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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Published in:Scientific Reports
Main Authors: Sherman, Peter, Chen, Xinyu, McElroy, Michael B.
Format: Text
Language:English
Published: Nature Publishing Group UK 2017
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701265/
http://www.ncbi.nlm.nih.gov/pubmed/29176621
https://doi.org/10.1038/s41598-017-16073-2
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spelling ftpubmed:oai:pubmedcentral.nih.gov:5701265 2023-05-15T15:06:46+02:00 Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate Sherman, Peter Chen, Xinyu McElroy, Michael B. 2017-11-24 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701265/ http://www.ncbi.nlm.nih.gov/pubmed/29176621 https://doi.org/10.1038/s41598-017-16073-2 en eng Nature Publishing Group UK http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701265/ http://www.ncbi.nlm.nih.gov/pubmed/29176621 http://dx.doi.org/10.1038/s41598-017-16073-2 © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. CC-BY Article Text 2017 ftpubmed https://doi.org/10.1038/s41598-017-16073-2 2017-12-03T01:35:07Z 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. Text Arctic PubMed Central (PMC) Arctic Pacific Scientific Reports 7 1
institution Open Polar
collection PubMed Central (PMC)
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language English
topic Article
spellingShingle Article
Sherman, Peter
Chen, Xinyu
McElroy, Michael B.
Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate
topic_facet Article
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.
format Text
author Sherman, Peter
Chen, Xinyu
McElroy, Michael B.
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://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701265/
http://www.ncbi.nlm.nih.gov/pubmed/29176621
https://doi.org/10.1038/s41598-017-16073-2
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op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701265/
http://www.ncbi.nlm.nih.gov/pubmed/29176621
http://dx.doi.org/10.1038/s41598-017-16073-2
op_rights © The Author(s) 2017
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
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