Abstract
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.
Highlights
After the agriculture sector, the industry in the mining sector is what has contributed significantly to the Brazilian economy in recent years, so that Brazil has occupied the second position in exports of iron ore globally [1]
We present the future climate projections generated by the MPI and REGCM4 models for both the rainy and dry seasons as changes, i.e., the percentage difference between the future climate (2015/2037) and current climate (1990/2012)
We performed a dynamic downscaling using REGCM4 regional model driven by MPI global model for current (1990 to 2012) and near-future (2015 to 2039) climate conditions in order to characterize the seasonal rainfall regimes throughout railroad regions in the EFC (Pará/Maranhão states) in eastern Amazon and EFVM (Minas Gerais/Espírito Santo states) in southeastern Brazil
Summary
The industry in the mining sector is what has contributed significantly to the Brazilian economy in recent years, so that Brazil has occupied the second position in exports of iron ore globally [1]. In the second semester, driest period of the year, there are prolonged droughts (lack of rainfall) that commonly are associated with conditions of fires in eastern Amazon. Such seasonal phenomena induce negative impacts on ore transport operations, since they can result in decreasing the speed of trains or even cause temporary outages, and are complicating factors in terms of the logistics required to perform the activities of both general operation and maintenance
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