Caio A' S' Coelho

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

• Caio A. S. Coelho
• Centro de Previsão de Tempo e Estudos Climáticos
  (CPTEC)
• Instituto Nacional de Pesquisas Espaciais (INPE)
• caio_at_cptec.inpe.br

• PLAN OF TALK
• History
• Aims
• Planned activities
• Motivating results
• Summary

CPTEC-IRI Workshop , Cachoeira Paulista (Brazil),
8 November 2006
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History of EUROBRISA

• 2001-2005 PhD work on forecast calibration and
  combination (Coelho 2005)
• Developed conceptual framework for forecasting
• (Bayesian approach named forecast assimilation)
• Nino index (Coelho et al. 2003, 2004)
• Equatorial Pacific SST
• (Stephenson et al. 2005)
• South American rainfall
• (Coelho et al. 2006a)
• Regional rainfall and river flow downscaling
• (Coelho et al. 2006b)
• 2005 Preparation, submission and approval of
  EUROBRISA proposal by ECMWF council
• 2005/2006 Preparation, submission and approval
  of young investigator fellowship by FAPESP and
  start of EUROBRISA

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The EUROBRISA Projectkey Idea To improve
seasonal forecasts in S. Americaa region where
there is seasonal forecast skill and useful
value.
http//www.cptec.inpe.br/caio/EUROBRISA/index.htm
l

• 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, and
  agriculture)

Affiliated institutions
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Planned activities
Climate prediction research and development

• Produce probabilistic forecasts of precip. and
  temp. with empirical and dynamical coupled models
  
• Deliver objectively combined (dynamical
  empirical) well-calibrated forecasts
• Compare skill of empirical, dynamical and
  combined forecasts using deterministic and
  probabilistic measures
• Dynamical and statistical downscaling
• Seasonal predictability studies

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

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EUROBRISA multi-model ensemble system

• 4 coupled global circulation models 1 empirical
  model

Empirical model Predictor Atlantic and Pacific
SST Predictands Precipitation and temperature
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Correlation maps DJF rainfall anomalies
DEMETER Multi-model ()
Empirical
Integrated
ECMWF, Meteo-France, UKMO (1959-2001), I.C.
November

• Comparable level of determinist skill
• Better skill in tropical and southeastern South
  America

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Mean Anomaly Correlation Coefficient
Empirical
Multi-model
Integrated
Most skill in ENSO years and forecast
assimilation can improve skill
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Brier Skill Score for DJF rainfall
ENS
Multi-model
Integrated
Empirical
Forecast assimilation improved Brier Skill Score
(BSS) in the tropics
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Brier Score decomposition
reliability
uncertainty
resolution
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Reliability component of the BSS
Multi-model
Integrated
Empirical
Forecast assimilation improved reliability in
many regions
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Resolution component of the BSS
Integrated
Multi-model
Empirical
Forecast assimilation improved resolution in the
tropics
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Regional rainfall downscaling
Multi-model ensemble 3 DEMETER coupled
models ECMWF, Meteo-France, UKMO 3-month
lead Start Aug NDJ Period 1959-2001
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South box NDJ rainfall anomaly
Multi-model
- - - Observation
Forecast
Forecast assimilation
(Coelho et al. 2006b)

• Forecast assimilation improves skill substantially

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North box NDJ rainfall anomaly
Multi-model
- - - Observation
Forecast
Forecast assimilation
(Coelho et al. 2006b)

• Forecast assimilation improved skill marginally

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River flow predictions (NDJ)
Annual cycle
(Coelho et al. 2006b)

• Harder to downscale river flow than rainfall

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Agricultural application
(Challinor et al. 2004)
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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
• Collaborative activities with IRI are of great
  interest

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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
  Climate
• Predictions. 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.
  van
• Oldenborgh, 2006b A Bayesian approach for
  multi-model downscaling Seasonal forecasting of
  regional
• rainfall 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