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Caio A. S. Coelho Centro de Previs ã o de Tempo e Estudos Clim á ticos (CPTEC)

The EUROBRISA operational system. Caio A. S. Coelho Centro de Previs ã o de Tempo e Estudos Clim á ticos (CPTEC) Instituto Nacional de Pesquisas Espaciais (INPE) caio@cptec.inpe.br. PLAN OF TALK 1. Introduction 2. EUROBRISA integrated forecasting system 3. Forecasts for 2007-2008

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Caio A. S. Coelho Centro de Previs ã o de Tempo e Estudos Clim á ticos (CPTEC)

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  1. The EUROBRISA operational system Caio A. S. Coelho Centro de Previsão de Tempo e Estudos Climáticos (CPTEC) Instituto Nacional de Pesquisas Espaciais (INPE) caio@cptec.inpe.br PLAN OF TALK 1. Introduction 2. EUROBRISA integrated forecasting system 3. Forecasts for 2007-2008 4. Skill of the hindcasts 5. Summary 1st EUROBRISA workshop, Paraty, 17-19 March 2008

  2. 1. Seasonal climate forecasts Forecasts of climate conditions for the next 3-6 months DJF • • • • • • • May Apr Mar Feb Nov Dec Jan 0 1 2 3 4 5 6 1-month lead for DJF Current forecast approaches • Empirical/statistical models • Dynamical atmospheric models • Dynamical coupled (ocean-atmosphere) models

  3. Coupled model Country ECMWF System 3 International UKMO U.K. 2. EUROBRISA integrated forecasting system for South America • Combined and calibrated coupled + empirical precip. forecasts • Hybrid multi-model probabilistic system Integrated Empirical model Predictors: Atlantic e Pacific SST Predictand: Precipitation Hindcast period: 1987-2001

  4. The Empirical model • Data sources: • SST: Reynolds OI v2 • Reynolds et al. (2002) • Precipitation: GPCP v2Adler et al. (2003) Y Z Y|Z ~ N (M (Z - Zo),T) Y: DJF precipitation Z: October sea surface temp. (SST) Model uses first three leading Maximum CovarianceAnalysis (MCA) modes of the matrix YT Z. Coelho et al. (2006)

  5. Empirical forecast: DJF 2007/08 Observed Oct 2007 SST DJF 2007 forecast Corr. DJF First mode (71%) Second mode (7.7%) Issued: November 2007

  6. Conceptual framework Data Assimilation “Forecast Assimilation” Stephenson et al. (2005)

  7. Calibration and combination procedure: Forecast Assimilation Stephenson et al. (2005) X: forecasts (coupled + empir.) Y: DJF precipitation Prior: Likelihood: Matrices Posterior: Forecast assimilation uses the first three MCA modes of the matrix YT X.

  8. 1-month lead precip. forecasts EUROSIP: ECMWF UKMO Meteo-FranceEmpirical (SST based) Integrated (Combined) Real time and verification products Web site launched in Oct 2007: http://www6.cptec.inpe.br/eurobrisa/

  9. 3. EUROBRISA forecasts for 2007-2008

  10. Examples of forecast productsProbability of most likely precip. tercile: DJF 2007/08 Integrated Empirical ECMWF UKMO Issued: Nov 2007

  11. Categorical forecast: DJF 2007/08 precip. ECMWF UKMO Integrated Empirical Issued: Nov 2007

  12. Prob. above average precip: DJF 2007/08 ECMWF UKMO Integrated Empirical Issued: Nov 2007

  13. Prob. precip. in lower tercile: DJF 2007/08 ECMWF UKMO Integrated Empirical Issued: Nov 2007

  14. Obs. SST anomaly Feb 2007 EUROBRISA integrated forecast for AMJ 2007 Issued: March 2007 Prob. of most likely precip. tercile (%) Observed precip. tercile Gerrity score (tercile categories) Hindcasts: 1987-2001

  15. Obs. SST anomaly Mar 2007 EUROBRISA integrated forecast for MJJ 2007 Issued: April 2007 Prob. of most likely precip. tercile (%) Observed precip. tercile Gerrity score (tercile categories) Hindcasts: 1987-2001

  16. Obs. SST anomaly Apr 2007 EUROBRISA integrated forecast for JJA 2007 Issued: May 2007 Observed precip. tercile Prob. of most likely precip. tercile (%) Gerrity score (tercile categories) Hindcasts: 1987-2001

  17. Obs. SST anomaly May 2007 EUROBRISA integrated forecast for JAS 2007 Issued: Jun 2007 Prob. of most likely precip. tercile (%) Observed precip. tercile Gerrity score (tercile categories) Hindcasts: 1987-2001

  18. Obs. SST anomaly Jun 2007 EUROBRISA integrated forecast for ASO 2007 Issued: Jul 2007 Prob. of most likely precip. tercile (%) Gerrity score (tercile categories) Observed precip. tercile Hindcasts: 1987-2001

  19. Obs. SST anomaly Jul 2007 EUROBRISA integrated forecast for SON 2007 Issued: Aug 2007 Prob. of most likely precip. tercile (%) Gerrity score (tercile categories) Observed precip. tercile Hindcasts: 1987-2001

  20. Obs. SST anomaly Aug 2007 EUROBRISA integrated forecast for OND 2007 Issued: Sep 2007 Prob. of most likely precip. tercile (%) Gerrity score (tercile categories) Observed precip. tercile Hindcasts: 1987-2001

  21. Obs. SST anomaly Sep 2007 EUROBRISA forecastsfor NDJ 2007/08 Issued: Oct 2007 Prob. of most likely precip. tercile (%) Integrated Empirical ECMWF UKMO

