gadm.org/ The comprehensive GADM database covers countries and lower level subdivisions such as states, provinces, and counties.

Israel Annual Average GHI 2008 (israel:ghi_9_stations_Israel)

This dataset contains the annual average Solar Radiation (GHI) from 9 stations in Israel. A 20-year database of meteorological measurements from the Negev sites: Arad, Beersheba, Besor Farm, Eilat, Hatzeva, Mitzpe Ramon, Sede Boqer, Sedom and Yotvata was employed to synthesize a set of updated Typical Meteorological Year data files (TMY v.5) based on the direct beam component, and the archived hourly data. Report on the Solar Radiation Maps of the Negev: http://irena.masdar.ac.ae/docs/Israel_solar_radiation_maps_of_the_Negev.pdf Report on the Data Processing for the Negev Radiation Survey: Part III – Typical Meteorological Year (TMY), Version 5: http://irena.masdar.ac.ae/docs/Israel_data_processing_for_the_Negev_radiation_survey.pdf

Global Geothermal Points Heat Flow IHFC 2015 (irena:global_heatflow_2015)

The Global heat flow data are maintained by the International Heat Flow Commission (IHFC) of the International Association of Seismology and Physics of the Earth's Interior (IASPEI). The new global compilation covers over 50,000 heat flow data points. The contour lines and a raster have been developed from this data with help from the Royal Melbourne Institute of Technology (RMIT) in Melbourne, Australia. Original website http://www.ihfc-iugg.org/products/global-heat-flow-database

global_wgs84 (testing:global_wgs84)

GOCE Bouguer Anomaly World (gravity:goce_bouguer_anomaly)

GOCE Bouguer anomaly: calculation height =8000m above reference ellipsoid. Unit: mGal. This field differs from the GOCE free air disturbance by subtracting the effect of global elevated land masses and the effect of ocean basins filled with water. This field reflects to a great deal the thickness variations of the uppermost layer of the stratified earth, the crust. The crust has an average lower density than the underlying mantle, and therefore a thin crust produces an increased positive Bouguer anomaly. The greater amplitude of this signal masks the superficial density variations due to the geologic density variations seen in the free air gravity disturbance. Details on page Gravity_for_Geothermics at http://www.lithoflex.org/IRENA/. References Balmino, G., N. Vales, S. Bonvalot , A. Briais, 2012. Spherical harmonic modelling to ultra-high degree of Bouguer and isostatic anomalies, J Geod, 86, 499–520, DOI 10.1007/s00190-011-0533-4 Barthelmes, F., 2013. Definition of Functionals of the Geopotential and Their Calculation from Spherical Harmonics Models, Scientific Technical Report STR09/02, Revised Edition, January 2013, Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Potsdam, Germany, http://icgem.gfz-potsdam.de/ICGEM/, DOI: 10.2312/GFZ.b103-0902-26 Braitenberg, C., 2014. Exploration of tectonic structures with GOCE in Africa and across-continents. International Journal of Applied Earth Observation and Geoinformation, in press doi:10.1016/j.jag.2014.013. Bucha, B., Janak, J., 2013. A MATLAB-based graphical user interface program for computing functionals of the geopotential up to ultra-high degrees and orders. Computers & Geosciences 56, 186-196, http://dx.doi.org/10.1016/j.cageo.2013.03.012. Claessens, S.J. , Hirt, C., 2013. Ellipsoidal topographic potential: New solutions for spectral forward gravity modeling of topography with respect to a reference ellipsoid, Journal of Geophysical Research - Solid Earth, Vol. 118(11), 5991-6002, doi: 10.1002/2013JB010457. Earth2012, 2014. Link: http://geodesy.curtin.edu.au/research/models/Earth2012/, Accessed on 20.09.2014. Floberghagen, R., Fehringer, M., Lamarre, D., Muzi, D., Frommknecht, B., Steiger, C., Piñeiro, J., da Costa, A., 2011. Mission design, operation and exploitation of the gravity field and steady-state ocean circulation explorer (GOCE) mission. Journal of Geodesy 85, 749-758. Hirt, C., Kuhn, M., 2012. Evaluation of high-degree series expansions of the topographic potential to higher-order powers, Journal Geophysical Research. (JGR) Solid Earth, 117, B12407, doi:10.1029/2012JB009492. Kuhn, M., Featherstone, W.E., Kirby, J.F., 2009. Complete spherical Bouguer gravity anomalies over Australia. Aust. J. Earth Sci., 56, 213–223. Pail R, Bruinsma S, Migliaccio F., Förste C., Goiginger H., Schuh W.-D, Höck E, Reguzzoni M., Brockmann J. M, Abrikosov O., Veicherts M., Fecher T., Mayrhofer R., Krasbutter I., Sansó, F., Tscherning, C.C. , 2011. First GOCE gravity field models derived by three different approaches. J Geod, 85/11: 819-843, doi: 10.1007/s00190-011-0467-x. Reguzzoni, M., Sampietro, D., 2014. GEMMA: An Earth crustal model based on GOCE satellite data, International Journal of Applied Earth Observation and Geoinformation,in press, avialbale online 10 May 2014, ISSN 0303-2434, http://dx.doi.org/10.1016/j.jag.2014.04.002. Time-wise solution- release 5 documentation on ESA-GOCE homepage, 2014. Link: https://earth.esa.int/documents/10174/1604019/GO_CONS_EGM_GCF_2_TIM_R5_DataSheet.pdf, Authors: Graz University of Technology, Institute for Theoretical and Satellite Geodesy; University of Bonn, Institute of Geodesy and Geoinformation; TU München, Institute of Astronomical and Physical Geodesy. Accessed on 20.09.2014. Torge, W., 1989. Gravimetry. Berlin, De Gruyter, ISBN 3-11-010702-3 Authors: Carla Braitenberg, Department of Mathematics and Earth Sciences, University of Trieste. Email: berg@units.it (Corresponding author) Christian Hirt, The Institute for Geoscience Research, Curtin University, Perth, Email: c.hirt@curtin.edu.au Blazej Bucha, Department of Theoretical Geodesy, Slovak University of Technology, Bratislava, Email: blazej.bucha@stuba.sk

