摘要
北京冬奥服务对站点气象要素预报提出了明确需求,2 m气温预报偏差在±2℃以内,10 m风速预报平均偏差小于观测的30%,文中提出一种基于相似集合嵌套一元线性回归的预报方法—嵌套相似集合(AnEn-Ne),该方法基于相似集合思路,在满足一定条件时,启动其嵌套一元线性回归提供订正预报。冬奥赛期(2021年11月1日—2022年3月15日)实时业务预报表明,嵌套相似集合具有较好的预报效果,相对业务数值模式(CMA-BJ)预报,预报精度显著提高,相对相似集合预报和一元线性回归预报精度明显提高,其预报结果满足冬奥服务需求。复杂地形下的要素预报检验表明,CMA-BJ模式预报2 m气温虽然存在较明显的系统偏差,但与观测相关较强,对观测的表征意义明显,订正后能有效消除复杂地形影响,10 m风速模式预报偏差振荡明显,模式预报与观测相关较弱,表征意义差,订正后站间差异明显;改进CMA-BJ模式复杂地形区近地面风速预报对观测的表征意义,可进一步提高该预报方法对10 m风速订正预报的精度。
Beijing Winter Olympic service has made a clear request for prediction of weather elements at individual sites.The 2 m temperature forecast bias is less than±2℃,and 10 m wind speed forecast bias is less than 30%of observation average.This paper proposes a forecast method based on analog ensemble(AnEn)nested linear regression(LR)—analog ensemble nested linear regression(AnEn-Ne).When certain conditions are met,the nested linear regression is activated to provide revised forecasts.The real-time operational forecasts during the Winter Olympic period(1 November 2021 to 15 March 2022)show that the AnEn-Ne method has a better forecast effect.Compared with that of the CMA-BJ,the forecast accuracy of the AnEn-Ne is improved significantly;compared with that of AnEn and LR,the forecast accuracy of the AnEn-Ne is obviously improved,and the forecasts meet the service demand at the Winter Olympic stations.The verification of forecasted elements in complex terrain area shows that,despite an obvious systematic deviation of 2 m temperature in the forecast by the CMA-BJ,the forecasts are strongly correlated with observations and show an obvious representation of observations,and the influence of complex terrain can be effectively eliminated after correction.The CMA-BJ forecast Bias of 10 m wind speed demonstrates an oscillation feature,and the correlation between the model forecasts and observations is weak,indicating a poor model representation of surface wind.The differences in 10 m wind speed between stations are obvious after correction.Improving the representation of the CMA-BJ model on surface wind speed prediction in complex terrain areas can further improve the accuracy of the method for the correction of 10 m wind speed prediction.
作者
王在文
全继萍
张鑫宇
WANG Zaiwen;QUAN Jiping;ZHANG Xinyu(Institute of Urban Meteorology,Beijing 100089,China)
出处
《气象学报》
CAS
CSCD
北大核心
2023年第6期926-942,共17页
Acta Meteorologica Sinica
基金
国家重点研发计划项目(2018YFF0300102)。
