基于OMOS方法的地面气温短时预报——以重庆市为例  

Application of OMOS in short-term forecast of surface air temperature in Chongqing

作　　者：王田 季焱 杜钦 朱寿鹏 智协飞[2] WANG TianJI Yan;DU Qin;ZHU Shoupeng;ZHI Xiefei(Henan Meteorological Observation Data Center,Henan Key Laboratory of Agrometeorological Support and Applied Technique,China Meteorological Administration,Zhengzhou 450003,China;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science&Technology,Nanjing 210044,China;Chongqing Institute of Meteorological Sciences,Chongqing 401147,China;Key Laboratory of Transportation Meteorology,CMA,Nanjing 210041,China;Nanjing Joint Institute for Atmospheric Sciences,Nanjing 210041,China)

机构地区：[1]河南省气象探测数据中心/河南省农业气象保障与应用技术重点实验室,郑州450003 [2]南京信息工程大学气象灾害预报预警与评估协同创新中心,南京210044 [3]重庆市气象科学研究所,重庆401147 [4]中国气象局交通气象重点开放实验室,南京210041 [5]南京气象科技创新研究院,南京210041

出　　处：《气象科学》2023年第5期652-661,共10页Journal of the Meteorological Sciences

基　　金：重庆市气象局业务技术攻关重点(团队)项目(ywgg-201412);中国气象局河南省农业气象保障与应用技术重点实验室开放研究基金(AMF202111)。

摘　　要：基于重庆市气象局业务运行的风暴尺度快速同化和预报系统(Storm-Scale Rapid Assimilation and Forecast System,SSRAFS)、气象信息综合分析处理系统(Meteorological Information Comprehensive Analysis And Process System,MICAPS)地面观测和高空观测资料,进行模式输出统计(Model Output Statistics,MOS)方法和纳入超前实况因子的MOS(MOS with Prior Observation Predictors,OMOS)方法对重庆地区地面气温96 h内逐小时预报试验,并以SSRAFS地面气温预报结果作为参考进行对比分析。结果表明:MOS方法在1~96 h预报时效内的预报技巧高于SSRAFS,气温预报均方根误差(Root Mean Square Error,RMSE)平均减小1.22℃,CC和HR2分别平均增大0.006和20.4%;在1~7 h预报时效,RMSE平均减小1.70℃,CC和HR2分别平均增大0.07和34.5%;且MOS方法在重庆东北部及中南部地区改进效果较为明显。OMOS方法在气温短期预报中表现优于MOS方法,尤其在1~7 h预报时效,比MOS方法RMSE平均减小0.43℃,CC和HR2分别平均增大0.008和8.3%;其在1~4 h预报时效时表现更加优异,与MOS方法相比,RMSE平均减小0.66℃,CC和HR2分别平均增大0.13和12.3%。因此,在MOS的基础上,OMOS能够进一步提升地面气温的预报技巧,且在重庆东北部及中南部地区的预报效果有明显改进。Based on the Storm-Scale Rapid Assimilation and Forecast System(SSRAFS)operated by the Chongqing Meteorological Administration,along with MICAPS ground observation and upper-air observation data,this study conducted experiments on hourly surface air temperature forecasts within 96 hours for the Chongqing region.Model Output Statistics(MOS)and MOS with Prior Observation Predictors(OMOS)methods were utilized,and a comparative analysis was performed by using the SSRAFS surface air temperature forecasts as a reference.Results indicate that MOS outperforms SSRAFS in terms of forecasting skill for lead times ranging from 1 to 96 hours.On average,MOS reduces the RMSE of surface air temperature forecasts by 1.22℃,while increasing CC and HR2 by 0.006 and 20.4%respectively.For 1-7 h forecasts,MOS achieves an average decrease in RMSE of 1.70℃,and average increases in CC and HR2 of 0.07 and 34.5%,respectively.MOS exhibits a more noticeable improvement in the northeastern and south-central regions of Chongqing.Comparatively,OMOS performs better than MOS for short-term temperature forecasts,particularly within 1-7 h lead times,with an average decrease in RMSE of 0.43℃,and average increases in CC and HR2 of 0.008 and 8.3%,respectively.OMOS demonstrates even better performance during 1-4 h lead times,with an average decrease in RMSE of 0.66℃,and average increases in CC and HR2 of 0.13 and 12.3%,respectively,compared to MOS.Therefore,OMOS further enhances the forecasting skill of surface air temperature based on MOS,with significant improvements observed in the northeastern and south-central regions of Chongqing.

关 键 词：MOS预报 OMOS 地面气温 

分 类 号：P456.7[天文地球—大气科学及气象学]