Annual Specific Production at 100m a.g.l./a.s.l. (italy:grid_nazionale_prod100)

Source: RSE S.p.A. Website: www.rse-web.it Description: Annual mean wind speed and specific production maps at four levels (25, 50, 75 and 100 m) above ground and sea, with 1 km spatial resolution, are available in a WebGIS for navigation and free download. The maps have been calculated by means of the WINDS model of Genoa University. The onshore maps have been calibrated with more than 200 met stations data, the offshore maps with satellite data and few available direct measurements. Constraints maps can be overlapped. A “Performance Calculation” tool allows the user to perform a technical-economical evaluation of hypothesis of wind farms based on the dataset of the Wind Atlas. Detailed description: http://irena.masdar.ac.ae/docs/OWEMES_Italian_wind_atlas_english_version_paper.pdf Original website: http://atlanteeolico.rse-web.it/viewer.htm Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=3034. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Annual Specific Production at 50m a.g.l./a.s.l. (italy:grid_nazionale_prod50)

Source: RSE S.p.A. Website: www.rse-web.it Description: Annual mean wind speed and specific production maps at four levels (25, 50, 75 and 100 m) above ground and sea, with 1 km spatial resolution, are available in a WebGIS for navigation and free download. The maps have been calculated by means of the WINDS model of Genoa University. The onshore maps have been calibrated with more than 200 met stations data, the offshore maps with satellite data and few available direct measurements. Constraints maps can be overlapped. A “Performance Calculation” tool allows the user to perform a technical-economical evaluation of hypothesis of wind farms based on the dataset of the Wind Atlas. Detailed description: http://irena.masdar.ac.ae/docs/OWEMES_Italian_wind_atlas_english_version_paper.pdf Original website: http://atlanteeolico.rse-web.it/viewer.htm Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=3034. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Annual Mean WindSpeed at 100m a.g.l./a.s.l. (italy:grid_nazionale_vento100)

