基于 S2S 模式的长江中下游夏季降水次季节预报评估与诊断

Evaluation and diagnosis of subseasonal prediction of summer precipitation in the middle and lower reaches of the Yangtze River by S2S models

摘要

长江中下游是我国夏季降水最为集中的区域之一，提高其次季节预报水平对防汛减灾具有重要意义。基于次季节至季节 (Subseasonal to Seasonal，S2S) 计划里中国气象局 (CMA)、欧洲中期天气预报中心 (ECMWF)、英国气象局 (UKMO) 三套模式 (统称 S2S 模式) 预报资料，系统评估了单模式及多模式集合 (MME) 对长江中下游夏季 1—6 候降水的预报技巧及误差时空结构特征，进一步定量分析了各模式对夏季季节内振荡 (BSISO) 的预报能力及其与降水预报技巧之间的关系。结果表明：(1) 在确定性预报方面，各模式均表现为集合平均优于控制预报，预报技巧随时效延长逐渐衰减；ECMWF 整体最优、UKMO 次之、CMA 相对偏弱。MME 在第 3 候时效以后表现出更稳定且更高的技巧，显示出较高的预报延伸潜力。(2) 概率预报评估显示，ECMWF 在不同降水阈值下均表现最好，且预报技巧随降水阈值升高呈现先增后减特征；MME 在所有时效和所有阈值下均显著优于气候态预报和单模式预报。Brier Score (BS) 评分分解诊断表明，单模式对极端强降水较中部阈值降水表现出更高的可靠性但更低的分辨能力，MME 相较于单模式在可靠性与分辨能力两方面均有明显改进。(3) 各模式对 BSISO 信号的预报技巧与其降水预报技巧具有显著正相关，相关系数达 0.9 以上，BSISO 活动是该区域次季节降水可预报性的关键来源之一。该研究结果有望为各模式在长江中下游夏季降水次季节预报业务中的应用以及预报订正提供参考。

Abstract

The middle and lower reaches of the Yangtze River represent one of the regions in China experiencing heavy summer precipitation. Improving subseasonal prediction skills in this region is therefore of great importance for flood prevention and disaster mitigation. This study systematically evaluates the forecasting skill and error characteristics of both single-model (ECMWF, CMA, and UKMO) and multi-model ensemble systems for summer precipitation in the middle and lower Yangtze River region from lead pentad 1 to 6. We further quantitatively analyze the model ability to forecast BSISO and its relationship with precipitation forecasting skill. The results indicate: (1) In deterministic forecasting, all models show that ensemble mean forecasts outperform control forecasts, with forecast skill gradually decreasing as lead time extends. ECMWF is the best overall, followed by UKMO and CMA. The multi-model ensemble shows the most stable and highest skill after the 3^rd lead pentad, demonstrating greater forecast extension potential. (2) Probability evaluation shows that ECMWF performs the best across all precipitation thresholds, with forecast skill increasing at the beginning and then decreasing as the threshold rises. The multi-model ensemble significantly outperforms both the climate baseline and single-model forecasts across all lead times and thresholds. Brier score decomposition reveals that single-model forecasts for extreme high/low precipitation thresholds exhibit higher reliability but lower resolution compared to mid-range thresholds. In contrast, multi-model ensembles show significant improvements in both reliability and resolution. (3) The skill of models in forecasting BSISO signals is significantly positively correlated with their precipitation forecasting skill, showing correlation coefficients of greater than 0.9 and indicating that BSISO activity is a key source of subseasonal predictability for precipitation over this region. This study provides guidance for application of models in subseasonal precipitation forecasting over the middle and lower Yangtze River, and offers insights for forecast calibration.

关键词

S2S 模式 / 长江中下游 / 夏季降水 / 次季节预报 / 预报技巧

Key words

S2S models / the middle and lower reaches of the Yangtze River / summer precipitation / subseasonal prediction / prediction diagnosis

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基金资助

全国暴雨研究开放基金项目(BYKJ2024Q17，BYKJ2025Q18，BYKJ2025Q25)

国家自然科学基金项目(42205162，42275164)

江苏省自然科学青年基金项目(BK20231110)