Climate Change Predictions From A Municipal Perspective – Downscaling Model Projections For Integrated Socioeconomic And Health Analysis In Brazil

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Numerical climate models render data in a gridded format which is often problematic for integrated analysis with other kinds of data in jurisdictional formats. In this paper a method of converting model outputs into a country municipal grid is explained which enabled depicting climate predictions from the Eta-Hadgem2-ES model into the municipal level in Brazil. The conversion was made using a combination of interpolation and buffering techniques in ArcGIS for two emission scenarios (RCP 4.5 and 8.5) and three timeframes (2011-2040, 2041-2070, 2071-2100) for mean temperature increase and number of heatwave days (WSDI). Furthermore, a joint analysis with GDP per capita (GDPc) was undertaken in order to estimate different levels of exposure and vulnerability. The results show a coherent matching of the gridded dataset with a temperature increase gradient from coastal areas towards inland. The joint climate and GDPc analysis show that in the beginning of the century the exposure is more severe in the Centre-West and Southeast regions where GDPc tends to be higher. However, as the century unravels new municipalities without the highest warming but with the lowest GDPc levels emerge from the results. The results show that their warming by the mid-century is high to raise critical levels of exposure, due to very low GDPc levels which in the RCP 8.5 scenario is anticipated to the mid-century. The municipalized database of climate data is an invaluable resource for further integrated analysis studies exploring the implications of climate change on different sectors including human health.