S2S气候模式产品在黄河流域径流预测中的应用

次季节气候和径流预测是主动减灾的一个关键。基于国家气候中心第三代气候模式系统的次季节到季节模式(CMA-CPS v3 S2S)的气候预测信息和HBV水文模型,应用集合预测技术研发了未来40 d时段平均径流量和时段内极端干旱概率预测模型,应用平均方差技巧评分、距平相关系数、相对操作特征曲线面积、布赖尔技巧评分开展了回报检验,并检验了2021年黄河流域径流异常预测效果。结果表明,所建模型能够以较高技巧预测黄河流域未来40 d时段平均的径流量,且表现出枯季预测技巧高、湿季技巧低的季节差异;对秋末11月和冬季3个月(12月、1月、2月)的极端干旱概率预测也有较高技巧。对于2021年5—8月黄河上中游干旱和9—10月的秋汛,该方法正确预测了除6月、9月外的其他4个月的径流异常方向,但异常程度与实况存在差异。对径流预测水平影响因素的进一步分析表明,S2S降水预测能力影响径流预测水平,特别是丰水期的径流预测,但还有降水之外的其他因素影响径流预测技巧。

Application of S2S Climate Model Products in Runoff Prediction in the Yellow River Basin

Sub-seasonal to seasonal (S2S) climate and runoff prediction is of great importance for active disaster reduction. The prediction models of runoff anomaly and extreme drought for the future 40 days are developed based on CMA-CPS v3 climate model by National Climate Center, China Meteorological Administration, and a hydrological model HBV. The performance of the models are evaluated with the indices of MSSS, ACC, AUC and BSS for hindcast, and verified for the runoff anomaly prediction over the Yellow River Basin in 2021. The results suggest that runoff mean prediction for the future 40 days is skillful, and the skill is higher in dry season than wet season. Moreover, the extreme drought prediction is skillful in later autumn (November) and the winter months (December, January and February). The direction of monthly runoff anomaly from May to October in 2021 are predicted correctly except in June and September, but the anomaly degrees are different from observation. Finally, the analysis of skill variation with lead time and seasons, and the skill difference between runoff and precipitation reveals that the skill of precipitation prediction by S2S climate model influences runoff skill, especially during wet season. However, there are also other factors than precipitation affecting the skill of runoff prediction.