Dynamical downscaling of ECMWF Ensemble seasonal forecasts over East Africa with RegCM3

被引:55
|
作者
Diro, G. T. [1 ]
Tompkins, A. M. [1 ]
Bi, X. [1 ,2 ]
机构
[1] Abdus Salam Int Ctr Theoret Phys, Earth Syst Phys Sect, IT-34100 Trieste, Italy
[2] Chinese Acad Sci, Inst Atmospher Phys, Climate Change Res Ctr, Beijing, Peoples R China
关键词
REGIONAL-CLIMATE MODEL; SCALE ATMOSPHERIC CIRCULATION; SEA-SURFACE TEMPERATURE; INTERANNUAL VARIABILITY; TROPICAL CONVECTION; PREDICTION SYSTEM; NORDESTE BRAZIL; DOMAIN CHOICE; PRECIPITATION; RAINFALL;
D O I
10.1029/2011JD016997
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Dynamical downscaling of ECMWF ERA-interim reanalysis and an ensemble of May-start ECMWF seasonal hindcasts is performed with ICTP's regional climate model (RegCM3) over the horn of Africa for a ten year period. Using ERA-interim 'perfect boundary' conditions the regional model reproduced both the spatial and interannual variability of the region's rainfall and improved the global model's reproduction of year to year rainfall variability, capturing the teleconnection between ENSO and the region's precipitation pattern well. The ensembles of ECMWF seasonal hindcasts and the respective downscaled RegCM3 hindcast suite were then validated in terms of the seasonal climate and deterministic and probabilistic skill scores at a one to four month lead time. Both RegCM3 and ECMWF hindcasts reproduce the spatial and temporal rainfall variability well, but overestimate the mean and variability over the Arabian peninsula and misrepresent the teleconnection between ENSO and precipitation over the western Indian Ocean. The positive bias over the Arabian peninsula in RegCM3 and the teleconnection error between ENSO and precipitation anomalies over the western Indian Ocean are due to the propagation of errors from the driving GCMs to the regional model. Nevertheless, the probabilistic assessment (ROCS and RPSS) indicated that both ECMWF and RegCM3 have significant skill suggesting the potential utility of dynamical forecasts over the region. Comparing the skill of ECMWF and RegCM3 probabilistic hindcasts, ECMWF generally performs better on grid point by grid point comparison and at homogeneous zones over Ethiopia but RegCM3 outperforms when aggregated on a country scale and when compared against high resolution rain gauge data set.
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页数:20
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