Comparing TIGGE multimodel forecasts with reforecast-calibrated ECMWF ensemble forecasts

被引:103
作者
Hagedorn, Renate [1 ,2 ]
Buizza, Roberto [1 ]
Hamill, Thomas M. [3 ]
Leutbecher, Martin [1 ]
Palmer, T. N. [1 ]
机构
[1] European Ctr Medium Range Weather Forecasts, Reading RG2 9AX, Berks, England
[2] Deutsch Wetterdienst, Offenbach, Germany
[3] NOAA, Earth Syst Res Lab, Boulder, CO USA
关键词
multimodel ensemble; reforecasts; calibration; forecast evaluation; PRECIPITATION FORECASTS; PREDICTION SYSTEM; COMBINATION; REANALYSIS; SKILL; MODEL; VERIFICATION; TEMPERATURES; STATISTICS; RATIONALE;
D O I
10.1002/qj.1895
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Forecasts provided by the THORPEX Interactive Grand Global Ensemble (TIGGE) project were compared with reforecast-calibrated ensemble predictions from the European Centre for Medium-Range Weather Forecasts (ECMWF) in extratropical regions. Considering the statistical performance of global probabilistic forecasts of 850 hPa and 2 m temperatures, a multimodel ensemble containing nine ensemble prediction systems (EPS) from the TIGGE archive did not improve on the performance of the best single-model, the ECMWF EPS. However, a reduced multimodel system, consisting of only the four best ensemble systems, provided by Canada, the USA, the United Kingdom and ECMWF, showed an improved performance. The multimodel ensemble provides a benchmark for the single-model systems contributing to the multimodel. However, reforecast-calibrated ECMWF EPS forecasts were of comparable or superior quality to the multimodel predictions, when verified against two different reanalyses or observations. This improved performance was achieved by using the ECMWF reforecast dataset to correct for systematic errors and spread deficiencies. The ECMWF EPS was the main contributor for the improved performance of the multimodel ensemble; that is, if the multimodel system did not include the ECMWF contribution, it was not able to improve on the performance of the ECMWF EPS alone. These results were shown to be only marginally sensitive to the choice of verification dataset. Copyright (c) 2012 Royal Meteorological Society
引用
收藏
页码:1814 / 1827
页数:14
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