Interannual Variability and Seasonal Predictability of Wind and Solar Resources
Solar and wind resources available for power generation are subject to variability due to meteorological factors. Here, we use a new global climate reanalysis product, Version 2 of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), to quantify interannual variability...
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ftdoajarticles:oai:doaj.org/article:b0a9f84b13264d039c133180129df5ed 2023-05-15T15:07:40+02:00 Interannual Variability and Seasonal Predictability of Wind and Solar Resources Nir Y. Krakauer Daniel S. Cohan 2017-07-01T00:00:00Z https://doi.org/10.3390/resources6030029 https://doaj.org/article/b0a9f84b13264d039c133180129df5ed EN eng MDPI AG https://www.mdpi.com/2079-9276/6/3/29 https://doaj.org/toc/2079-9276 2079-9276 doi:10.3390/resources6030029 https://doaj.org/article/b0a9f84b13264d039c133180129df5ed Resources, Vol 6, Iss 3, p 29 (2017) renewable energy interannual variability seasonal forecasting teleconnections Science Q article 2017 ftdoajarticles https://doi.org/10.3390/resources6030029 2022-12-30T20:03:48Z Solar and wind resources available for power generation are subject to variability due to meteorological factors. Here, we use a new global climate reanalysis product, Version 2 of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), to quantify interannual variability of monthly-mean solar and wind resource from 1980 to 2016 at a resolution of about 0.5 degrees. We find an average coefficient of variation (CV) of 11% for monthly-mean solar radiation and 8% for wind speed. Mean CVs were about 25% greater over ocean than over land and, for land areas, were greatest at high latitude. The correlation between solar and wind anomalies was near zero in the global mean, but markedly positive or negative in some regions. Both wind and solar variability were correlated with values of climate modes such as the Southern Oscillation Index and Arctic Oscillation, with correlations in the Northern Hemisphere generally stronger during winter. We conclude that reanalysis solar and wind fields could be helpful in assessing variability in power generation due to interannual fluctuations in the solar and wind resource. Skillful prediction of these fluctuations seems to be possible, particularly for certain regions and seasons, given the persistence or predictability of climate modes with which these fluctuations are associated. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Merra ENVELOPE(12.615,12.615,65.816,65.816) Resources 6 3 29 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
renewable energy interannual variability seasonal forecasting teleconnections Science Q |
spellingShingle |
renewable energy interannual variability seasonal forecasting teleconnections Science Q Nir Y. Krakauer Daniel S. Cohan Interannual Variability and Seasonal Predictability of Wind and Solar Resources |
topic_facet |
renewable energy interannual variability seasonal forecasting teleconnections Science Q |
description |
Solar and wind resources available for power generation are subject to variability due to meteorological factors. Here, we use a new global climate reanalysis product, Version 2 of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), to quantify interannual variability of monthly-mean solar and wind resource from 1980 to 2016 at a resolution of about 0.5 degrees. We find an average coefficient of variation (CV) of 11% for monthly-mean solar radiation and 8% for wind speed. Mean CVs were about 25% greater over ocean than over land and, for land areas, were greatest at high latitude. The correlation between solar and wind anomalies was near zero in the global mean, but markedly positive or negative in some regions. Both wind and solar variability were correlated with values of climate modes such as the Southern Oscillation Index and Arctic Oscillation, with correlations in the Northern Hemisphere generally stronger during winter. We conclude that reanalysis solar and wind fields could be helpful in assessing variability in power generation due to interannual fluctuations in the solar and wind resource. Skillful prediction of these fluctuations seems to be possible, particularly for certain regions and seasons, given the persistence or predictability of climate modes with which these fluctuations are associated. |
format |
Article in Journal/Newspaper |
author |
Nir Y. Krakauer Daniel S. Cohan |
author_facet |
Nir Y. Krakauer Daniel S. Cohan |
author_sort |
Nir Y. Krakauer |
title |
Interannual Variability and Seasonal Predictability of Wind and Solar Resources |
title_short |
Interannual Variability and Seasonal Predictability of Wind and Solar Resources |
title_full |
Interannual Variability and Seasonal Predictability of Wind and Solar Resources |
title_fullStr |
Interannual Variability and Seasonal Predictability of Wind and Solar Resources |
title_full_unstemmed |
Interannual Variability and Seasonal Predictability of Wind and Solar Resources |
title_sort |
interannual variability and seasonal predictability of wind and solar resources |
publisher |
MDPI AG |
publishDate |
2017 |
url |
https://doi.org/10.3390/resources6030029 https://doaj.org/article/b0a9f84b13264d039c133180129df5ed |
long_lat |
ENVELOPE(12.615,12.615,65.816,65.816) |
geographic |
Arctic Merra |
geographic_facet |
Arctic Merra |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Resources, Vol 6, Iss 3, p 29 (2017) |
op_relation |
https://www.mdpi.com/2079-9276/6/3/29 https://doaj.org/toc/2079-9276 2079-9276 doi:10.3390/resources6030029 https://doaj.org/article/b0a9f84b13264d039c133180129df5ed |
op_doi |
https://doi.org/10.3390/resources6030029 |
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Resources |
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6 |
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29 |
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