Comparing TIGGE multimodel forecasts with reforecast‐calibrated ECMWF ensemble forecasts

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 © 2012 Royal Meteorological Society

[1]  Mio Matsueda,et al.  Can MCGE Outperform the ECMWF Ensemble , 2008 .

[2]  John S. Woollen,et al.  NCEP-DOE AMIP-II reanalysis (R-2). Bulletin of the American Meteorological Society . , 2002 .

[3]  David S. Richardson,et al.  Effects of observation errors on the statistics for ensemble spread and reliability , 2004 .

[4]  J. Keller,et al.  Investigation of predictability during the extratropical transition of tropical cyclones using the THORPEX interactive grand global ensemble (TIGGE) , 2010 .

[5]  Thomas M. Hamill,et al.  Ensemble Calibration of 500-hPa Geopotential Height and 850-hPa and 2-m Temperatures Using Reforecasts , 2007 .

[6]  L. Isaksen,et al.  The ERA-40 Reanalysis , 2004 .

[7]  Bob Glahn,et al.  Reforecasts: An Important Dataset for Improving Weather Predictions , 2008 .

[8]  Mark A. Liniger,et al.  Can multi‐model combination really enhance the prediction skill of probabilistic ensemble forecasts? , 2007 .

[9]  Huug van den Dool,et al.  An analysis of multimodel ensemble predictions for seasonal climate anomalies , 2002 .

[10]  A. Sterl,et al.  The ERA‐40 re‐analysis , 2005 .

[11]  Renate Hagedorn,et al.  Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part II: Precipitation , 2008 .

[12]  Upmanu Lall,et al.  Improved Combination of Multiple Atmospheric GCM Ensembles for Seasonal Prediction , 2004 .

[13]  T. N. Krishnamurti,et al.  Improved Weather and Seasonal Climate Forecasts from Multimodel Superensemble. , 1999, Science.

[14]  Thomas M. Hamill,et al.  Comparison of Ensemble-MOS Methods Using GFS Reforecasts , 2007 .

[15]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[16]  David S. Richardson,et al.  On the effect of ensemble size on the discrete and continuous ranked probability scores , 2008 .

[17]  Mark A. Liniger,et al.  Seasonal Ensemble Forecasts: Are Recalibrated Single Models Better than Multimodels? , 2009 .

[18]  Andrew P. Morse,et al.  DEVELOPMENT OF A EUROPEAN MULTIMODEL ENSEMBLE SYSTEM FOR SEASONAL-TO-INTERANNUAL PREDICTION (DEMETER) , 2004 .

[19]  P. Houtekamer,et al.  Data Assimilation Using an Ensemble Kalman Filter Technique , 1998 .

[20]  Martin Köhler,et al.  Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time‐scales , 2008 .

[21]  Ensemble Configurations for Typhoon Precipitation Forecasts , 2003 .

[22]  H. Hersbach Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems , 2000 .

[23]  F. Doblas-Reyes,et al.  Multi-model seasonal hindcasts over the Euro-Atlantic: skill scores and dynamic features , 2000 .

[24]  T. Palmer,et al.  Stochastic representation of model uncertainties in the ECMWF ensemble prediction system , 2007 .

[25]  Thomas M. Hamill,et al.  Probabilistic Quantitative Precipitation Forecasts Based on Reforecast Analogs: Theory and Application , 2006 .

[26]  Renate Hagedorn,et al.  Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part I: Two-Meter Temperatures , 2008 .

[27]  P. L. Houtekamer,et al.  Verification of an Ensemble Prediction System against Observations , 2007 .

[28]  Uncertainty in atmospheric temperature analyses , 2008 .

[29]  Thomas M. Hamill,et al.  Will Perturbing Soil Moisture Improve Warm-Season Ensemble Forecasts? A Proof of Concept , 2006 .

[30]  Craig H. Bishop,et al.  The THORPEX Interactive Grand Global Ensemble , 2010 .

[31]  Renate Hagedorn,et al.  The rationale behind the success of multi-model ensembles in seasonal forecasting — I. Basic concept , 2005 .

[32]  T. Palmer,et al.  Stochastic parametrization and model uncertainty , 2009 .

[33]  Thomas M. Hamill,et al.  Ensemble Reforecasting: Improving Medium-Range Forecast Skill Using Retrospective Forecasts , 2004 .

[34]  Martin Leutbecher,et al.  Scale‐dependent verification of ensemble forecasts , 2008 .

[35]  Anton H. Westveld,et al.  Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation , 2005 .

[36]  Roberto Buizza,et al.  TIGGE: Preliminary results on comparing and combining ensembles , 2008 .

[37]  Richard Swinbank,et al.  Medium‐range multimodel ensemble combination and calibration , 2009 .

[38]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[39]  Thomas M. Hamill,et al.  Hypothesis Tests for Evaluating Numerical Precipitation Forecasts , 1999 .

[40]  M. Kanamitsu,et al.  NCEP–DOE AMIP-II Reanalysis (R-2) , 2002 .

[41]  Renate Hagedorn,et al.  The rationale behind the success of multi-model ensembles in seasonal forecasting — II. Calibration and combination , 2005 .

[42]  Renate Hagedorn,et al.  The rationale behind the success of multi-model ensembles in seasonal forecasting-II , 2005 .

[43]  T. Palmer,et al.  Development of a European Multi-Model Ensemble System for Seasonal to Inter-Annual Prediction (DEMETER) , 2004 .