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›› 2013, Vol. 36 ›› Issue (4): 700-708.

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

HU  Zeng-yun1,NI  Yong-yong1,2,SHAO  Hua1,YIN  Gang1,2,3,YAN  Yan1,2,JIA Chao-jun1   

  1. 1    State  Key  Laboratory  of  Desert  and  Oasis  Ecology, Xinjiang  Institute  of  Ecology  and  Geography, Chinese  Academy  of  Sciences, Urumqi  830011, Xinjiang, China;   2   University  of  Chinese  Academy  of  Sciences, Beijing   100039, China;3   School  of  Information  Science  and  Engineering, Xinjiang  University, Urumqi  830046, Xinjiang, China
  • Received:2012-12-03 Revised:2013-01-30 Online:2013-07-25

Abstract: In this paper,the applicability of three reanalysis precipitation datasets,CFSR,ERA-Interim and MERRA,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 reanalysis 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 between CFSR,ERA-Interim and MERRA. For each reanalysis data,MERRA precipitation agrees most closely with OBSR=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 correlated 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 between the three reanalysis datasets indicate that CFSR precipitation values are bigger than ERA-Interim from January to May and from October to December with the average difference 16.33 mm,while smaller than ERA-Interim in the other months. The precipitation differences between CFSR and MERRA are positive for all the months during the year,and the corresponding average difference is higher than 21.9 mm. All the monthly precipitations for ERA-Interim are bigger than MERRA,and the biggest differences reach to 24 mm in May,June and July.  (3) For the three reanalysis datasets,the best precipitation accuracy appears in 500-1 000 m ranges. When the altitude is over 1 000 m,the precipitation accuracy is decreasing following the altitude increasing which shows that the simulation results of the three reanalysis are poor at high altitudes. From the above analysis,it was found that although there exists some uncertainties for the three reanalysis simulation results at different months and areas in Central Asia,the sufficient evidences show that the result from MERRA matching the OBS precipitation data is better than that from CFSR and ERA-Interim. Therefore,MERRA precipitation data can be used to study the precipitation spatial and temporal patterns in Central Asia. The results of the applicability study between the three reanalysis datasets and [OBS] can provide theory and technology for the rectifying of the three reanalysis datasets.

Key words: Central Asia, precipitation, reanalysis data, meteorological station information, applicability study

CLC Number: 

  • P426.61