预报-观测概率匹配订正法在降水预报业务中的应用

Method of Forecast-observed Probability Matching: Application in Precipitation Forecast

为提高和改进模式产品对汛期降水预报准确率,利用近两年3—7月江西省92个地面气象观测站逐日降水资料和欧洲中心高分辨率数值模式预报24~72 h相应降水预报资料,采用Gamma函数作为累积降水概率分布拟合函数,将模式预报降水累积概率分布与观测降水累积概率分布进行概率匹配,获得不同量级降水的预报订正值,并检验了订正前后预报评分变化。结果显示:模式预报对江西降水预报存在大雨以上量级预报多漏报、小雨多空报的现象;经预报-观测概率匹配订正法订正后,可有效地修正模式预报系统性误差,对各等级降水有良好订正效果,尤其对暴雨的订正效果明显;时效越短订正效果越好。该订正法在业务中具有良好的应用效果。

To improve the accuracy of the model products for precipitation forecast in flood season, we used the daily precipitation data of 92 observation stations in Jiangxi between March and July from 2015 to 2016 and precipitation forecast produced by the ECMWF （24-72 h）, and chose the Gamma function to simulate the probability density distributions of precipitation and to capture the bias information, to match the probability of the model precipitation forecast and observation, and correct the different precipitation levels of model, thus to make a corrected precipitation value over ECMWF for every precipitation levels. The regional distribution characteristics of the model corrected precipitation value and the changes of the forecast scores before and after correction were analyzed. The results showed that： for the precipitation levels larger than 25 mm, the model precipitation forecast was less than the observation; for the low precipitation levels such as light rain, the model precipitation forecast was more than the observation; the model＇ s systematic errors could be effectively corrected after revising. The method of forecast-observation probability matching was effective in improving the quality of precipitation forecast, especially for the heavy precipitation forecast. The shorter the forecast time was, the better the correction would be, and it would have good aoolication effect in business.