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<p>Extreme winter warm spell in North China (NCWS) has received increasing attention due to its severe impacts on agricultural and social activities along with its increasing frequency in recent years. Here, the boreal winter weather patterns over North China and its surroundings were identified into seven different types according to the Cost733class package, and Type 2 (T2) and Type 4 (T4) weather patterns were found to be the most favorable for the occurrence of the NCWS. Mean daily maximum temperature (Tmax) anomalies corresponding to the T2 and T4 weather patterns reached 2.82&#xa0;°C and 1.51&#xa0;°C, respectively, while the rest of the weather patterns had negative values. Statistical analyses, dynamical diagnostics and linear baroclinic model (LBM) experiments show that both T2 and T4 weather patterns are significantly influenced by the North Atlantic, but correspond to different sea surface temperature (SST) patterns. The T2 weather pattern is significantly influenced by the SST in the central eastern part of the North Atlantic (CENA) with a correlation coefficient of 0.59, while the T4 weather pattern is significantly influenced by the SST in the subtropical North Atlantic (STNA) with a correlation coefficient of -0.45. Experiential models established by the CENA and STNA SSTs can efficiently simulate the T2 and T4 weather pattern days and the NCWS, respectively. This research contributes to improved climate prediction for the NCWS, allowing us to take proactive measures in advance to minimize the impact of the NCWS on ecosystems and human activities.</p>

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Dominant synoptic circulation patterns of the winter warm spells in North China and the joint influence from the central-eastern and subtropical North Atlantic

  • 期刊论文

  • 发表日期：

    2025年6月9日

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  • Tiejun Xie,
  • Hui Gao,
  • Ting Ding

摘要

Extreme winter warm spell in North China (NCWS) has received increasing attention due to its severe impacts on agricultural and social activities along with its increasing frequency in recent years. Here, the boreal winter weather patterns over North China and its surroundings were identified into seven different types according to the Cost733class package, and Type 2 (T2) and Type 4 (T4) weather patterns were found to be the most favorable for the occurrence of the NCWS. Mean daily maximum temperature (Tmax) anomalies corresponding to the T2 and T4 weather patterns reached 2.82 °C and 1.51 °C, respectively, while the rest of the weather patterns had negative values. Statistical analyses, dynamical diagnostics and linear baroclinic model (LBM) experiments show that both T2 and T4 weather patterns are significantly influenced by the North Atlantic, but correspond to different sea surface temperature (SST) patterns. The T2 weather pattern is significantly influenced by the SST in the central eastern part of the North Atlantic (CENA) with a correlation coefficient of 0.59, while the T4 weather pattern is significantly influenced by the SST in the subtropical North Atlantic (STNA) with a correlation coefficient of -0.45. Experiential models established by the CENA and STNA SSTs can efficiently simulate the T2 and T4 weather pattern days and the NCWS, respectively. This research contributes to improved climate prediction for the NCWS, allowing us to take proactive measures in advance to minimize the impact of the NCWS on ecosystems and human activities.