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<p>Using the Sub-seasonal to Seasonal (S2S) data from the European Centre for Medium-Range Weather Forecasts (ECMWF), this study investigates the most predictable modes and prediction skills of late summer precipitation in eastern China, as well as their associated sources of predictability. By employing the maximum signal-to-noise empirical orthogonal function (MSN EOF) analysis on late summer precipitation predictions in eastern China, the results identify the most predictable mode as featuring a strong precipitation signal over the Yangtze River Basin, characterized by a meridional triple pattern. This pattern is significantly linked to sea surface temperature (SST) variations in the equatorial central eastern Pacific and the southern Indian Ocean. During this period, the SST evolution plays a crucial role in driving anomalous circulations over the northwest Pacific, acting as a key source of the predictability. The second predictable mode is characterized by a strengthening signal over the northwest Pacific, a weakening signal in the central western Pacific, and warming in the Indian Ocean. The MSN EOF method effectively captures the ocean-atmosphere interactions underlying these precipitation modes. The main predictable modes and their sources of predictability are further utilized to develop calibration schemes. By selecting high-skill modes, the prediction models are reconstructed to eliminate internal forecast biases, thereby improving precipitation prediction skills. The corrected temporal correlation coefficients indicate significant improvements in forecasts for central and eastern mainland China, offering a potential pathway for improving late summer precipitation predictions in the region.</p>

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Sources of predictability and skill in late summer precipitation forecasts of eastern China: insights from EC-S2S

  • 期刊论文

  • 发表日期：

    2025年6月18日

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  • Xintong Hou,
  • Zhihai Zheng,
  • Guolin Feng,
  • Zheng Chen,
  • Ting Zheng,
  • Pengcheng Yan,
  • Peiyi Fan

摘要

Using the Sub-seasonal to Seasonal (S2S) data from the European Centre for Medium-Range Weather Forecasts (ECMWF), this study investigates the most predictable modes and prediction skills of late summer precipitation in eastern China, as well as their associated sources of predictability. By employing the maximum signal-to-noise empirical orthogonal function (MSN EOF) analysis on late summer precipitation predictions in eastern China, the results identify the most predictable mode as featuring a strong precipitation signal over the Yangtze River Basin, characterized by a meridional triple pattern. This pattern is significantly linked to sea surface temperature (SST) variations in the equatorial central eastern Pacific and the southern Indian Ocean. During this period, the SST evolution plays a crucial role in driving anomalous circulations over the northwest Pacific, acting as a key source of the predictability. The second predictable mode is characterized by a strengthening signal over the northwest Pacific, a weakening signal in the central western Pacific, and warming in the Indian Ocean. The MSN EOF method effectively captures the ocean-atmosphere interactions underlying these precipitation modes. The main predictable modes and their sources of predictability are further utilized to develop calibration schemes. By selecting high-skill modes, the prediction models are reconstructed to eliminate internal forecast biases, thereby improving precipitation prediction skills. The corrected temporal correlation coefficients indicate significant improvements in forecasts for central and eastern mainland China, offering a potential pathway for improving late summer precipitation predictions in the region.