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<p>Extreme cold events (ECEs) are among the most severe winter climate phenomena in the Northern Hemisphere, resulting in substantial economic losses and human casualties. Previous studies have assessed ECEs via grid-based detection algorithms, revealing a decline in their occurrence since the 1990s under global warming. However, the ability of CMIP6 (Coupled Model Intercomparison Project Phase 6) models to simulate spatiotemporally continuous ECEs remains unclear. This study evaluated the performance of CMIP6 models in simulating three-dimensional winter ECEs over the Northern Hemisphere from 1959 to 2020. The results show that the CMIP6 models significantly underestimate the frequency, duration, and intensity of ECEs while overestimating their projection area. Using metrics such as the Perkins skill score (PSS), root-mean-square error (RMSE), interannual variability skill score (IVS) and multimodel ensemble average (MME), we identified the top seven models that outperform the CMIP6 MME in historical simulations. These models were further assessed for their ability to simulate strong and weak ECEs. The findings indicate that the selected models effectively capture the increasing trend of strong ECEs and the decreasing trend of weak ECEs. Using the best-performing models, we analyzed the impact of human activities on ECEs. The results revealed that weak ECEs decrease under greenhouse gas (GHG) forcing but increase under anthropogenic aerosol (AA) forcing. In contrast, strong ECEs increase under both GHG and AA forcing but decrease under natural (NAT) forcing. These findings underscore the continued risk of severe ECE-related disasters, highlighting the need for further research to mitigate economic losses and guide adaptation.</p>

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Assessment of winter three-dimensional extreme cold events over the Northern Hemisphere during 1959–2020 based on CMIP6 models

  • 期刊论文

  • 发表日期：

    2025年8月14日

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  • Xiaoxia Wang,
  • Yongli He,
  • Jingjing Jia,
  • Hao Wang,
  • Xin Li,
  • Tingting Chen,
  • Xiaodan Guan

摘要

Extreme cold events (ECEs) are among the most severe winter climate phenomena in the Northern Hemisphere, resulting in substantial economic losses and human casualties. Previous studies have assessed ECEs via grid-based detection algorithms, revealing a decline in their occurrence since the 1990s under global warming. However, the ability of CMIP6 (Coupled Model Intercomparison Project Phase 6) models to simulate spatiotemporally continuous ECEs remains unclear. This study evaluated the performance of CMIP6 models in simulating three-dimensional winter ECEs over the Northern Hemisphere from 1959 to 2020. The results show that the CMIP6 models significantly underestimate the frequency, duration, and intensity of ECEs while overestimating their projection area. Using metrics such as the Perkins skill score (PSS), root-mean-square error (RMSE), interannual variability skill score (IVS) and multimodel ensemble average (MME), we identified the top seven models that outperform the CMIP6 MME in historical simulations. These models were further assessed for their ability to simulate strong and weak ECEs. The findings indicate that the selected models effectively capture the increasing trend of strong ECEs and the decreasing trend of weak ECEs. Using the best-performing models, we analyzed the impact of human activities on ECEs. The results revealed that weak ECEs decrease under greenhouse gas (GHG) forcing but increase under anthropogenic aerosol (AA) forcing. In contrast, strong ECEs increase under both GHG and AA forcing but decrease under natural (NAT) forcing. These findings underscore the continued risk of severe ECE-related disasters, highlighting the need for further research to mitigate economic losses and guide adaptation.