Source: RSE S.p.A. Website: www.rse-web.it Description: Annual mean wind speed and specific production maps at four levels (25, 50, 75 and 100 m) above ground and sea, with 1 km spatial resolution, are available in a WebGIS for navigation and free download. The maps have been calculated by means of the WINDS model of Genoa University. The onshore maps have been calibrated with more than 200 met stations data, the offshore maps with satellite data and few available direct measurements. Constraints maps can be overlapped. A “Performance Calculation” tool allows the user to perform a technical-economical evaluation of hypothesis of wind farms based on the dataset of the Wind Atlas. Detailed description: http://irena.masdar.ac.ae/docs/OWEMES_Italian_wind_atlas_english_version_paper.pdf Original website: http://atlanteeolico.rse-web.it/viewer.htm Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=3034. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Annual Mean WindSpeed at 50m a.g.l./a.s.l. (italy:grid_nazionale_vento50)

Source: RSE S.p.A. Website: www.rse-web.it Description: Annual mean wind speed and specific production maps at four levels (25, 50, 75 and 100 m) above ground and sea, with 1 km spatial resolution, are available in a WebGIS for navigation and free download. The maps have been calculated by means of the WINDS model of Genoa University. The onshore maps have been calibrated with more than 200 met stations data, the offshore maps with satellite data and few available direct measurements. Constraints maps can be overlapped. A “Performance Calculation” tool allows the user to perform a technical-economical evaluation of hypothesis of wind farms based on the dataset of the Wind Atlas. Detailed description: http://irena.masdar.ac.ae/docs/OWEMES_Italian_wind_atlas_english_version_paper.pdf Original website: http://atlanteeolico.rse-web.it/viewer.htm Please access he data quality information for this dataset at: http://globalatlas.irena.org/dqif/publishdata.aspx?datasetid=3034. Also for additional information please download the data quality framework report at: goo.gl/T2wMaq

Global Geothermal Contour Lines Heat Flow IHFC 2015 (irena:heatflow_2015_contours)

The Global heat flow data are maintained by the International Heat Flow Commission (IHFC) of the International Association of Seismology and Physics of the Earth's Interior (IASPEI). The new global compilation covers over 50,000 heat flow data points. The contour lines and a raster have been developed from this data with help from the Royal Melbourne Institute of Technology (RMIT) in Melbourne, Australia. Original website http://www.ihfc-iugg.org/products/global-heat-flow-database

inland_water_bodies (tanzania:inland_water_bodies)

Intermediate Map Grid Connected 100Km 2013 (ecowas_demo:intermediate_pv_grid_100km)

Intermediate Map Grid Connected 100Km 2013 for Solar PV opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 100 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Grid Connected 20Km 2013 (ecowas_demo:intermediate_pv_grid_20km)

Intermediate Map Grid Connected 20Km 2013 for Solar PV opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 20 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Grid Connected 75Km 2013 (ecowas_demo:intermediate_pv_grid_75km)

Intermediate Map Grid Connected 75Km 2013 for Solar PV opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 75 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Off-Grid 150Km 2013 (ecowas_demo:intermediate_pv_offgrid_150km)

Intermediate Map Off-Grid 150Km 2013 for Solar PV opportunity scores for offgrid applications in the ECOWAS region. Illustration for the following parameters: - further than 150 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Off-Grid 50Km 2013 (ecowas_demo:intermediate_pv_offgrid_50km)

Intermediate Map Off-Grid 50Km 2013 for Solar PV opportunity scores for offgrid applications in the ECOWAS region. Illustration for the following parameters: - further than 50 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Population 2013 (ecowas_demo:intermediate_pv_population_grid)

Intermediate Map Population 2013 for Solar PV opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - a population density below 500 hab/km2; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Wind Elevation 2013 (ecowas_demo:intermediate_wind_elevation)

Intermediate Map Elevation 2013 for Wind opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - elevation below 2000m; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Wind Grid Connected 150Km (ecowas_demo:intermediate_wind_grid_150km)

Intermediate Map Grid Connected 150Km 2013 for Wind opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 150 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Wind Grid Connected 75km 2013 (ecowas_demo:intermediate_wind_grid_75km)

Intermediate Map Grid Connected 75Km 2013 for Wind opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 75 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Wind Off-Grid 150Km 2013 (ecowas_demo:intermediate_wind_offgrid_150km)

Intermediate Map Off-Grid 150Km 2013 for Wind opportunity scores for offgrid applications in the ECOWAS region. Illustration for the following parameters: - further than 150 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Wind Off-Grid 75Km 2013 (ecowas_demo:intermediate_wind_offgrid_75km)

