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Evaluation of the Forecast Performance for North Atlantic Oscillation Onset

Evaluation of the Forecast Performance for North Atlantic Oscillation Onset
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摘要 By utilizing operational forecast products from TIGGE(The International Grand Global Ensemble) during 2006 to 2015,the forecasting performances of the European Centre for Medium-Range Weather Forecasts(ECMWF), National Centers for Environmental Prediction(NCEP), Japan Meteorology Agency(JMA) and China Meteorological Administration(CMA) for the onset of North Atlantic Oscillation(NAO) events are assessed against daily NCEP–NCAR reanalysis data. Twenty-two positive NAO(NAO+) and nine negative NAO(NAO-) events are identified during this time period. For these NAO events,control forecasts, one member of the ensemble that utilizes the currently most proper estimate of the analysis field and the best description of the model physics, are able to predict their onsets three to five days in advance. Moreover, the failure proportion for the prediction of NAO-onset is higher than that for NAO+ onset, which indicates that NAO-onset is harder to forecast. Among these four operational centers, ECMWF has performs best in predicting NAO onset, followed by NCEP,JMA, and then CMA.The forecasting performance of the ensemble mean is also investigated. It is found that, compared with the control forecast, the ensemble mean does not improve the forecasting skill with respect to the onset time of NAO events. Therefore,a confident forecast of NAO onset can only be achieved three to five days in advance. By utilizing operational forecast products from TIGGE(The International Grand Global Ensemble) during 2006 to 2015,the forecasting performances of the European Centre for Medium-Range Weather Forecasts(ECMWF), National Centers for Environmental Prediction(NCEP), Japan Meteorology Agency(JMA) and China Meteorological Administration(CMA) for the onset of North Atlantic Oscillation(NAO) events are assessed against daily NCEP–NCAR reanalysis data. Twenty-two positive NAO(NAO+) and nine negative NAO(NAO-) events are identified during this time period. For these NAO events,control forecasts, one member of the ensemble that utilizes the currently most proper estimate of the analysis field and the best description of the model physics, are able to predict their onsets three to five days in advance. Moreover, the failure proportion for the prediction of NAO-onset is higher than that for NAO+ onset, which indicates that NAO-onset is harder to forecast. Among these four operational centers, ECMWF has performs best in predicting NAO onset, followed by NCEP,JMA, and then CMA.The forecasting performance of the ensemble mean is also investigated. It is found that, compared with the control forecast, the ensemble mean does not improve the forecasting skill with respect to the onset time of NAO events. Therefore,a confident forecast of NAO onset can only be achieved three to five days in advance.
出处 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2019年第7期753-765,共13页 大气科学进展(英文版)
基金 supported by the National Natural Science Foundation of China (Grant Nos. 41230420 and 41775001)
关键词 NAO ONSET OPERATIONAL FORECAST TIGGE DATASET NAO onset operational forecast TIGGE dataset
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