Caio A. S. CoelhoCentro de Previsão de Tempo e Estudos Climáticos (CPTEC)

Instituto Nacional de Pesquisas Espaciais (INPE)caio@cptec.inpe.br

ENSEMBLES meeting on seasonal to decadal prediction Barcelona, 7-8 June 2007

PLAN OF TALK• Aims• Activities• Results• Summary

EUROBRISA: A EURO-BRazilian Initiative for improving South American seasonal forecasts

The EUROBRISA Projectkey Idea: To improve seasonal forecasts in S. America:a region where there is seasonal forecast skill and useful value.

Aims• Strengthen collaboration and promote exchange of expertise and information between European and S. American seasonal forecasters

• Produce improved well-calibrated real-time probabilistic seasonal forecasts for South America

• Develop real-time forecast products for non-profitable governmental use (e.g. reservoir management, hydropower production, agriculture and health)

Involved institutions Country Partners

CPTEC Brazil Coelho, Cavalcanti, CostaSilva Dias, Pezzi

ECMWF EU Anderson, Balmaseda, Doblas-Reyes, Stockdale

INMET Brazil Moura, Silveira, Lucio

Met Office UK Graham, Davey, Colman

Météo France France Déqué

UFPR Brazil Guetter

Uni. of Exeter UK Stephenson

Uni. of São Paulo Brazil Ambrizzi, Silva Dias

http://www.cptec.inpe.br/~caio/EUROBRISA/

CIIFEN Ecuador Camacho

IRI USA Baethgen, Goddard

UFRGS Brazil Bergamaschi

Affiliated institutions

EUROBRISA activities

• Probabilistic forecasts of precip. and temp. with empirical and dynamical coupled models

• Production of objectively combined (dynamical + empirical) well-calibrated integrated forecasts

• Skill assessment of empirical, dynamical and combined forecasts using deterministic and probabilistic measures

• Dynamical and statistical downscaling• Seasonal predictability studies

Climate prediction research and development

Impacts (collaborative work with users)• Hydrology: Downscaling of seasonal forecasts for

river flow predictions and use in hydrological models

• Agriculture: Research on the use of seasonal forecasts in agricultural activities; Downscaling of seasonal forecasts for use in crop models

EUROBRISA multi-model ensemble system

4 coupled global circulation models + 1 empirical model

Coupled Model Country Hindcast period

CPTEC Brazil 1982-2001

ECMWF S3 International 1981-2005

Meteo-France France 1993-2004

UKMO U.K. 1987-2005

Empirical modelPredictor: Atlantic and Pacific SSTPredictands: Precipitation and temperature

Longest common period: 1987-2001 (CPTEC,ECMWF,UKMO)

Precipitation results for JJA

Empirical Integrated

Correlation maps: JJA precip. anomalies

Better skill in tropical South AmericaIntegrated forecasts have improved skill in tropical South America and Southeast Argentina

• Hindcast period: 1987-2001• Coupled models with I.C. 1st May (1-month lead)• Empirical model uses April SST as predictor• Integrated forecasts (coupled + empirical) with forecast assimilation

ECMWF UKMO

Empirical Integrated

Gerrity score for JJA tercile precip. categories

Better skill in tropical South AmericaIntegrated forecasts have improved skill in tropical South America and Southeast Argentina

ECMWF UKMO

• Hindcast period: 1987-2001• Coupled models with I.C. 1st May (1-month lead)• Empirical model uses April SST as predictor• Integrated forecasts (coupled + empirical) with forecast assimilation

Empirical Integrated

ROC skill score for JJA positive anomalies

Integrated forecasts have improved skill in tropical South America and Southeast Argentina

ECMWF UKMO

• Hindcast period: 1987-2001• Coupled models with I.C. 1st May (1-month lead)• Empirical model uses April SST as predictor• Integrated forecasts (coupled + empirical) with forecast assimilation

Empirical Integrated

Brier skill score for JJA precip. in the upper tercile

Integrated forecasts have improved skill in tropical S. America

ECMWF UKMO

• Hindcast period: 1987-2001• Coupled models with I.C. 1st May (1-month lead)• Empirical model uses April SST as predictor• Integrated forecasts (coupled + empirical) with forecast assimilation

Empirical Integrated

Reliability component of the Brier skill score for JJA precip. in the upper tercile

Integrated forecasts have improved reliability in tropical S. America

ECMWF UKMO

• Hindcast period: 1987-2001• Coupled models with I.C. 1st May (1-month lead)• Empirical model uses April SST as predictor• Integrated forecasts (coupled + empirical) with forecast assimilation

Empirical Integrated

Resolution component of the Brier skill score for JJA precip. in the upper tercile

Integrated forecasts have improved resolution in north Brazil

ECMWF UKMO

• Hindcast period: 1987-2001• Coupled models with I.C. 1st May (1-month lead)• Empirical model uses April SST as predictor• Integrated forecasts (coupled + empirical) with forecast assimilation

Empirical Integrated

Example: JJA 2007 precipitation forecast

Most likely tercile category forecast: upper tercile (wet conditions) in North South America

and lower tercile (dry conditions) in central South America

Issued: May 2007

ECMWF UKMO

EUROBRISA summary• Challenging initiative for improving the quality of

South American seasonal forecasts

• Facilitate exchange and transfer of technology, knowledge and expertise between participating institutions

• Valuable opportunity to:- develop an objectively integrated (i.e. dynamical + empirical) forecasting system for

South America- work closely with end-users to evaluate our forecasting system in terms of user variables rather than solely on traditional climate variables

• Preliminary results on seasonal precipitation are encouraging

• More results will be available at http://www.cptec.inpe.br/~caio/EUROBRISA

References: • Coelho C.A.S., S. Pezzulli, M. Balmaseda, F. J. Doblas-Reyes and D. B. Stephenson, 2003: “Skill of Coupled Model Seasonal Forecasts: A Bayesian Assessment of ECMWF ENSO Forecasts”. ECMWF Technical Memorandum No. 426, 16pp.• Coelho C.A.S., S. Pezzulli, M. Balmaseda, F. J. Doblas-Reyes and D. B. Stephenson, 2004: “Forecast Calibration and Combination: A Simple Bayesian Approach for ENSO”. J. Climate, 17, 1504-1516. • Coelho C.A.S. 2005: “Forecast Calibration and Combination: Bayesian Assimilation of Seasonal ClimatePredictions”. PhD Thesis. University of Reading. 178 pp. • Coelho C.A.S., D. B. Stephenson, M. Balmaseda, F. J. Doblas-Reyes and G. J. van Oldenborgh, 2006a: Towards an integrated seasonal forecasting system for South America. J. Climate , 19, 3704-3721. • Coelho C.A.S., D. B. Stephenson, F. J. Doblas-Reyes, M. Balmaseda, A. Guetter and G. J. vanOldenborgh, 2006b: A Bayesian approach for multi-model downscaling: Seasonal forecasting of regionalrainfall and river flows in South America. Meteorological Applications, 13, 73-82. • Stephenson, D. B., Coelho, C. A. S., Doblas-Reyes, F.J. and Balmaseda, M., 2005: “Forecast Assimilation: A Unified Framework for the Combination of Multi-Model Weather and Climate Predictions.” Tellus A, Vol. 57, 253-264.

Available from http://www.cptec.inpe.br/~caio