Intermediate Map Off-Grid 75Km 2013 for Wind opportunity scores for offgrid applications in the ECOWAS region. Illustration for the following parameters: - further than 75 km from the existing grid; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Intermediate Map Wind WindSpeed 2013 (ecowas_demo:intermediate_wind_windspeed)

Intermediate Map Wind Speed 2013 for Wind opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - for a wind speed starting from 4.5 m/s, suitable at 7 m/s and beyond; The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Korea – Temperature at 2 km depth for enhanced geothermal systems by KIGAM (korea_geothermal:korea_temp_at_2km_depth)

These layers show the temperature at depths (1 – 5km) across Korea indicating several areas in the country that could be probable for enhanced geothermal systems (EGS). The layers are a result of a study conducted in 2010 by Yoonho Song et al., of the Korean Institute for Geosciences and Mineral Resources. Access the full report (in Korean) for more: http://tinyurl.com/zfuwvve

Korea – Temperature at 4 km depth for enhanced geothermal systems by KIGAM (korea_geothermal:korea_temp_at_4km_depth)

These layers show the temperature at depths (1 – 5km) across Korea indicating several areas in the country that could be probable for enhanced geothermal systems (EGS). The layers are a result of a study conducted in 2010 by Yoonho Song et al., of the Korean Institute for Geosciences and Mineral Resources. Access the full report (in Korean) for more: http://tinyurl.com/zfuwvve

kth_annual_windspeed_africa (kth:kth_annual_windspeed_africa)

Length of Growing Period (tanzania:length_growing_period)

Global Population Database World 1km ORNL 2011 (irena:lspop20111)

The LandScan 2011 Global Population Database was developed by Oak Ridge National Laboratory (ORNL) for the United States Department of Defense (DoD).

Change in population density every1km between 2011 and 2012 (irena:lspop2012-2011)

Map of changes in population density between 2011 and 2012 based on LandScan 2011 and 2012 Global Population Database, developed by Oak Ridge National Laboratory (ORNL) for the United States Department of Defense (DoD).

Global Population Database World 1km ORNL 2014 (irena:lspop2014)

The LandScan 2014 Global Population Database was developed by Oak Ridge National Laboratory (ORNL) for the United States Department of Defense (DoD).

Global Population Database World 1km ORNL 2018 (irena:lspop2018)

The LandScan 2016 Global Population Database was developed by Oak Ridge National Laboratory (ORNL) for the United States Department of Defense (DoD).

Meteorological Stations (tanzania:meteorological_stations)

Wind Speed at 100m Switzerland 100m Meteotest (meteotest:meteotest_wind_100m_wgs84)

Wind speed (100 m above ground), Switzerland (m/s), 100 m resolution; Source: www.wind-data.ch; Copyright: Meteotest, Switzerland. The maps may be used freely for personal use. If a map is published in print, the following text must be included below the map: © METEOTEST.

oil_palm_cons_agriculture_high_input_suitability_index (tanzania:oil_palm_cons_agriculture_high_input_suitability_index)

oil_palm_cons_agriculture_low_input_suitability_index (tanzania:oil_palm_cons_agriculture_low_input_suitability_index)

oil_palm_tillage_high_input_suitability_index (tanzania:oil_palm_tillage_high_input_suitability_index)

oil_palm_tillage_low_input_suitability_index (tanzania:oil_palm_tillage_low_input_suitability_index)

Global Power Generators OpenStreetMap 2015 (irena:osm_global_power_generators)

This map shows the power generators for the whole world. The power lines have been reviewed for positional accuracy using google satellite maps. Most of the lines checked on the map, seem to correspond with the actual location lines as confirmed by high resolution aerial images from google satellite maps. Limitations on the dataset include incompleteness in certain areas, and less information on the voltage capacity of some of the lines. This dataset was extracted from the OpenStreetMap initiative. OpenStreetMap® is open data, licensed under the Open Data Commons Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF). © OpenStreetMap contributors http://www.openstreetmap.org/copyright

Global sub stations OpenStreetMap 2015 extract (irena:osm_global_power_stations)

