文献类型：期刊文献

英文题名：Delay in Antarctic Ozone Recovery Projection Based on Bias-Corrected Optimal Chemistry-Climate Model Initiative Phase 1 Models

作者：Shi, Houxiang[1,2];Zhang, Yu[1,2,3];Chen, Junzhe[1,3,4];Xu, Jianjun[2,3,4];Xu, Yuyang[1,2,5]

机构：[1]Guangdong Ocean Univ, Coll Ocean & Meteorol, Lab Coastal Ocean Variat & Disaster Predict, Zhanjiang 524088, Peoples R China;[2]Guangdong Ocean Univ, South China Sea Inst Marine Meteorol, CMA GDOU Joint Lab Marine Meteorol, Zhanjiang 524088, Peoples R China;[3]Guangdong Ocean Univ, Western Guangdong Key Lab Marine Meteorol Disaster, Zhanjiang 524088, Peoples R China;[4]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen 518120, Peoples R China;[5]Minist Nat Resources, Key Lab Space Ocean Remote Sensing & Applicat, Key Lab Climate Resources & Environm Continental S, Zhanjiang 524088, Peoples R China

年份：2026

卷号：18

期号：11

外文期刊名：SUSTAINABILITY

收录：SSCI(收录号：WOS:001790704700001)、SCI-EXPANDED(收录号：WOS:001790704700001)、、Scopus(收录号：2-s2.0-105041552592)、WOS

基金：This research was funded by the National Natural Science Foundation of China (42130605, 42205076 and 72293604), the Project of Key Laboratory of Guangdong Provincial Department of Education (2025KSYS009), and the Guangdong Basic and Applied Basic Research Foundation (2024A1515010064).

语种：英文

外文关键词：Antarctic ozone; CCMI-1; model evaluation; model correction; recovery projection; environmental sustainability

外文摘要：Anthropogenic emissions have caused the Antarctic ozone hole, a major global environmental crisis since the late 20th century. Although ozone recovery began in the early 21st century, substantial uncertainty remains regarding the timing of its return to pre-loss levels. This study innovatively develops a "model optimization-bias correction" framework based on spatial pattern (S1) and long-term trend (S2) metrics, assessing 17 Chemistry-Climate Model Initiative Phase 1 (CCMI-1) models using the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis for the climate (ERA5). Results: (1) Most models accurately reproduce the Antarctic ozone's spatial distribution and long-term trends: MRI-ESM1r1 performs best for spatial patterns (S1 = 0.80), GEOSCCM for long-term trends (S2 = 0.82); EMAC-L90MA, UMSLIMCAT, etc., show poor spatial pattern performance (S1 < 0.30), while IPSL and EMAC-L90MA have large trend biases and underperform in trend simulation (S2 < 0.10). (2) Integrating S1 and S2 scores, the Preferred Multi-Model Ensemble comprising the top eight models (PMME8) minimizes ERA5 deviation, outperforming the multi-model ensemble (MME); the Combined Nonstationary Cumulative Distribution Function matching (CNCDFm) correction of this ensemble reduces systematic bias by 15-60%. (3) Antarctic ozone recovery time shows a gradual delay following optimal model selection and bias correction. PMME-adjusted projects recovery in October 2063 (2053-2072), later than MME (2052) and PMME (2058), with inter-member uncertainty narrowing from 43 years to 19 years. Similarly, this feature is also found for September, November, and the spring mean. This study provides a reliable methodological foundation for projections of Antarctic ozone recovery and offers scientific support for the compliance assessment and policy adjustment of the Montreal Protocol, thereby advancing environmental sustainability and global ozone governance.