摘要
基于DERF 2.0模式数据,应用均一化标准差、均方根误差等方法,以2013年乌鲁木齐春季逐日温度及24 h变温检验为背景,初步评估了该模式对延伸期春季强降温过程的预报能力。结果表明:(1)逐日气温预报整体偏差随预报时效推进而增大,延伸期预报偏差明显大于中期。(2)旬平均温度的中期预报偏差普遍在-2～-8℃,延伸期的预报偏差最小在0℃左右,最大为-15.5℃。(3)日平均气温以及最高、最低气温的逐日偏差均以冷偏差为主,偏差范围为5～-15℃,延伸期预报偏差范围为-5～-15℃。模式对升温阶段的预报冷偏差随升温加剧而增大,对降温阶段的预报偏差随降温加剧而减小。24 h变温偏差主要在±5℃范围内变化,延伸期的24 h变温偏差比中期预报偏大可达|8|℃以上。(4)DERF 2.0模式对中短期温度预报有一定水平,延伸期预报能力下降,可参考价值较弱。(5)对强降温过程的结束日的温度预报偏差小,而对过程初始日的温度预报冷偏差大,造成对降温过程的预报暖偏差大,强降温过程普遍漏报。
Based on DERF2.0 data,using the method of Normalized Standard Deviation（NSTD）,RMSE and so on,with the background of Spring daily temperature and 24 h temperature-change evaluation in 2013,a preliminary assessment of DERF 2.0 extended-range prediction ability for spring strong cooling process is made. The results show that：（1） The overall daily temperature bias is increased with impel of forecast time,extended-range forecast bias is more than medium-range obviously.（2） The bias of ten-day average temperature generally in -2 ～-8 ℃,extended-range forecast minimum bias is about 0℃,the maximum bias is -15.5 ℃.（3）Daily bias of T_（2m）、T_（max） and T_（min） is mainly cold,concentrated in 5 ～ 15 ℃,extended-range forecast bias is mainly change between -5～ 15 ℃. Cold bias of warming stage is increase with temperature rise,but the bias of cooling stage is decrease with temperature drop. 24 h temperature-change bias is mainly changes in 5 ℃,the extended-range forecast bias is ｜8｜ ℃ larger than medium-range.（4）The DERF 2.0 model has certain prediction ability to the mid-shot-term temperature,but the ability for extended-range forecast is too weak to reference.（5）There is a small ending-T forecast bias and large cold initial-T bias for strong cooling process,as aresult,it made a large process warm bias and missing report.
作者
李淑娟
毛炜峄
于晓晶
窦新英
陈颖
贾孜拉.拜山
LI Shujuan;MAO Weiyi;YU Xiaojing;DOU Xinying;CHEN Ying;JiazilaBaishan(Institute of Desert Meteorology,CMA,Urumqi 830002,China;Center for Central Asian Atmosphere Science Research,Urumqi 830002,China;Xinjiang Meteorological Observatory,Urumqi 830002,China;Xinjiang Climate Center,Urumqi 830002,China)
出处
《沙漠与绿洲气象》
2018年第3期40-47,共8页
Desert and Oasis Meteorology
基金
中央级公益性科研院所基本科研业务费专项(IDM2016003)
新疆维吾尔自治区科技计划项目(2013911016)