This map shows the substations for the whole world. The power lines have been reviewed for positional accuracy using google satellite maps. Most of the lines checked on the map, seem to correspond with the actual location lines as confirmed by high resolution aerial images from google satellite maps. Limitations on the dataset include incompleteness in certain areas, and less information on the voltage capacity of some of the lines. This dataset was extracted from the OpenStreetMap initiative. OpenStreetMap® is open data, licensed under the Open Data Commons Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF). © OpenStreetMap contributors http://www.openstreetmap.org/copyright

Global power lines OpenStreetMap 2016 (irena:osm_global_powerlines_2016)

This map shows the power lines for the whole world. The power lines have been reviewed for positional accuracy using google satellite maps. Most of the lines checked on the map, seem to correspond with the actual location lines as confirmed by high resolution aerial images from google satellite maps. Limitations on the dataset include incompleteness in certain areas, and less information on the voltage capacity of some of the lines. This dataset was extracted from the OpenStreetMap initiative. OpenStreetMap® is open data, licensed under the Open Data Commons Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF). © OpenStreetMap contributors http://www.openstreetmap.org/copyright

Annual Average Solar GHI in Peru (peru:peru_solar_annual)

Average daily solar maps incident to monthly and annual level for the period 1975-1990 are shown, using 500 national letter prepared at a scale of 1: 100 000. The irradiation data were obtained from data processing of heliophany and temperatures and a database of sunlight, in total 197 records used stations nationwide. Angstrom Model was used - Prescott (for heliophany data) and Model Bristow- Campbell (for temperature data) plus interpolation and simulation models.

Average Solar GHI August in Peru (peru:peru_solar_august)

Average daily solar maps incident to monthly and annual level for the period 1975-1990 are shown, using 500 national letter prepared at a scale of 1: 100 000. The irradiation data were obtained from data processing of heliophany and temperatures and a database of sunlight, in total 197 records used stations nationwide. Angstrom Model was used - Prescott (for heliophany data) and Model Bristow- Campbell (for temperature data) plus interpolation and simulation models.

Average Solar GHI February in Peru (peru:peru_solar_february)

Average daily solar maps incident to monthly and annual level for the period 1975-1990 are shown, using 500 national letter prepared at a scale of 1: 100 000. The irradiation data were obtained from data processing of heliophany and temperatures and a database of sunlight, in total 197 records used stations nationwide. Angstrom Model was used - Prescott (for heliophany data) and Model Bristow- Campbell (for temperature data) plus interpolation and simulation models.

Average Solar GHI July in Peru (peru:peru_solar_july)

Average daily solar maps incident to monthly and annual level for the period 1975-1990 are shown, using 500 national letter prepared at a scale of 1: 100 000. The irradiation data were obtained from data processing of heliophany and temperatures and a database of sunlight, in total 197 records used stations nationwide. Angstrom Model was used - Prescott (for heliophany data) and Model Bristow- Campbell (for temperature data) plus interpolation and simulation models.

Average Solar GHI March in Peru (peru:peru_solar_march)

Average daily solar maps incident to monthly and annual level for the period 1975-1990 are shown, using 500 national letter prepared at a scale of 1: 100 000. The irradiation data were obtained from data processing of heliophany and temperatures and a database of sunlight, in total 197 records used stations nationwide. Angstrom Model was used - Prescott (for heliophany data) and Model Bristow- Campbell (for temperature data) plus interpolation and simulation models.

Average Solar GHI November in Peru (peru:peru_solar_november)

Average daily solar maps incident to monthly and annual level for the period 1975-1990 are shown, using 500 national letter prepared at a scale of 1: 100 000. The irradiation data were obtained from data processing of heliophany and temperatures and a database of sunlight, in total 197 records used stations nationwide. Angstrom Model was used - Prescott (for heliophany data) and Model Bristow- Campbell (for temperature data) plus interpolation and simulation models.

