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Predictability of Northeast Brazil Rainfall and Real-Time Forecast Skill, 1987–98

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  • 1 Hadley Centre for Climate Prediction and Research, Met Office, Bracknell, Berkshire, United Kingdom
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Abstract

The predictability of rainy season rainfall over northeast Brazil for the relatively long period 1912–98 is analyzed using dynamical and empirical techniques. The dynamical assessments are based on the HadAM2b atmospheric model forced with the Met Office Global Sea Ice and Sea Surface Temperature Dataset (GISST3). Ensembles of simulations and hindcasts starting from real initial conditions for 1982–93 made under the European Community Prediction of Climate Variations on Seasonal to Interannual Timescales (PROVOST) program are analyzed. The results demonstrate a relatively high degree of predictability. Its source lies mostly in tropical Atlantic and Pacific sea surface temperatures. The results confirm the less extensive evidence of other authors that northeast Brazil is a region where two separate ocean basins influence seasonal climate to a comparable extent. Overall, the sea surface temperature gradient between the northern and southern tropical Atlantic appears to be the more important influence, though El Niño can be dominant when it is strong. These assessments of predictability are consistent with the performance of over a decade of real-time long lead and updated forecasts, issued over the period 1987–98. Multiple regression and linear discriminant analysis prediction techniques, together with model forecasts in the last few years, were used to provide best estimate and probability real-time forecasts of rainy season rainfall. These forecasts had a level of skill that was close to the state of the art in seasonal forecasting

Corresponding author address: Andrew Colman, Met Office, London Rd., Bracknell, Berkshire, RG12 2SY, United Kingdom.

Email: awcolman@meto.gov.uk

Abstract

The predictability of rainy season rainfall over northeast Brazil for the relatively long period 1912–98 is analyzed using dynamical and empirical techniques. The dynamical assessments are based on the HadAM2b atmospheric model forced with the Met Office Global Sea Ice and Sea Surface Temperature Dataset (GISST3). Ensembles of simulations and hindcasts starting from real initial conditions for 1982–93 made under the European Community Prediction of Climate Variations on Seasonal to Interannual Timescales (PROVOST) program are analyzed. The results demonstrate a relatively high degree of predictability. Its source lies mostly in tropical Atlantic and Pacific sea surface temperatures. The results confirm the less extensive evidence of other authors that northeast Brazil is a region where two separate ocean basins influence seasonal climate to a comparable extent. Overall, the sea surface temperature gradient between the northern and southern tropical Atlantic appears to be the more important influence, though El Niño can be dominant when it is strong. These assessments of predictability are consistent with the performance of over a decade of real-time long lead and updated forecasts, issued over the period 1987–98. Multiple regression and linear discriminant analysis prediction techniques, together with model forecasts in the last few years, were used to provide best estimate and probability real-time forecasts of rainy season rainfall. These forecasts had a level of skill that was close to the state of the art in seasonal forecasting

Corresponding author address: Andrew Colman, Met Office, London Rd., Bracknell, Berkshire, RG12 2SY, United Kingdom.

Email: awcolman@meto.gov.uk

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