CFSR、ERA-Interim和MERRA降水资料在中亚地区的适用性  

Applicability study of CFSR,ERA-Interim and MERRA precipitation estimates in Central Asia

作　　者：胡增运[1] 倪勇勇[1,2] 邵华[1] 殷刚[1,2,3] 艳燕[1,2] 贾超君[1] 

机构地区：[1]中国科学院新疆生态与地理研究所,荒漠与绿洲生态国家重点实验室,新疆乌鲁木齐830011 [2]中国科学院大学,北京100049 [3]新疆大学信息科学与工程学院,新疆乌鲁木齐830046

出　　处：《干旱区地理》2013年第4期700-708,共9页Arid Land Geography

基　　金：科技部国际合作项目(2010DFA92720-10);中国科学院“西部之光”博士项目(XBBS201006)

摘　　要：利用中亚1979—2011年间162个观测站点月降水数据（OBS），以平均偏差（MBE）、相关系数（R）、平均绝对误差（MAE）和均方根误差（RMSE）对CFSR、ERA—Interim和MERRA气象再分析降水数据在中亚地区的适用性进行评估。结果表明：（1）3套数据的模拟效果存在明显差异。其中MERRA的模拟精度最高（R=0．71），ERA—Interim次之（R=0．53），CFSR最低（R=0．50）；体现出3套数据不同的同化方案和数据源导致模拟效果的不同；（2）降水的年内变化上，3套再分析数据之间具有较好的一致性，但对OBS均表现出高估，并且对强降水月份（3，4月）高估幅度最大；（3）3套数据对海拔500～1000m地区的降水模拟精度最好，超过1000m后，随海拔升高模拟精度下降。以上规律可为3套数据的订正及其在中亚地区气候变化研究中的应用提供科学依据。In this paper, the applicability of three reanalysis precipitation datasets, CFSR, ERA-Interim and MER- RA, in Central Asia was evaluated with the observed monthly precipitation data （ OBS ） during 1979-2011 from 162 meteorological stations by the correlation analysis, t test and the method of least squares. Accuracies of the reanaly- sis datasets were quantified with mean bias error （ MBE ） , correlation coefficient （ R ）, mean absolute error （ MAE ） and root mean square error （RMSE）. In addition, the variations of the three reanalysis precipitation accuracies at different months and altitudes are analyzed. The results suggest as follows： （1） All the three reanalysis datasets tend to overestimate the OBS precipitation. However, there exist obvious differences of the simulation results be- tween CFSR, ERA-Interim and MERRA. For each reanalysis data, MERRA precipitation agrees most closely with OBS （ R = 0.53, MBE= 5.12 mm） than CFSR and ERA-Interim, the following is ERA-Interim with （R= 0.53, MBE = 17.75 mm） and the worst is CFSR with （R = 0.50, AE = 27.04 mm） although all of them significantly cor- related with the OBS precipitations （p 〈 0.05 ） . This may be affected by the scarcity and uneven distribution of the meteorological stations, the complex topography in Central Asia. Furthermore, different assimilation techniques, data sources and models used in different reanalysis datasets can also cause the different simulation results. （2） CFSR, ERA-Interim and MERRA have the consistency trend in monthly precipitation change. Comparing with the OBS precipitation, the biggest magnitude overestimates appear in March and April for the three reanalysis datasets. While the smallest magnitude overestimates appear in August, September and October. The precipitation differences be- tween the three reanalysis datasets indicate that CFSR precipitation values are bigger than ERA-Interim from Janu- ary to May and from October to December with the average difference 16.33 mm, whi

关 键 词：中亚 降水 再分析数据 站点资料 适用性研究 

分 类 号：P468.024[天文地球—大气科学及气象学]