Average Solar GHI September in Peru (peru:peru_solar_september)

Average daily solar maps incident to monthly and annual level for the period 1975-1990 are shown, using 500 national letter prepared at a scale of 1: 100 000. The irradiation data were obtained from data processing of heliophany and temperatures and a database of sunlight, in total 197 records used stations nationwide. Angstrom Model was used - Prescott (for heliophany data) and Model Bristow- Campbell (for temperature data) plus interpolation and simulation models.

plate60a_rainfed_maize_plus_3Degrees_and_10_rainfall (biotest:plate60a_rainfed_maize_plus_3Degrees_and_10_rainfall)

plate60b_rainfed_maize_plus_3Degrees_and_10_rainfall (biotest:plate60b_rainfed_maize_plus_3Degrees_and_10_rainfall)

plate60c_rainfed_maize_plus_3Degrees_and_10_rainfall (biotest:plate60c_rainfed_maize_plus_3Degrees_and_10_rainfall)

Solar PV Grid Connected 150km 2013 (ecowas_demo:pv_cent_150)

Opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 150 km from the existing grid; - for a annual global horizontal irradiation starting from 1500 kwh/m2/y, suitable at 2100 kwh/m2/y and beyond; - a population density below 500 hab/km2; - not in forested areas, water bodies or protected areas. The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Solar PV Grid Connected 75km 2013 (ecowas_demo:pv_cent_75)

Opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 75 km from the existing grid; - for a annual global horizontal irradiation starting from 1500 kwh/m2/y, suitable at 2100 kwh/m2/y and beyond; - a population density below 500 hab/km2; - not in forested areas, water bodies or protected areas. The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Solar PV off-Grid 150km 2013 (ecowas_demo:pv_descent_150)

Opportunity scores for offgrid applications in the ECOWAS region. Illustration for the following parameters: - further than 150 km from the existing grid; - for a annual global horizontal irradiation starting from 1500 kwh/m2/y, suitable at 2100 kwh/m2/y and beyond; - a non-null population density; - not in forested areas, water bodies or protected areas. The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Solar PV off-Grid 50km 2013 (ecowas_demo:pv_descent_50)

Opportunity scores for offgrid applications in the ECOWAS region. Illustration for the following parameters: - further than 50 km from the existing grid; - for a annual global horizontal irradiation starting from 1500 kwh/m2/y, suitable at 2100 kwh/m2/y and beyond; - a non-null population density; - not in forested areas, water bodies or protected areas. The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

railway (tanzania:railway)

Rainfall Pattern (tanzania:rainfall_pattern)

roads (tanzania:roads)

Mongolia Solar Radiation Measurements GHI DNI DHI 2012 (mongolia:solar_mongolia_2012)

Location of the solar measurement stations in Mongolia with measurements of the Direct, Diffuse and Global radiation components. The full record covers the period from 2004 to 2012. The data record available through the Global Atlas is an extract which covers the year of 2012. The data was supplied by the Ministry of Energy of Mongolia.

solarmed_DNI_horizon (solar-med-atlas:solarmed_DNI_horizon)

Sudan Measuring Stations (sudan:sudan_measuring_stations)

This dataset shows measuring stations and gives access to the data from two WMO meteorological stations, DONGOLA and NYALA: DONGOLA meteorological station. The measurement mast is located at 19.17N, 30.48E, 226m (elevation). Monthly average wind speeds (m/s) at 10m height and 3 hourly Wind speeds and direction (in knots) from 2001-2010. NYALA meteorological station. The measurement mast is located at 12.00N, 24.80E, 675m (elevation). Monthly average wind speeds from 2001-2010 (m/s). The WMO network comprises over 13400 measurement stations all over the world. The data from these stations was supplied to IRENA by the Sudan Meteorological Authority. The monthly averages were initially presented in knots (nautical mile per hour). The values were subsequently converted to meters per second (m/s) using (1kn = 0.514444mps).

sugar_cane_cons_agriculture_high_input_suitability_index (tanzania:sugar_cane_cons_agriculture_high_input_suitability_index)

sugar_cane_cons_agriculture_low_input_suitability_index (tanzania:sugar_cane_cons_agriculture_low_input_suitability_index)

sugar_cane_tillage_high_input_suitability_index (tanzania:sugar_cane_tillage_high_input_suitability_index)

sugar_cane_tillage_low_input_suitability_index (tanzania:sugar_cane_tillage_low_input_suitability_index)

suitability_pv_centralized_150km (latin_america_suitability_analysis:suitability_pv_centralized_150km)

suitability_pv_descentralized_100km (latin_america_suitability_analysis:suitability_pv_descentralized_100km)

suitability_pv_descentralized_75km (latin_america_suitability_analysis:suitability_pv_descentralized_75km)

suitability_wind_centralized_150km (latin_america_suitability_analysis:suitability_wind_centralized_150km)

