摘要
本文以四川省2021年7月14日20时—15日20时(北京时,下同)的暴雨过程为例,利用SAL(Structure-Amplitude-Location)检验方法定量分析了CMA-GFS、CMA-MESO、CMA-EPS、EC和EC-EPS共5个模式对雨带结构、强度、位置预报的准确性,并进一步评估了各模式在四川省主汛期(7月)的空间预报性能,并对强降水过程预报的准确性进行了分析.结果表明:(1)SAL方法可以直观地为预报员提供数值模式对降水结构、强度、位置的预报效果;(2)EC模式对暴雨预报的准确性最高,CMA-MESO对雨带位置的预报有很好的参考价值;(3)在实际预报业务中,强降水可参考CMA-MESO模式适当将EC模式强降水落区进行调整,并对降水量级进行订正.
Abstract
Taking the rainstorm process in Sichuan Province from 20:00 BST on 14 to 20:00 BST on 15 July,2021 as an example,this paper quantitatively analyzed the accuracy of five models(CMA-GFS,CMA-MESO,CMA-EPS,EC and EC-EPS)in forecasting the structure,intensity and location of rain bands by using the SAL test method,and further evaluates the spatial forecasting performance of each model in the main flood season(July)of Sichuan Province,and analyzed the accuracy of heavy rainfall process forecasting.Results show that:(1)the SAL method can intuitively provide forecasters with the prediction effect of numerical models on the structure,intensity and location of rainfall.(2)The EC model has the highest accuracy for rainstorm forecasting,and CMA-MESO has good reference value for the location forecasting of rain belt.(3)In the actual forecasting business,the heavy precipitation can adjust the heavy precipitation location refer to the CMA-MESO model,and the precipitation level can be corrected.
基金项目
国家重点研发资助项目(2021YFC3000900)
四川省自然科学基金资助项目(2023NSFSC0242)
高原与盆地暴雨旱涝灾害四川省重点实验室科技发展基金项目(SCQXKJYJXMS202214)
四川智能网格预报创新团队智能网格—全流程检验评估技术整合资助项目(SCQXKJZD202101-08)
四川智能网格预报创新团队智能网格—全流程检验评估技术整合资助项目(SCQXKJZD202101-04)
维普
万方数据