文献类型：期刊文献

英文题名：Applicability Evaluation of Antarctic Ozone Reanalysis and Merged Satellite Datasets

作者：Chen, Junzhe[1,2];Zhang, Yu[1,2,3];Shi, Houxiang[1,4];Hu, Hao[1,2];Xu, Jianjun[2,4]

机构：[1]Guangdong Ocean Univ, Coll Ocean & Meteorol, Lab Coastal Ocean Variat & Disaster Predict, Zhanjiang 524088, Peoples R China;[2]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen 518120, Peoples R China;[3]Minist Nat Resources, Key Lab Space Ocean Remote Sensing & Applicat, Key Lab Climate Resources & Environm Continental S, Zhanjiang 524088, Peoples R China;[4]Guangdong Ocean Univ, South China Sea Inst Marine Meteorol, CMA GDOU Joint Lab Marine Meteorol, Zhanjiang 524088, Peoples R China

年份：2025

卷号：16

期号：6

外文期刊名：ATMOSPHERE

收录：SCI-EXPANDED(收录号：WOS:001515276500001)、、EI(收录号：20252618679352)、Scopus(收录号：2-s2.0-105009146179)、WOS

基金：This research was funded by the National Natural Science Foundation of China (42205076, 72293604), the Guangdong Basic and Applied Basic Research Foundation (NO. 2024A1515010064) and the First-Class Discipline Plan of Guangdong Province (080503032101, 231420003).

语种：英文

外文关键词：Antarctic ozone; reanalysis dataset; merged satellite dataset; applicability evaluation; interannual variation; long-term trend

外文摘要：In this study, based on total column ozone observations from eight Antarctic stations, we evaluate the applicability of ERA5, C3S-MSR, MERRA-2, and JRA-55 reanalysis datasets and the NIWA-BS merged satellite dataset, in terms of interannual variation and long-term trend, using the correlation coefficient (R), root-mean-square error (RMSE), interannual variability skill score (IVS), and linear trend bias (TrBias). The results show that for interannual variation, C3S-MSR performs well at multiple stations, while JRA-55 performs poorly at most stations, especially Marambio, Rothera, and Faraday/Vernadsky, which are located at lower latitudes on the Antarctic Peninsula. Additionally, all datasets show significantly higher RMSE at Dumont D'Urville and Arrival Heights, which generally are located around the edge of the Antarctic stratospheric vortex where total column ozone values are more variable and on average larger than in the core of the vortex. The comprehensive ranking results show that C3S-MSR performs the best, followed by ERA5 and NIWA-BS, with MERRA-2 and JRA-55 ranking lower. For the long-term trend, each of the datasets has large bias values at Arrival Heights, and the absolute TrBias values of JRA-55 are larger at three stations on the Antarctic Peninsula. The overall averaged results show that C3S-MSR and NIWA-BS have the smallest absolute TrBias, and perform best in reflecting the Antarctic ozone trends, while ERA5 and JRA-55 significantly overestimate the Antarctic ozone recovery trend and perform poorly. Based on our analysis, the C3S-MSR dataset can be recommended to be prioritized when analyzing the interannual variations in Antarctic stratospheric ozone, and both the C3S-MSR reanalysis and NIWA-BS datasets should be prioritized for trend analysis.