Evaluation of ERA5 wind parameter with in-situ data offshore China

There are abundant wind energy resources along the coast of China. Understanding spatial-temporal characteristics of wind speed is significant in meteorology, coastal engineering design and maritime industries. Reliable wind products such as reanalysis data, coupled with accurate wind speed measurements, are essential for elucidating the primary characteristics of the wind field. In this study, we evaluated hourly 10 m and 100 m wind speed data from the fifth-generation ECMWF atmospheric reanalysis (ERA5) by comparing it with direct wind measurements obtained from 19 wind tower located across the coastal waters of China. The results are as follows: 1) the basic statistical characteristic between ERA5 reanalysis and observed wind speeds demonstrate good consistency. However, the ERA5 tends to underestimate wind speed, particularly at high speeds during extreme conditions. 2) Compare ERA5 data with observations from each station using a frequency distribution-based score method, hourly scores of most stations are between 0.8 to 0.9. It shows the higher simulation skill in the northern region than the southern due to the influence of high-frequency typhoon in the South China Sea. 3)Distribution function parameters, mean values, variability, and wind threshold frequencies were analyzed for this ensemble of observation, providing an overall description of wind characteristics. Generally speaking, there is no clear linear relationship between scores and the other variables. On longer time scales (6-24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.

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Publication Details

Journal
PLoS ONE
Published
2025-05-09
DOI
https://doi.org/10.1371/journal.pone.0317751
Citations
7
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
7.74

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article

Evaluation of ERA5 wind parameter with in-situ data offshore China

Weidong Ji, Xiaokai Hu, Guanghong Liao, Wenfei Xue et al.
7 citations
PLoS ONE
Climate variability and models
7.74
article

Evaluation of ERA5 wind parameter with in-situ data offshore China

Weidong Ji, Xiaokai Hu, Guanghong Liao, Wenfei Xue, Ning Qi, Rongfu Li, Zhigang Cao, Hongying Yang
article en
7 citations

Abstract

There are abundant wind energy resources along the coast of China. Understanding spatial-temporal characteristics of wind speed is significant in meteorology, coastal engineering design and maritime industries. Reliable wind products such as reanalysis data, coupled with accurate wind speed measurements, are essential for elucidating the primary characteristics of the wind field. In this study, we evaluated hourly 10 m and 100 m wind speed data from the fifth-generation ECMWF atmospheric reanalysis (ERA5) by comparing it with direct wind measurements obtained from 19 wind tower located across the coastal waters of China. The results are as follows: 1) the basic statistical characteristic between ERA5 reanalysis and observed wind speeds demonstrate good consistency. However, the ERA5 tends to underestimate wind speed, particularly at high speeds during extreme conditions. 2) Compare ERA5 data with observations from each station using a frequency distribution-based score method, hourly scores of most stations are between 0.8 to 0.9. It shows the higher simulation skill in the northern region than the southern due to the influence of high-frequency typhoon in the South China Sea. 3)Distribution function parameters, mean values, variability, and wind threshold frequencies were analyzed for this ensemble of observation, providing an overall description of wind characteristics. Generally speaking, there is no clear linear relationship between scores and the other variables. On longer time scales (6-24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.

PLoS ONEVol. 20(5)
Hohai University (CN), Ministry of Natural Resources (CN), Goldwind (China) (CN), NARI Group (China) (CN)
Anhui Provincial Key Research and Development Plan
Affordable and clean energy
Openalex Percentile: Top 2%
Climate variability and models
7.74
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