Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models

The characteristics of near-surface wind speed (NWS) are important to the study of dust storms, evapotranspiration, heavy rainfall, air pollution, and wind energy development. This study evaluated the performance of 30 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) through compa...

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Main Authors: Hao Deng, Wei Hua, Guangzhou Fan
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Atmosphere
Subjects:
Online Access:https://www.mdpi.com/2073-4433/12/8/1062
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spelling doaj-2a155488c6a44058ad8624d3a84144732021-08-26T13:31:46ZengMDPI AGAtmosphere2073-44332021-08-01121062106210.3390/atmos12081062Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 ModelsHao Deng0Wei Hua1Guangzhou Fan2School of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610225, ChinaSchool of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610225, ChinaPlateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu 610225, ChinaThe characteristics of near-surface wind speed (NWS) are important to the study of dust storms, evapotranspiration, heavy rainfall, air pollution, and wind energy development. This study evaluated the performance of 30 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) through comparison with observational NWS data acquired in China during a historical period (1975–2014), and projected future changes in NWS under three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) based on an optimal multi-model ensemble. Results showed that most models reproduced the spatial pattern of NWS for all seasons and the annual mean, although the models generally overestimated NWS magnitude. All models tended to underestimate the trends of decline of NWS for all seasons and the annual mean. On the basis of a comprehensive ranking index, the KIOST-ESM, CNRM-ESM2-1, HadGEM3-GC31-LL, CMCC-CM2-SR5, and KACE-1-0-G models were ranked as the five best-performing models. In the projections of future change, nationally averaged NWS for all months was weaker than in the historical period, and the trends decreased markedly under all the different scenarios except the winter time series under SSP2-4.5. Additionally, the projected NWS over most regions of China weakened in both the early period (2021–2060) and the later period (2061–2100).https://www.mdpi.com/2073-4433/12/8/1062CMIP6near-surface wind speedChinaevaluationprojection
collection DOAJ
language English
format Article
sources DOAJ
author Hao Deng
Wei Hua
Guangzhou Fan
spellingShingle Hao Deng
Wei Hua
Guangzhou Fan
Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models
Atmosphere
CMIP6
near-surface wind speed
China
evaluation
projection
author_facet Hao Deng
Wei Hua
Guangzhou Fan
author_sort Hao Deng
title Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models
title_short Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models
title_full Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models
title_fullStr Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models
title_full_unstemmed Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models
title_sort evaluation and projection of near-surface wind speed over china based on cmip6 models
publisher MDPI AG
series Atmosphere
issn 2073-4433
publishDate 2021-08-01
description The characteristics of near-surface wind speed (NWS) are important to the study of dust storms, evapotranspiration, heavy rainfall, air pollution, and wind energy development. This study evaluated the performance of 30 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) through comparison with observational NWS data acquired in China during a historical period (1975–2014), and projected future changes in NWS under three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) based on an optimal multi-model ensemble. Results showed that most models reproduced the spatial pattern of NWS for all seasons and the annual mean, although the models generally overestimated NWS magnitude. All models tended to underestimate the trends of decline of NWS for all seasons and the annual mean. On the basis of a comprehensive ranking index, the KIOST-ESM, CNRM-ESM2-1, HadGEM3-GC31-LL, CMCC-CM2-SR5, and KACE-1-0-G models were ranked as the five best-performing models. In the projections of future change, nationally averaged NWS for all months was weaker than in the historical period, and the trends decreased markedly under all the different scenarios except the winter time series under SSP2-4.5. Additionally, the projected NWS over most regions of China weakened in both the early period (2021–2060) and the later period (2061–2100).
topic CMIP6
near-surface wind speed
China
evaluation
projection
url https://www.mdpi.com/2073-4433/12/8/1062
work_keys_str_mv AT haodeng evaluationandprojectionofnearsurfacewindspeedoverchinabasedoncmip6models
AT weihua evaluationandprojectionofnearsurfacewindspeedoverchinabasedoncmip6models
AT guangzhoufan evaluationandprojectionofnearsurfacewindspeedoverchinabasedoncmip6models
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