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Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China

ERA5 is the latest fifth-generation reanalysis global atmosphere dataset from the European Centre for Medium-Range Weather Forecasts, replacing ERA-Interim as the next generation of representative satellite-observational data on the global scale. ERA5 data have been evaluated and applied in differen...

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Autores principales: Jiao, Donglai, Xu, Nannan, Yang, Fan, Xu, Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8429776/
https://www.ncbi.nlm.nih.gov/pubmed/34504211
http://dx.doi.org/10.1038/s41598-021-97432-y
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author Jiao, Donglai
Xu, Nannan
Yang, Fan
Xu, Ke
author_facet Jiao, Donglai
Xu, Nannan
Yang, Fan
Xu, Ke
author_sort Jiao, Donglai
collection PubMed
description ERA5 is the latest fifth-generation reanalysis global atmosphere dataset from the European Centre for Medium-Range Weather Forecasts, replacing ERA-Interim as the next generation of representative satellite-observational data on the global scale. ERA5 data have been evaluated and applied in different regions, but the performances are inconsistent. Meanwhile, there are few precise evaluations of ERA5 precipitation data over long time series have been performed in Chinese mainland. This study evaluates the temporal-spatial performance of ERA5 precipitation data from 1979 to 2018 based on gridded-ground meteorological station observational data across China. The results showed that ERA5 data could capture the annual and seasonal patterns of observed precipitation in China well, with correlation coefficient values ranging from 0.796 to 0.945, but ERA5 slightly overestimated precipitation in the summer. Nonetheless, the results also showed that the accuracy of the precipitation products was strongly correlated with topographic distribution and climatic divisions. The performance of ERA5 shows spatial inherently across China that the highest correlation coefficient values locate in eastern, Northwestern and North China and the lowest biases locate in Southeast China. This study provides a reliable data assessment of the ERA5 data and precipitation trend analyses in China. The results provide accuracy references for the further use of precipitation satellite data for hydrological calculations and climate numerical simulations.
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spelling pubmed-84297762021-09-13 Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China Jiao, Donglai Xu, Nannan Yang, Fan Xu, Ke Sci Rep Article ERA5 is the latest fifth-generation reanalysis global atmosphere dataset from the European Centre for Medium-Range Weather Forecasts, replacing ERA-Interim as the next generation of representative satellite-observational data on the global scale. ERA5 data have been evaluated and applied in different regions, but the performances are inconsistent. Meanwhile, there are few precise evaluations of ERA5 precipitation data over long time series have been performed in Chinese mainland. This study evaluates the temporal-spatial performance of ERA5 precipitation data from 1979 to 2018 based on gridded-ground meteorological station observational data across China. The results showed that ERA5 data could capture the annual and seasonal patterns of observed precipitation in China well, with correlation coefficient values ranging from 0.796 to 0.945, but ERA5 slightly overestimated precipitation in the summer. Nonetheless, the results also showed that the accuracy of the precipitation products was strongly correlated with topographic distribution and climatic divisions. The performance of ERA5 shows spatial inherently across China that the highest correlation coefficient values locate in eastern, Northwestern and North China and the lowest biases locate in Southeast China. This study provides a reliable data assessment of the ERA5 data and precipitation trend analyses in China. The results provide accuracy references for the further use of precipitation satellite data for hydrological calculations and climate numerical simulations. Nature Publishing Group UK 2021-09-09 /pmc/articles/PMC8429776/ /pubmed/34504211 http://dx.doi.org/10.1038/s41598-021-97432-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Jiao, Donglai
Xu, Nannan
Yang, Fan
Xu, Ke
Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China
title Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China
title_full Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China
title_fullStr Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China
title_full_unstemmed Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China
title_short Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China
title_sort evaluation of spatial-temporal variation performance of era5 precipitation data in china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8429776/
https://www.ncbi.nlm.nih.gov/pubmed/34504211
http://dx.doi.org/10.1038/s41598-021-97432-y
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