摘要
动力降尺度被广泛的应用于区域气候降尺度工作中,用来制作高时空分辨率的区域气候场。本文采用WRF模式的张弛方法对美国第三代再分析资料(CFSR)进行了动力降尺度,使用观测张弛法同化自动气象站观测资料的同时,采用分析张弛法同化了大尺度再分析资料。选取辽宁省7月和10月作为夏季和秋季代表月份,分析不同降尺度方案对地面要素的模拟能力,发现使用张弛方法在区域气候降尺度过程中,可以明显提高地面2 m温度、10 m风速和2 m相对湿度的模拟能力,其中使用张弛算法同化大尺度的再分析资料和观测资料的准确度最高,相较于控制试验,7月和10月温度、风速和相对湿度的平均均方根误差分别减少了25%、39%和30%。
Dynamical downscaling is widely applied in regional climate downscaling to generate regional climate fields with high spatial-temporal resolution. Using the nudging techniques based on the Weather Research and Fore- casting （WRF） model, Climate Forecast System Reanalysis （CFSR） data were dynamically downscaled over Lia- oning province. The observational data from automatic weather stations were assimilated based on the observation nudging method and the large-scale reanalysis data were assimilated based on the analysis nudging method. Meteor- ological elements determined by different downscaling methods were compared with the observations in Liaoning province during July and October to test the accuracy of each method. The results indicated that the modelling ca- pability of temperature at 2 m height,wind speed at 10 m height, and relative humidity at 2 m height is significant- ly improved using nudging methods in the regional climate downscaling process. The simulation performance be- comes even better after assimilating automatic weather station data and the large-scale reanalysis data based on the nudging methods, with the average root-mean-square error of temperature, wind speed, and relative humidity in Ju- ly and October decreasing by 25% ,39% ,and 30% respectively .
作者
易雪
李得勤
赵春雨
周晓宇
崔妍
侯依玲
YI Xue1, LI De-qin2, ZHAO Chun-yu1, ZHOU Xiao-yu1, CUI Yan1, HOU Yi-ling1(1. Regional Climate Center of Shenyang, Shenyang 110166, China; 2. Shenyang Central Meteorological Observatory, Shenyang 110166, Chin)
出处
《气象与环境学报》
2018年第2期1-10,共10页
Journal of Meteorology and Environment
基金
中国气象局气候变化专项(CCSF201608)
国家自然科学基金(41675098)
辽宁省气象局博士科研专项(D201602)共同资助
关键词
区域气候场
WRF模式
观测张弛
分析张弛
气候模拟
Regional climate field
Weather Research and Forecasting （WRF） model
Observation nudging
Analy- sis nudging
Climate modeling
