Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate
China hosts the world’s largest market for wind-generated electricity. The financial return and carbon reduction benefits from wind power are sensitive to changing wind resources. Wind data derived from an assimilated meteorological database are used here to estimate what the wind generated electric...
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Nature Publishing Group UK
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ftharvardudash:oai:dash.harvard.edu:1/34493373 2023-05-15T15:06:02+02:00 Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate Sherman, Peter Chen, Xinyu McElroy, Michael B. 2017 application/pdf http://nrs.harvard.edu/urn-3:HUL.InstRepos:34493373 https://doi.org/10.1038/s41598-017-16073-2 en_US eng Nature Publishing Group UK doi:10.1038/s41598-017-16073-2 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701265/pdf/ Scientific Reports Sherman, Peter, Xinyu Chen, and Michael B. McElroy. 2017. “Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate.” Scientific Reports 7 (1): 16294. doi:10.1038/s41598-017-16073-2. http://dx.doi.org/10.1038/s41598-017-16073-2. http://nrs.harvard.edu/urn-3:HUL.InstRepos:34493373 Journal Article 2017 ftharvardudash https://doi.org/10.1038/s41598-017-16073-2 2022-04-05T18:39:00Z China hosts the world’s largest market for wind-generated electricity. The financial return and carbon reduction benefits from wind power are sensitive to changing wind resources. Wind data derived from an assimilated meteorological database are used here to estimate what the wind generated electricity in China would have been on an hourly basis over the period 1979 to 2015 at a geographical resolution of approximately 50 km × 50 km. The analysis indicates a secular decrease in generating potential over this interval, with the largest declines observed for western Inner Mongolia (15 ± 7%) and the northern part of Gansu (17 ± 8%), two leading wind investment areas. The decrease is associated with long-term warming in the vicinity of the Siberian High (SH), correlated also with the observed secular increase in global average surface temperatures. The long-term trend is modulated by variability relating to the Pacific Decadal Oscillation (PDO) and the Arctic Oscillation (AO). A linear regression model incorporating indices for the PDO and AO, as well as the declining trend, can account for the interannual variability of wind power, suggesting that advances in long-term forecasting could be exploited to markedly improve management of future energy systems. Version of Record Article in Journal/Newspaper Arctic Harvard University: DASH - Digital Access to Scholarship at Harvard Arctic Pacific Scientific Reports 7 1 |
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Harvard University: DASH - Digital Access to Scholarship at Harvard |
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English |
description |
China hosts the world’s largest market for wind-generated electricity. The financial return and carbon reduction benefits from wind power are sensitive to changing wind resources. Wind data derived from an assimilated meteorological database are used here to estimate what the wind generated electricity in China would have been on an hourly basis over the period 1979 to 2015 at a geographical resolution of approximately 50 km × 50 km. The analysis indicates a secular decrease in generating potential over this interval, with the largest declines observed for western Inner Mongolia (15 ± 7%) and the northern part of Gansu (17 ± 8%), two leading wind investment areas. The decrease is associated with long-term warming in the vicinity of the Siberian High (SH), correlated also with the observed secular increase in global average surface temperatures. The long-term trend is modulated by variability relating to the Pacific Decadal Oscillation (PDO) and the Arctic Oscillation (AO). A linear regression model incorporating indices for the PDO and AO, as well as the declining trend, can account for the interannual variability of wind power, suggesting that advances in long-term forecasting could be exploited to markedly improve management of future energy systems. Version of Record |
format |
Article in Journal/Newspaper |
author |
Sherman, Peter Chen, Xinyu McElroy, Michael B. |
spellingShingle |
Sherman, Peter Chen, Xinyu McElroy, Michael B. Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate |
author_facet |
Sherman, Peter Chen, Xinyu McElroy, Michael B. |
author_sort |
Sherman, Peter |
title |
Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate |
title_short |
Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate |
title_full |
Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate |
title_fullStr |
Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate |
title_full_unstemmed |
Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate |
title_sort |
wind-generated electricity in china: decreasing potential, inter-annual variability and association with changing climate |
publisher |
Nature Publishing Group UK |
publishDate |
2017 |
url |
http://nrs.harvard.edu/urn-3:HUL.InstRepos:34493373 https://doi.org/10.1038/s41598-017-16073-2 |
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Arctic Pacific |
geographic_facet |
Arctic Pacific |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
doi:10.1038/s41598-017-16073-2 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701265/pdf/ Scientific Reports Sherman, Peter, Xinyu Chen, and Michael B. McElroy. 2017. “Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate.” Scientific Reports 7 (1): 16294. doi:10.1038/s41598-017-16073-2. http://dx.doi.org/10.1038/s41598-017-16073-2. http://nrs.harvard.edu/urn-3:HUL.InstRepos:34493373 |
op_doi |
https://doi.org/10.1038/s41598-017-16073-2 |
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Scientific Reports |
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1 |
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