suitability_wind_descentralized_100km (latin_america_suitability_analysis:suitability_wind_descentralized_100km)

suitability_wind_descentralized_75km (latin_america_suitability_analysis:suitability_wind_descentralized_75km)

sunflower_cons_agriculture_high_input_suitability_index (tanzania:sunflower_cons_agriculture_high_input_suitability_index)

sunflower_cons_agriculture_low_input_suitability_index (tanzania:sunflower_cons_agriculture_low_input_suitability_index)

sunflower_tillage_high_input_suitability_index (tanzania:sunflower_tillage_high_input_suitability_index)

sunflower_tillage_low_input_suitability_index (tanzania:sunflower_tillage_low_input_suitability_index)

sweet_sorghum_cons_agriculture_high_input_suitability_index (tanzania:sweet_sorghum_cons_agriculture_high_input_suitability_index)

sweet_sorghum_cons_agriculture_low_input_suitability_index (tanzania:sweet_sorghum_cons_agriculture_low_input_suitability_index)

sweet_sorghum_tillage_high_input_suitability_index (tanzania:sweet_sorghum_tillage_high_input_suitability_index)

sweet_sorghum_tillage_low_input_suitability_index (tanzania:sweet_sorghum_tillage_low_input_suitability_index)

thermal_areas (chile_geothermal:thermal_areas)

Thermal Zones (tanzania:thermal_zones)

Total Potential Low Temperature Spain (spain:total_potential_low_temperature)

This layer shows potential areas for low temperature geothermal systems with temperatures less than 100 degrees Celsius. The map highlights several areas and estimates the total potential for each area in GWh The full details for this map and the methodology with which they have been developed is contained in the report: Evaluacion Del Potencial De Energia Geothermica, Estudio Technico Per 2011 – 2020 (p 167). http://www.idae.es/uploads/documentos/documentos_11227_e9_geotermia_A_db72b0ac.pdf

Total Potential Stimulated Systems Spain (spain:total_potential_stimulated_systems)

This layer shows potential areas for stimulated geothermal systems (otherwise called enhanced geothermal systems – EGS). The map highlights several areas with significant potential in GWh. The full details for this map and the methodology with which they have been developed is contained in the report: Evaluacion Del Potencial De Energia Geothermica, Estudio Technico Per 2011 – 2020 (p 168). http://www.idae.es/uploads/documentos/documentos_11227_e9_geotermia_A_db72b0ac.pdf

Total Potential Very Low Temperature in Subsoil Rocks (spain:total_potential_very_low_temp_in_subsoil_rocks)

This layer shows areas in Spain with potential for very low temperature geothermal applications at with temperatures less than 30 degrees Celsius. The full details for this map and the methodology with which they have been developed is contained in the report: Evaluacion Del Potencial De Energia Geothermica, Estudio Technico Per 2011 – 2020 (p 114). http://www.idae.es/uploads/documentos/documentos_11227_e9_geotermia_A_db72b0ac.pdf

Geothermal sites in Turkey (turkey:turkey_geothermal_resources)

The layer classifies 375 identified geothermal sites by fluid temperature range. In addition, the layer also contains the location, estimated potential, elevation, actual fluid temperature and flow rates, area, etc for each site. The layer was produced originally in Turkish language by the Directorate of Mineral Research and Exploration (MTA) in Turkey and subsequently translated by IRENA. http://www.atag.itu.edu.tr/v3/?p=135

World Database on Protected Areas World polygon UNEP May 2016 (IUCN:wdpa_poly_may2016)

The World Database on Protected Areas (WDPA) is the most comprehensive spatial dataset on the world's marine and terrestrial protected areas, produced through a joint initiative of the International Union for the Conservation of Nature (IUCN) and the United National Environment Programme (UNEP). The WDPA contains the UN List of protected areas (official national data) as well as authoritative information sourced by non-governmental organizations, academic institutions, international convention secretariats and many others. The WDPA is used for reporting on global indicators and trends, ecological gap analysis, environmental impact analysis and is increasingly used for private sector decision-making. The WDPA is hosted and managed at the UNEP World Conservation Monitoring Centre.

