首页 | 本学科首页   官方微博 | 高级检索  
     

动态最优网格降水消空技术
引用本文:张成军,赵声蓉,任小芳,张亚刚,苏洋. 动态最优网格降水消空技术[J]. 气象科技, 2022, 50(5): 677-685
作者姓名:张成军  赵声蓉  任小芳  张亚刚  苏洋
作者单位:1 中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室,宁夏气象防灾减灾实验室,银川 750002;2 宁夏气象台,银川 750002;国家气象中心,北京 100081
基金项目:2021年中国气象局创新发展专项(CXFZ2021Z034 97)、宁夏回族自治区重点研发计划项目(2021BEG03021)共同资助
摘    要:为了提高5 km分辨率的网格降水预报准确率,针对数值模式网格降水预报产品中尚存在许多降水空报的现象,基于网格降水实况,应用动态建模和机器训练择优技术,借助新检验参数归一化后的单调性、新降水TS公式在计算上的便利性,建立了两种动态最优降水消空技术方案,开展网格降水消空研究。研究表明,两步法抑制了消空阈值偏大现象,归一化法使阈值优选更加直接。用这两种方法,晴雨准确率全部上升,其中,ECMWF(European Centre for Medium-range Weather Forecasts)提高最大(2.39%~4.76%);降水TS评分,ECMWF提高最大,白天提高多(2.98%~3.64%),夜间提高少(1.61%~1.78%),但CMA-SH9(中国气象局上海数值预报模式系统)和CMA-BJ(中国气象局北京快速更新循环数值预报系统)则出现下降。归一化法在白天使晴雨准确率提高最多。分析表明,经过消空处理后,雨空百分率下降数值明显大于雨漏百分率增加数值,从而使空报率出现大幅下降,晴雨准确率也升高明显。

关 键 词:网格降水  消空  动态建模  训练择优
收稿时间:2021-10-28
修稿时间:2022-06-17

Dynamic Optimal Technology for Eliminating False Positive Prediction of Grid Precipitation
ZHANG Chengjun,ZHAO Shengrong,REN Xiaofang,ZHANG Yagang,SU Yang. Dynamic Optimal Technology for Eliminating False Positive Prediction of Grid Precipitation[J]. Meteorological Science and Technology, 2022, 50(5): 677-685
Authors:ZHANG Chengjun  ZHAO Shengrong  REN Xiaofang  ZHANG Yagang  SU Yang
Abstract:In order to improve the accuracy of grid precipitation forecast, aiming at the phenomenon that there are still much empty precipitation forecasts in the numerical model grid precipitation forecast, based on the live grid precipitation, applying the dynamic modelling and machine training, with the monotonicity of normalized new test parameters, and the computational convenience of the new precipitation TS scoring formula, the dynamic optimal elimination of grid by grid precipitation is researched. The research show that the empty precipitation threshold is suppressed in the two step method, and the process of threshold training selection is more direct in the normalized method. With these two methods, the rain or shine accuracy is all increased. Among them, ECMWF (European Centre for Medium Range Weather Forecasts) increases by 2.39%-4.76%; the TS score of ECMWF improves the most, increasing 2.98%-3.64% during the day and increasing 1.61%-1.78% at night. However, the TS scores in CMA SH9 and CMA BJ decline. The normalized method increases the clear/rain forecast accuracy the most during the day. The analysis shows that the drop in the false alarm rate is significantly greater than the missing forecast rate. As a result, the FAR drops significantly, and the clear/rain forecast accuracy also increases significantly.
Keywords:grid precipitation   eliminating false forecast   dynamic modelling   training selection optimal
本文献已被 维普 等数据库收录!
点击此处可从《气象科技》浏览原始摘要信息
点击此处可从《气象科技》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号