Abstract

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 joint analysis of municipal Gross Domestic Product per capita (GDPc) and predicted temperature increase was undertaken in order to estimate different levels of human and economic exposure. This is based on a method of converting model outputs into a country municipal grid which enabled depicting climate predictions from the Eta-Hadgem2-ES Regional Climate Model (RCM) into the municipal level in Brazil. The conversion to country municipality grid 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). The results were used to support the Third National Communication (TCN) of Brazil to the United Nations Framework Convention on Climate Change (UNFCCC) and show a coherent matching of the gridded output from the original RCM. The joint climate and GDPc analysis show that in the beginning of the century the more severe warming is centred over regions where GDPc is generally higher (Centre-West and Southeast). At the end of the century, critical levels of warming spread north and northeastwards where municipalities have the lowest GDPc levels. In the high emission scenario (RCP 8.5), the strongest warming and the spreading over poorer regions are anticipated to the mid-century. These results are the key to further explore solutions for climate change adaptation based on current resources and prepare in different sectors, for long-term risk management and climate adaptation planning strategies.

Highlights

  • In the prospect of a changing and more extreme climate, different sectors in society have an increasing demand for Climate Services [1] including multi-scenario climate projections for climate change impact and risk assessments

  • To overcome resolution limitations in Global Climate Models (GCMs), dynamical downscaling is often undertaken through nesting regional climate models (RCMs) within GCMs enabling greater resolution for climate impact and risk assessment [2]

  • This paper presents a methodology used to interpolate the gridded outputs from the Eta RCM into the Brazilian municipality network so as to enable an integrated analysis of climate, health and socioeconomic data to inform the Health Chapter of the Third National Communication (TCN) of Brazil to the United Nations Framework Convention on Climate Change (UNFCCC)

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Summary

Introduction

In the prospect of a changing and more extreme climate, different sectors in society have an increasing demand for Climate Services [1] including multi-scenario climate projections for climate change impact and risk assessments. The Eta RCM has been developed by the Brazilian CPTEC/INPE and has been operational for weather forecasting since 1997 In recent years it has been considered sufficiently robust for dynamical downscaling [3] and regional climate change studies [4]. The latest advancement in the Eta RCM is its 20 km resolution where, nested within two CMIP5 models (Hadgem2-ES and MIROC5) and the Brazilian Earth System Model (BESM). This allows for the first time to build a Poor Man’s2 multi-GCM ensemble which enabled a first evaluation and model intercomparison of Eta’s regional climate simulations [5]

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