An artificial intelligence reconstruction of global gridded surface winds

Gridded wind speed data products with global coverage and continuous long-term time series are widely used in many applications, such as evaluating wind energy potential [1] and drought processes [2]. However, some available products do not accurately reproduce observed wind speed trends on land [3], [4], leading to biased or inaccurate conclusions in studies on wind-related phenomena. In-situ weather stations involve direct measurements that accurately preserve wind speed trends. Still, the uneven distribution and incomplete time series have constrained their widespread applications in regional and global analyses. These limitations, which we have encountered firsthand in investigating the global wind stilling and reversal phenomena [4], have inspired us to create a new global gridded surface wind product that preserves observed wind patterns and trends.

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Main Authors: Zhou, Lihong, Liu, Haofeng, Jiang, Xin, Ziegler, Alan D., Azorín-Molina, César, Liu, Jiang, Zeng, Zhenzhong
Other Authors: National Natural Science Foundation of China
Format: artículo biblioteca
Published: Elsevier 2022
Online Access:http://hdl.handle.net/10261/287670
http://dx.doi.org/10.13039/501100011033
http://dx.doi.org/10.13039/501100001809
http://dx.doi.org/10.13039/501100003359
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spelling dig-cide-es-10261-2876702023-01-26T14:50:02Z An artificial intelligence reconstruction of global gridded surface winds Zhou, Lihong Liu, Haofeng Jiang, Xin Ziegler, Alan D. Azorín-Molina, César Liu, Jiang Zeng, Zhenzhong National Natural Science Foundation of China Southern University of Science and Technology (China) Ministerio de Ciencia, Innovación y Universidades (España) Agencia Estatal de Investigación (España) Generalitat Valenciana Gridded wind speed data products with global coverage and continuous long-term time series are widely used in many applications, such as evaluating wind energy potential [1] and drought processes [2]. However, some available products do not accurately reproduce observed wind speed trends on land [3], [4], leading to biased or inaccurate conclusions in studies on wind-related phenomena. In-situ weather stations involve direct measurements that accurately preserve wind speed trends. Still, the uneven distribution and incomplete time series have constrained their widespread applications in regional and global analyses. These limitations, which we have encountered firsthand in investigating the global wind stilling and reversal phenomena [4], have inspired us to create a new global gridded surface wind product that preserves observed wind patterns and trends. This work was supported by the National Natural Science Foundation of China (42071022), the start-up fund provided by Southern University of Science and Technology (29/Y01296122), and Highlight Project on Water Security and Global Change of Southern University of Science and Technology (G02296302). Cesar Azorin-Molina was supported by Evaluación y atribución de la variabilidad de la velocidad media y las rachas máximas de viento: causas del fenómeno stilling (RTI2018-095749-A-100), Cambios observados, proyecciones futuras e índices de la velocidad del viento y sus extremos en la Comunidad Valenciana (AICO/2021/023), and the Spanish National Research Centre Interdisciplinary Thematic Platform PTI-CLIMA. We thank Met Office (HadISD), ECMWF (ERA5), and CMIP6 for providing wind speed data used in this work. 2023-01-26T14:50:02Z 2023-01-26T14:50:02Z 2022 2023-01-26T14:50:02Z artículo doi: 10.1016/j.scib.2022.09.022 issn: 2095-9273 e-issn: 2095-9281 Science Bulletin 67(20): 2060-2063 (2022) http://hdl.handle.net/10261/287670 10.1016/j.scib.2022.09.022 http://dx.doi.org/10.13039/501100011033 http://dx.doi.org/10.13039/501100001809 http://dx.doi.org/10.13039/501100003359 #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095749-A-I00/ES/EVALUACION Y ATRIBUCION DE LA VARIABILIDAD DE LA VELOCIDAD MEDIA Y LAS RACHAS MAXIMAS DE VIENTO: CAUSAS DEL FENOMENO STILLING/ http://dx.doi.org/10.1016/j.scib.2022.09.022 Sí none Elsevier National Natural Science Foundation of China Chinese Academy of Sciences
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country España
countrycode ES
component Bibliográfico
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databasecode dig-cide-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del CIDE España
description Gridded wind speed data products with global coverage and continuous long-term time series are widely used in many applications, such as evaluating wind energy potential [1] and drought processes [2]. However, some available products do not accurately reproduce observed wind speed trends on land [3], [4], leading to biased or inaccurate conclusions in studies on wind-related phenomena. In-situ weather stations involve direct measurements that accurately preserve wind speed trends. Still, the uneven distribution and incomplete time series have constrained their widespread applications in regional and global analyses. These limitations, which we have encountered firsthand in investigating the global wind stilling and reversal phenomena [4], have inspired us to create a new global gridded surface wind product that preserves observed wind patterns and trends.
author2 National Natural Science Foundation of China
author_facet National Natural Science Foundation of China
Zhou, Lihong
Liu, Haofeng
Jiang, Xin
Ziegler, Alan D.
Azorín-Molina, César
Liu, Jiang
Zeng, Zhenzhong
format artículo
author Zhou, Lihong
Liu, Haofeng
Jiang, Xin
Ziegler, Alan D.
Azorín-Molina, César
Liu, Jiang
Zeng, Zhenzhong
spellingShingle Zhou, Lihong
Liu, Haofeng
Jiang, Xin
Ziegler, Alan D.
Azorín-Molina, César
Liu, Jiang
Zeng, Zhenzhong
An artificial intelligence reconstruction of global gridded surface winds
author_sort Zhou, Lihong
title An artificial intelligence reconstruction of global gridded surface winds
title_short An artificial intelligence reconstruction of global gridded surface winds
title_full An artificial intelligence reconstruction of global gridded surface winds
title_fullStr An artificial intelligence reconstruction of global gridded surface winds
title_full_unstemmed An artificial intelligence reconstruction of global gridded surface winds
title_sort artificial intelligence reconstruction of global gridded surface winds
publisher Elsevier
publishDate 2022
url http://hdl.handle.net/10261/287670
http://dx.doi.org/10.13039/501100011033
http://dx.doi.org/10.13039/501100001809
http://dx.doi.org/10.13039/501100003359
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