  22. Obs. SST anomaly Oct 2007 EUROBRISA forecastsfor DJF 2007/08 Issued: Nov 2007 Prob. of most likely precip. tercile (%) Integrated Empirical ECMWF UKMO

  23. Obs. SST anomaly Nov 2007 EUROBRISA forecastsfor JFM 2008 Issued: Dec 2007 Prob. of most likely precip. tercile (%) Integrated Empirical ECMWF UKMO

  24. Obs. SST anomaly Dec 2007 EUROBRISA forecastsfor FMA 2008 Issued: Jan 2008 Prob. of most likely precip. tercile (%) Integrated Empirical ECMWF UKMO

  25. Obs. SST anomaly Jan 2008 EUROBRISA forecastsfor MAM 2008 Issued: Feb 2008 Prob. of most likely precip. tercile (%) Integrated Empirical ECMWF UKMO

  26. 4. Skill of the hindcasts

  27. Examples of verification products Correlation btw. obs. and fcst. DJF precip. anom. Empirical Integrated ECMWF UKMO • Hindcast period: 1987-2001 • Coupled models with I.C. 1st Nov (1-month lead for DJF) • Empirical model uses Oct SST as predictor for DJF precip. • Integrated forecasts (coupled + empirical) with forecast assimilation • Best skill in tropical and southeast South America

  28. Brier Skill Score (pos. or neg. anomaly): DJF precipitation Empirical Integrated ECMWF UKMO • Hindcast period: 1987-2001 • Coupled models with I.C. 1st Nov (1-month lead for DJF) • Empirical model uses Oct SST as predictor for DJF precip. • Integrated forecasts (coupled + empirical) with forecast assimilation

  29. Reliability diagram (pos. or neg. anomaly): DJF precipitation Integrated ECMWF UKMO Empirical • Hindcast period: 1987-2001 • Coupled models with I.C. 1st Nov (1-month lead for DJF) • Empirical model uses Oct SST as predictor for DJF precip. • Integrated forecasts (coupled + empirical) with forecast assimilation

  30. ROC curve (pos. or neg. anomaly): DJF precipitation Empirical Integrated ECMWF UKMO • Hindcast period: 1987-2001 • Coupled models with I.C. 1st Nov (1-month lead for DJF) • Empirical model uses Oct SST as predictor for DJF precip. • Integrated forecasts (coupled + empirical) with forecast assimilation

  31. ROC skill score (pos. or neg. anomaly): DJF precipitation Empirical Integrated ECMWF UKMO • Hindcast period: 1987-2001 • Coupled models with I.C. 1st Nov (1-month lead for DJF) • Empirical model uses Oct SST as predictor for DJF precip. • Integrated forecasts (coupled + empirical) with forecast assimilation A is the area under the ROC curve

  32. Ranked probability skill score (tercile categories): DJF precipitation Empirical Integrated ECMWF UKMO • Hindcast period: 1987-2001 • Coupled models with I.C. 1st Nov (1-month lead for DJF) • Empirical model uses Oct SST as predictor for DJF precip. • Integrated forecasts (coupled + empirical) with forecast assimilation

  33. Gerrity score (tercile categories): DJF precipitation Empirical Integrated ECMWF UKMO • Hindcast period: 1987-2001 • Coupled models with I.C. 1st Nov (1-month lead for DJF) • Empirical model uses Oct SST as predictor for DJF precip. • Integrated forecasts (coupled + empirical) with forecast assimilation

  34. 5. Summary • EUROBRISA integrated forecasting system: First operational hybrid (empirical-dynamical) probabilistic seasonal forecasting system for South America • Current operational system: SST-based empirical model + two dynamical coupled models (ECMWF and UKMO) • Good performance in 2007 over regions where forecasts have historically moderate to good skill • Web products include a range of forecast and verification products for the EUROBRISA integrated forecasting system in addition to Meteo-France coupled model forecasts • Additional information at http://www6.cptec.inpe.br/eurobrisa and in Coelho et al.(2007)-CLIVAR Exchanges No 43 (Volume 12 No 4)

  35. References • Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, P. Arkin (2003), The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present). J. Hydrometeor., 4,1147-1167. • Coelho C.A.S., D. B. Stephenson, F. J. Doblas-Reyes, M. Balmaseda and R. Graham, 2007: Integrated seasonal climate forecasts for South America. CLIVAR Exchanges. No.43. Vol. 12, No. 4, 13-19. • Coelho C.A.S., D. B. Stephenson, F. J. Doblas-Reyes and M. Balmaseda, 2005: From multi-model ensemble predictions to well-calibrated probability forecasts: Seasonal rainfall forecasts over South America 1959-2001 CLIVAR Exchanges. No.32. Vol. 10, No. 1, 14-20. • Coelho C.A.S., D. B. Stephenson, M. Balmaseda, F. J. Doblas-Reyes and G. J. van Oldenborgh, 2006: “Towards an integrated seasonal forecasting system for South America”.J. Climate., Vol. 19, 3704-3721. • Reynolds, R. W., N. A. Rayner, T. M. Smith, D. C. Stokes and W. Wang (2002), An improved in situ and satellite SST analysis for climate. J. Climate, 15, 1609-1625. • Stephenson, D. B., C.A.S. Coelho, F. J. Doblas-Reyes, and M. Balmaseda, 2005: “Forecast Assimilation: A Unified Framework for the Combination of Multi-Model Weather and Climate Predictions.” Tellus A, Vol. 57, 253-264.

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