Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China

An increase in extreme temperature events could have a significant impact on terrestrial ecosystems. Reanalysis temperature data are an important data set for extreme temperature estimation in mountainous areas with few meteorological stations. The ability of ERA5-Land reanalysis data to capture the...

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Main Authors: Peng Zhao, Zhibin He, Dengke Ma, Wen Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-02-01
Series:Frontiers in Ecology and Evolution
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fevo.2023.1135895/full
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author Peng Zhao
Peng Zhao
Zhibin He
Dengke Ma
Dengke Ma
Wen Wang
Wen Wang
author_facet Peng Zhao
Peng Zhao
Zhibin He
Dengke Ma
Dengke Ma
Wen Wang
Wen Wang
author_sort Peng Zhao
collection DOAJ
description An increase in extreme temperature events could have a significant impact on terrestrial ecosystems. Reanalysis temperature data are an important data set for extreme temperature estimation in mountainous areas with few meteorological stations. The ability of ERA5-Land reanalysis data to capture the extreme temperature index published by the Expert Team on Climate Change Detection and Indices (ETCCDI) was evaluated by using the observational data from 17 meteorological stations in the Qilian Mountains (QLM) during 1979–2017. The results show that the ERA5-Land reanalysis temperature data can capture well for the daily maximum temperature, two warm extremes (TXx and TX90p) and one cold extreme (FD0) in the QLM. ERA5-Land’s ability to capture temperature extremes is best in summer and worst in spring and winter. In addition, ERA5-Land can capture trends in all extreme temperature indices except the daily temperature range (DTR). The main bias of ERA5-Land is due to the difference in elevation between the ground observation station and the ERA5-Land grid point. The simulation accuracy of ERA5-Land increases with the decrease of elevation difference. The results can provide a reference for the study of local extreme temperature by using reanalysis data.
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spelling doaj.art-fe50adbad75447bcb2837fbfdf1e8b7e2023-02-24T06:09:09ZengFrontiers Media S.A.Frontiers in Ecology and Evolution2296-701X2023-02-011110.3389/fevo.2023.11358951135895Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of ChinaPeng Zhao0Peng Zhao1Zhibin He2Dengke Ma3Dengke Ma4Wen Wang5Wen Wang6Linze Inland River Basin Research Station, Key Laboratory of Inland River Basin Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaLinze Inland River Basin Research Station, Key Laboratory of Inland River Basin Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou, ChinaLinze Inland River Basin Research Station, Key Laboratory of Inland River Basin Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaLinze Inland River Basin Research Station, Key Laboratory of Inland River Basin Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaAn increase in extreme temperature events could have a significant impact on terrestrial ecosystems. Reanalysis temperature data are an important data set for extreme temperature estimation in mountainous areas with few meteorological stations. The ability of ERA5-Land reanalysis data to capture the extreme temperature index published by the Expert Team on Climate Change Detection and Indices (ETCCDI) was evaluated by using the observational data from 17 meteorological stations in the Qilian Mountains (QLM) during 1979–2017. The results show that the ERA5-Land reanalysis temperature data can capture well for the daily maximum temperature, two warm extremes (TXx and TX90p) and one cold extreme (FD0) in the QLM. ERA5-Land’s ability to capture temperature extremes is best in summer and worst in spring and winter. In addition, ERA5-Land can capture trends in all extreme temperature indices except the daily temperature range (DTR). The main bias of ERA5-Land is due to the difference in elevation between the ground observation station and the ERA5-Land grid point. The simulation accuracy of ERA5-Land increases with the decrease of elevation difference. The results can provide a reference for the study of local extreme temperature by using reanalysis data.https://www.frontiersin.org/articles/10.3389/fevo.2023.1135895/fullreanalysisextreme temperatureERA5-LandQilian Mountainsclimate change
spellingShingle Peng Zhao
Peng Zhao
Zhibin He
Dengke Ma
Dengke Ma
Wen Wang
Wen Wang
Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China
Frontiers in Ecology and Evolution
reanalysis
extreme temperature
ERA5-Land
Qilian Mountains
climate change
title Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China
title_full Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China
title_fullStr Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China
title_full_unstemmed Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China
title_short Evaluation of ERA5-Land reanalysis datasets for extreme temperatures in the Qilian Mountains of China
title_sort evaluation of era5 land reanalysis datasets for extreme temperatures in the qilian mountains of china
topic reanalysis
extreme temperature
ERA5-Land
Qilian Mountains
climate change
url https://www.frontiersin.org/articles/10.3389/fevo.2023.1135895/full
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