Wind Grid Connected 100km 2013 (ecowas_demo:wind_cent_100_wgs84)

Opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 100 km from the existing grid; - for a wind speed starting from 4.5 m/s, suitable at 7 m/s and beyond; - a population density below 500 hab/km2; - not in forested areas, water bodies or protected areas; - not above 2000m. The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Wind Grid Connected 50km 2013 (ecowas_demo:wind_cent_50_wgs84)

Opportunity scores for grid connected applications in the ECOWAS region. Illustration for the following parameters: - less than 50 km from the existing grid; - for a wind speed starting from 4.5 m/s, suitable at 7 m/s and beyond; - a population density below 500 hab/km2; - not in forested areas, water bodies or protected areas; - not above 2000m. The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Wind off-Grid 100km 2013 (ecowas_demo:wind_descent_100_wgs84)

Opportunity scores for offgrid applications in the ECOWAS region. Illustration for the following parameters: - further than 100 km from the existing grid; - for a wind speed starting from 4.5 m/s, suitable at 7 m/s and beyond; - a non-null population density; - not in forested areas, water bodies or protected areas; - not above 2000m. The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Wind off-Grid 50km 2013 (ecowas_demo:wind_descent_50_wgs84)

Opportunity scores for offgrid applications in the ECOWAS region. Illustration for the following parameters: - further than 50 km from the existing grid; - for a wind speed starting from 4.5 m/s, suitable at 7 m/s and beyond; - a non-null population density; - not in forested areas, water bodies or protected areas; - not above 2000m. The scores are allocated as follows: the minimum score for a parameter starts at 0, with the minimum acceptable value. It increases linearly to 1 (100%), when a suitable value is reached. The value is maintained to 100% beyond this value. In our demonstration, the final score for a location is the average of the scores for each parameter. Limitations of the methods are indicated in the related report, available at: http://www.irena.org/globalatlas/Publication.aspx Project: Opportunity areas for grid connected and offgrid applications in the ECOWAS region. Project initiated under the Global Atlas initiative as a contribution to the GEOSS AIP 6. The proposed maps illustrate the capabilities of the Global Atlas for spatial planning purposes, in the case of the ECOWAS region. This demonstration shows a first range of possibilities for opportunity areas, based on a range of assumptions. The purpose of this demonstration is not to provide definitive assessment of opportunity zones for future developments, but to initiate a dialogue with the stakeholders of the region on the regional opportunities for solar and wind resources. The outcomes of this first cut analysis, and the selected assumptions, are to be reviewed in partnership with the regional stakeholders.Find the full report at: http://www.irena.org/globalatlas/Publication.aspx

Wind Energy Projects Belgium Economie (belgium:wind_energy_projects)

This dataset shows areas of windmills at Belgium sea. More information can be obtained through this link: http://www.mumm.ac.be/EN/Management/Sea-based/windmills_docs.php

Annual Average Wind Power density at 100m in Peru (peru:wind_power_density_at_100_m_year)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Annual Average Wind Power density at 80m in Peru (peru:wind_power_density_at_80_m_year)

Wind Energy Atlas of Peru shows the following wind maps: annual average of 50 m, 80 m and 100 m and 80 m monthly average; plus maps of annual average power density at 50 m, 80 m and 100 m and wind maps for each of the 24 regions, annual average and seasonal average of 80 m. Techniques have been used mesoscale and microscale modeling, combined with the use of a sophisticated simulation model reproducing atmospheric wind patterns on a large scale, microscale wind model that responds to the characteristics of the terrain and topography. We used historical weather data sources related to a three-dimensional network generated by the US National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), plus bases geophysical input data, mainly elevation and land use, vegetation index values and climatological temperature seawater. Elevation data have been generated and compiled on a digital elevation model (DEM) under the project SRTM (Shuttle Radar Topography Mission) by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The land uses were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer), with a resolution of 1 km.

Swaziland Wind Stations (swaziland:wind_stations)

Wind data provided was collected between May 2001 and April 2002 under the wind measurement project which was part of the Swaziland National Energy Policy Development Project supported by the Danish Co-operation for Environment and Development (DANCED). Tripod Wind Energy Aps oversaw the installation of the wind measuring masts as well as the data analysis and reporting. Mores at http://irena.masdar.ac.ae/docs/Wind_Measurements_in_Swaziland_Final.pdf

World airports (irena:world_airports)

Airports of the world