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<p>Based on station observations, reanalysis, and model data from 1961 to 2024, the causes of precipitation anomalies were analyzed through circulation diagnosis and correlation analysis of external forcing signals. It is revealed that the main reasons for the abnormally excessive midsummer precipitation in the Songhua River Basin in 2023 are the stronger East Asian summer monsoon, the northward shift of the ridge line of the Western Pacific Subtropical High, combined with the periodic activity of the Northeast Cold Vortex in the middle and high latitudes and the water vapor transport from southern typhoon systems. Key factors were selected using the prediction skills of numerical models to establish an objective prediction model. Verification shows that the average Pattern Anomaly Score (Ps) for the 1991–2020 period is 73.8, while the average Ps for four-year independent samples is 70.3. These higher scores indicate that the objective prediction model has a certain level of predictive skill for both the spatial pattern and trend of precipitation.</p>

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Investigating the synergistic drivers and zonal prediction of summer extreme precipitation in the Songhua River Basin in 2023

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月9日

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  • Jin Ban,
  • Jiaying Zhao,
  • Sizhuo Wei,
  • Ying Wang,
  • Xiaoxue Wang

摘要

Based on station observations, reanalysis, and model data from 1961 to 2024, the causes of precipitation anomalies were analyzed through circulation diagnosis and correlation analysis of external forcing signals. It is revealed that the main reasons for the abnormally excessive midsummer precipitation in the Songhua River Basin in 2023 are the stronger East Asian summer monsoon, the northward shift of the ridge line of the Western Pacific Subtropical High, combined with the periodic activity of the Northeast Cold Vortex in the middle and high latitudes and the water vapor transport from southern typhoon systems. Key factors were selected using the prediction skills of numerical models to establish an objective prediction model. Verification shows that the average Pattern Anomaly Score (Ps) for the 1991–2020 period is 73.8, while the average Ps for four-year independent samples is 70.3. These higher scores indicate that the objective prediction model has a certain level of predictive skill for both the spatial pattern and trend of precipitation.