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Socio-climatic hotspots in Brazil

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Abstract

Brazil suffers yearly from extreme weather and climate events, which can be exacerbated in a warmer climate. Although several studies have analyzed the projections of climate change in Brazil, little attention has been paid to defining the locations that can be most affected, and consequently have a more vulnerable population, in a spatially-explicit form. This study presents a spatial analysis of summarized climate change data and a joint investigation combining these possible climate changes and social vulnerability indicators in Brazil. The Regional Climate Change Index (RCCI), which can synthesize a large number of climate model projections, is used for the climate analysis, and the Socio-Climatic Vulnerability Index (SCVI) is proposed to aggregate local population vulnerabilities to the climate change information. The RCCI results show climatic hotspots emerging in Brazil, covering the western portion of the Northeast (NE), northwestern Minas Gerais state and center-western (CW) and northern regions (N), except northeast Pará and Amapá states. The SCVI analysis reveals major socio-climatic hotspots in the NE and several localized hotspots in some of the major Brazilian metropolitan regions, namely Manaus, Belo Horizonte, Brasília, Salvador, Rio de Janeiro and São Paulo. The two novelties of this study are a spatially detailed analysis of the RCCI in Brazil and the development of an index that can summarize the large amount of climate model information available today with social vulnerability indicators. Both indices may be important tools for improving the dialogue between climate and social scientists and for communicating climate change to policymakers in a more synthetic and socially relevant form.

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References

  • Adger WN (1999) Social vulnerability to climate change and extremes in coastal Vietnam. World Develop 27:249–269

    Article  Google Scholar 

  • Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Tank AMGK, Haylock M, Collins D, Trewin B, Rahimzadeh F, Tagipour A, Kumar KR, Revadekar J, Griffiths G, Vincent L, Stephenson DB, Burn J, Aguilar E, Brunet M, Taylor M, New M, Zhai P, Rusticucci M, Vazquez-Aguirre JL (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109

    Article  Google Scholar 

  • SEPLAN (Secretaria de Estado Planejamento e Desenvolvimento Econômico do Amazonas), Prefeitura de Manaus, Programa das Nações Unidas para Desenvolvimento Brasil, Fundação João Pinheiro. 2006. Atlas do Desenvolvimento Humano em Manaus. Manaus, SEPLAN/Prefeitura de Manaus,/PNUD-Brasil/Fundação João Pinheiro. 24p. Available at: http://www.pnud.org.br/publicacoes/atlas_manaus/Release_Atlas.pdf . Accessed in 01/Feb/2012

  • Baettig MB, Wild M, Imboden DM (2007) A climate change index: Where climate change may be most prominent in the 21st century. Geophys Res Lett 34:L01705

    Article  Google Scholar 

  • Bombardi RJ, Carvalho LMV (2009) IPCC Global coupled climate model simulations of the South America Monsoon System. Clim Dyn 33:893–916

    Article  Google Scholar 

  • Boulanger JP, Martinez F, Segura EC (2006) Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 1: temperature mean state and seasonal cycle in South America. Clim Dyn 27:233–259

    Article  Google Scholar 

  • Boulanger JP, Brasseur G, Carril AF, Castro M, Degallier N, Ereño C, Le Treut H, Marengo JA, Menendez CG, Nuñez MN, Penalba OC, Rolla AL, Rusticucci M, Terra R (2010) A Europe–South America network for climate change assessment and impact studies. Clim Change 98:307–329

    Article  Google Scholar 

  • Christensen JH, Carter TR, Rummukainen M, Amanatidis G (2007) Evaluating the performance and utility of regional climate models: the PRUDENCE project. Clim Change 81:1–6

    Article  Google Scholar 

  • Confalonieri UEC, Marinho DP, Rodriguez RE (2009) Public health vulnerability to climate change in Brazil. Clim Res 40:175–186

    Article  Google Scholar 

  • Davidson EA, Araujo AC, Artaxo P, Balch JK, Brown IF, Bustamante MMC, Coel MT, DeFries RS, Keller M, Longo M, Munger JW, Schroeder W, Soares-Filho BS, Souza CM Jr, Wofsy SC (2012) The Amazon basin in transition. Nature 481:321–328

    Article  Google Scholar 

  • Folha de São Paulo (2010) Reféns da chuva. Folha de São Paulo, 22. Jan.2010, p. C1

  • Folha de São Paulo (2011) Estado do Rio enfrenta a pior chuva em mais de 4 décadas. Folha de São Paulo, 13. Jan.2011, p. A1

  • IPP (Instituto Municipal de Urbanismo Pereira Passos), Instituto Universitário de Pesquisas do Rio de Janeiro, Instituto de Pesquisa Economica Aplicada, Fundação João Pinheiro. 2003. IDH dos bairros do Rio de Janeiro. Available at: http://www.pnud.org.br/pdf/Tabela%206.2.22%20IDH%20bairro%2091_00-15_12_03.xls, Accessed in 01/Feb/2012

  • PNUD (Programa das Nações Unidas para Desenvolvimento Brasil), Companhia de Desenvolvimento Urbano do Estado da Bahia, Fundação João Pinheiro, Instituto Brasileiro de Geografia e Estatística. 2006. Atlas de Desenvolvimento da Região Metropolitana de Salvador. PNUD/CONDER/Fundação João Pinheiro/IBGE. Available at: http://www.pnud.org.br/publicacoes/atlas_salvador/index.php. Accessed in: 01/Feb/2012

  • Diffenbaugh NS, Giorgi F, Raymond L, Bi X (2007) Indicators of 21st century socioclimatic exposure. Proc Natl Acad Sci USA 104:20195–20198

    Article  Google Scholar 

  • Eriksen SH, Kelly PM (2007) Developing credible vulnerability indicators for climate adaptation policy assessment. Mitig Adapt Strategies Glob Chang 12:495–524

    Article  Google Scholar 

  • Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Tank AMGK, Peterson T (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim