水科学进展2024，Vol.35Issue(1)：48-61,14.DOI:10.14042/j.cnki.32.1309.2024.01.005
顾及分类与定量误差订正的数值预报降水统计后处理方法
Integrated statistical post-processing methods for categorical and quantitative errors correction of numerical precipitation forecasts
摘要
Abstract
The utilization of statistical post-processed numerical precipitation forecasts is a significant approach to extend the effective forecast period of hydrological forecasting.Existed statistical post-processing methods struggle to simultaneously correct dichotomous and quantitative errors,and their impact on the effective forecast lead time for precipitation forecasting is frequently overlooked.In this study,we introduce a novel post-processing scheme called EQM-BMGD,which combines the Empirical Quantile Mapping model(EQM)and the Bernoulli-meta-Gaussian Distribution(BMGD).Additionally,we establish a comprehensive accuracy metric for evaluating the effective forecast period.Using the Han River Basin as a case study,comparative outcomes showed that EQM-BMGD integrated the strengths of the two individual methods,achieving precipitation forecasts with superior accuracy.The forecast accuracy(OP)and mean absolute error(EMA)of the post-processed average-basin forecasts increased by more than 10％,the OP of the forecast period 222-228 h was still close to 0.7,and EMA was less than 0.7 mm/(6h),and the EFPs were extended by 18-66 h.On a grid scale,the gains of OP and EMA for the 96-102 h forecast period exceeded 10％and 20％respectively for all grids.Except for a few grids in the southwest,the OP surpassed 0.8 while the EMA remained below 1.0 mm/(6 h).In addition,the EFPs of the grids in the northern part were lengthened by 18-54 h.It is demonstrated that the EQM-BMGD can effectively correct both categorical and quantitative errors,thereby enriching the available methodologies for statistical post-processing of numerical precipitation forecasts.关键词
数值预报降水/统计后处理/经验分位数映射/伯努利-元高斯分布/有效预见期Key words
numerical precipitation forecast/statistical post-processing/empirical quantile mapping/bernoulli-meta-gaussian/effective forecast period分类
天文与地球科学引用本文复制引用
李伶杰,王银堂,云兆得,刘勇,王磊之,苏鑫,徐勇..顾及分类与定量误差订正的数值预报降水统计后处理方法[J].水科学进展,2024,35(1):48-61,14.基金项目
国家重点研发计划资助项目(2022YFC3202802) （2022YFC3202802）
国家自然科学基金资助项目(52009081)The study is financially supported by the National Key R&D Program of China(No.2022YFC3202802)and the National Natural Science Foundation of China(No.52009081). （52009081）
