基于时间滞后集合和实时偏差订正的气温精细化预报研究  

Refined Air Temperature Forecast Based on Time-lagged Ensemble and Real-time Bias Correction

作　　者：张武龙[1,2] 陈朝平 杨康权[1,2] 周威 银航[1,2] ZHANG Wulong;CHEN Chaoping;YANG Kangquan;ZHOU Wei;YIN Hang(Sichuan Provincial Meteorological Observatory,Chengdu 610072,China;Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province,Chengdu 610072,China)

机构地区：[1]四川省气象台,成都610072 [2]高原与盆地暴雨旱涝灾害四川省重点实验室,成都610072

出　　处：《高原山地气象研究》2024年第1期51-58,共8页Plateau and Mountain Meteorology Research

基　　金：国家重点研发计划项目(2021YFC3000900);四川智能网格预报创新团队项目(SCQXCXTD-202201);中国气象局气象能力提升联合研究专项重点专项(22NLTSZ006);四川省重点实验室项目(SCQXKJZD202101,SCQXKJYJXMS202112);四川省重点研发项目(2022YFS0542,2022YFS0540);西南区域创新团队项目(XNQYCXTD-202202);中国气象局创新发展专项(CXFZ2023J016,CXFZ2024J013)。

摘　　要：基于SWC-WINGS模式0.01°×0.01°分辨率的小时2 m气温产品,利用时间滞后集合和实时偏差订正,得到新的逐小时滚动更新的1 km网格气温预报,并基于预报准确率、平均误差、平均绝对误差等指标,对2022年7—8月逐日逐时气温预报结果进行检验分析。结果表明:时间滞后集合预报准确率在各时效均高于SWC-WINGS模式最新时次预报,实时偏差订正可明显提升临近时效准确率,1~6 h时效的平均提高率为17.3%。SWC-WINGS模式对于四川地区高、低温预报存在明显的系统性偏差,时间滞后集合对于系统性偏差的改进能力有限,而实时偏差订正可将1 h时效上四川大部分地区低温和高温预报的平均绝对误差分别控制在1℃和2℃以内。针对2022年8月13日四川地区高温天气,时间滞后集合与实时偏差订正集成预报对SWC-WINGS模式预报有较好的订正效果。Based on hourly 2m air temperature product of SWC-WINGS model with a resolution of 0.01°×0.01°,a new 1km grid air temperature forecast with hourly rolling update was obtained by using time-lagged ensemble and real-time bias correction.The hourly air temperature forecast from July to August 2022 was verified by prediction accuracy,average error,and average absolute error.The results showed the accuracy of time-lagged ensemble forecast was higher than that of the up-to-date forecast,and the real-time bias correction leaded to obvious improvement with 17.3%in 1~6 h forecasts.The SWC-WINGS model had obvious systematic bias in the prediction of high and low temperature in Sichuan,and the time-lagged ensemble reduced the deviation weakly.The real-time bias correction could control the average absolute error of low and high temperature forecast in most areas of Sichuan within 1℃and 2℃,respectively.For the high temperature weather in Sichuan on 13 August 2022,the integration forecast of time-lagged ensemble and real-time bias correction had a high positive skill compared with SWC-WINGS model.

关 键 词：1公里网格 SWC-WINGS 时间滞后 偏差订正 

分 类 号：P457.3[天文地球—大气科学及气象学]