Integrated seasonal climate forecasts for South America Caio

Integrated seasonal climate forecasts for South America 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 • Introduction • Methods • Skill assessment • Summary 10 th International Meeting on Statistical Climatology Beijing, 20 -24 August 2007

1. Seasonal climate forecasts Forecasts of climate conditions for the next 3 -6 mo JJA • • May Jun Jul Aug Sep Oct Nov 0 1 2 3 4 5 6 1 -month lead for JJA Current forecast approaches • Empirical/statistical models • Dynamical atmospheric models • Dynamical coupled (ocean-atmosphere) models

Integrated forecasts for South America Combined and calibrated coupled + empirical fore Coupled model Country ECMWF International UKMO U. K. Integrated Empirical model Predictors: Atlantic e Pacific SST Predictand: Precipitation Hindcast period: 1987 -2001

2. The Empirical model Y Z Y|Z ~ N (M (Z - Zo), T) Y: JJA precipitation Z: April sea surface temperature (SST) Model uses first six leading Maximum Covariance Analysis (MCA) modes of the matrix YT Z. Coelho et al. (2006)

Empirical model leading mode: SCF 53. 7% April SST JJA Precipitation àTropical Pacific (ENSO) and Atlantic are the main sources of seasonal predictability for South America

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

4. Cross validated skill assessment

Correlation maps: JJA precip. anomalies ECMWF • • UKMO Empirical Integrated Hindcast period: 1987 -2001 Coupled models with I. C. 1 st May (1 -month lead for JJA) Empirical model uses April SST as predictor for JJA precip. Integrated forecasts (coupled + empirical) with forecast assimilation àBest skill in tropical South America àIntegrated forecasts have improved skill in tropical and southeast South America

Gerrity score for JJA tercile precip. categories ECMWF • • UKMO Empirical Integrated Hindcast period: 1987 -2001 Coupled models with I. C. 1 st May (1 -month lead for JJA) Empirical model uses April SST as predictor for JJA precip. Integrated forecasts (coupled + empirical) with forecast assimilation àBest skill in tropical South America àIntegrated forecasts have improved skill in tropical and southeast South America

ROC skill score for JJA positive anomalies ECMWF • • UKMO Empirical Integrated Hindcast period: 1987 -2001 Coupled models with I. C. 1 st May (1 -month lead for JJA) Empirical model uses April SST as predictor for JJA precip. Integrated forecasts (coupled + empirical) with forecast assimilation àIntegrated forecasts have improved skill in tropical and southeast South America

The EUROBRISA Project key Idea: To improve seasonal forecasts in S. America: a region where there is seasonal forecast skill and useful value. http: //www. cptec. inpe. br/~caio/EUROBRISA/ Aims • Strengthen collaboration and promote exchange of expertise and information between European and S. American seasonal forecasters Involved institutions Country Partners CPTEC Brazil Coelho, Cavalcanti, Costa Silva Dias, Pezzi ECMWF EU Anderson, Balmaseda, Doblas-Reyes, Stockdale INMET Brazil Moura Met Office UK Graham, Colman Météo France Déqué SIMEPAR Brazil Silveira UFPR institutions Brazil Affiliated Guetter CIIFEN Uni. of Exeter Ecuador UK Camacho Stephenson IRI Uni. of São Paulo USA Brazil Goddard Ambrizzi, Silva Dias UFRGS Brazil Bergamaschi • 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)

5. Summary • Forecast skill can be improved by calibration and combination • Availability of empirical and dynamical model forecasts provides opportunity to produce objectively integrated (i. e. combined and calibrated) forecasts • Preliminary results on seasonal precipitation are encouraging: improved skill in tropical and southeast South America • More results will be available at http: //www. cptec. inpe. br/~caio/EUROBRISA

References: • Coelho C. A. S. , D. B. Stephenson, M. Balmaseda, F. J. Doblas-Reyes and G. J. van Ol Towards an integrated seasonal forecasting system for South America. J. Climate , • 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

Forecast assimilation leading mode: SCF 63. 8% ECMWF UKMO Empirical Observation 1 -month lead for JJA àAll models depict ENSO north-south precipitation dipole

Example: JJA 2007 precipitation forecast ECMWF UKMO Empirical Integrated Issued: May 2007 Most likely tercile category forecast: upper tercile (wet conditions) in North South America and lower tercile (dry conditions) in central South America