Sources of Subseasonal Prediction Skill for Heatwaves over the Yangtze River Basin Revealed from Three S2S Models

Abstract

Based on the reforecast data (1999–2010) of three operational models [the China Meteorological Administration (CMA), the National Centers for Environmental Prediction of the U.S. (NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF)] that participated in the Subseasonal to Seasonal Prediction (S2S) project, we identified the major sources of subseasonal prediction skill for heatwaves over the Yangtze River basin (YRB). The three models show limited prediction skills in terms of the fraction of correct predictions for heatwave days in summer; the Heidke Skill Score drops quickly after a 5-day forecast lead and falls down close to zero beyond the lead time of 15 days. The superior skill of the ECMWF model in predicting the intensity and duration of the YRB heatwave is attributable to its fidelity in capturing the phase evolution and amplitude of high-pressure anomalies associated with the intraseasonal oscillation and the dryness of soil moisture induced by less precipitation via the land-atmosphere coupling. The effects of 10–30-day and 30–90-day circulation prediction skills on heatwave predictions are comparable at shorter forecast leads (10 days), while the biases in 30–90-day circulation amplitude prediction show close connection with the degradation of heatwave prediction skill at longer forecast leads (> 15–20 days). The biases of intraseasonal circulation anomalies further affect precipitation anomalies and thus land conditions, causing difficulty in capturing extremely hot days and their persistence in the S2S models.

摘要

次季节预测是衔接中短期预报与气候预测的纽带, 是发展无缝隙天气–气候预报系统的重要环节, 然而当今业务模式对次季节预测的能力相对薄弱。了解次季节可预报性来源, 进而提高灾害天气的次季节预测技巧, 是国际前沿科学难题。WMO次季节–季节(S2S)预测计划的多模式数据库为探索灾害天气次季节预测的潜在可预报性提供了机会。本文利用S2S计划的三家业务预报中心模式(CMA、NCEP、ECMWF)回报数据, 评估并诊断了影响长江流域热浪次季节可预报性的关键因子。结果表明, 当模式准确预测出西北太平洋上季节内尺度高压异常的位相演变和振幅, 及相应的环流和降水改变所导致土壤湿度变化时, 其对热浪的发生、强度与持续时间有较高预报技巧。不同频段的次季节环流预报技巧偏差对热浪预测的影响存在差异, 当预报提前时间较短时(提前10天), 10–30d和30–90d环流预报技巧对热浪预测的影响相当, 然而在预报提前时间较长时(提前15–20d以上), 30–90d环流预报的偏差是导致热浪预报技巧下降的关键因素。季节内环流异常的偏差再通过影响降水异常调制土壤状态, 使模式中缺乏支持高温增强的有利条件。