We performed a dynamic downscaling using REGCM4 regional model driven by MPI global model for current (1990/2012) and near-future (2015/2039) climate in order to characterize the seasonal rainfall regimes throughout t...We performed a dynamic downscaling using REGCM4 regional model driven by MPI global model for current (1990/2012) and near-future (2015/2039) climate in order to characterize the seasonal rainfall regimes throughout the railroad areas in eastern Amazon and southeastern Brazil. The analysis of observational data for the current climate indicated the existence of pronounced spatial variations in rainfall regime across railroad regions during both the rainy and dry seasons. Although models have presented generalized underestimation, the regional model showed improvements on spatial representation and intensity of the rainfall in comparison with global model results. We reported the future projections taking into account the correction of simulated rainfall by the values of the biases found in each respective seasonal regime, so that the results are expressed by percentage changes of the future (2015/2037) relative to the current climate patterns. For the railroad in eastern Amazon, projections indicate a weak decrease of rainfall of about -15% in the rainy season (January to May), however during the dry season (June to October) are expected drastic reductions between -70% and -90% in south (Carajás in Pará state) and north (Sao Luis in Maranhao state) portions. Conversely, for the railroad in southeast Brazil, model projections point out for an increased rainfall regime during the rainy season (October to February) around +30% to +40% in the east part of the region over the Espírito Santo state.展开更多
基金ICTP team for providing REGCM4 code.E.B.De Souza is partially sponsored by CNPQ(PQ2 Proc.3073980/2010-6 and Universal project Proc.484779/2012-5).
文摘We performed a dynamic downscaling using REGCM4 regional model driven by MPI global model for current (1990/2012) and near-future (2015/2039) climate in order to characterize the seasonal rainfall regimes throughout the railroad areas in eastern Amazon and southeastern Brazil. The analysis of observational data for the current climate indicated the existence of pronounced spatial variations in rainfall regime across railroad regions during both the rainy and dry seasons. Although models have presented generalized underestimation, the regional model showed improvements on spatial representation and intensity of the rainfall in comparison with global model results. We reported the future projections taking into account the correction of simulated rainfall by the values of the biases found in each respective seasonal regime, so that the results are expressed by percentage changes of the future (2015/2037) relative to the current climate patterns. For the railroad in eastern Amazon, projections indicate a weak decrease of rainfall of about -15% in the rainy season (January to May), however during the dry season (June to October) are expected drastic reductions between -70% and -90% in south (Carajás in Pará state) and north (Sao Luis in Maranhao state) portions. Conversely, for the railroad in southeast Brazil, model projections point out for an increased rainfall regime during the rainy season (October to February) around +30% to +40% in the east part of the region over the Espírito Santo state.
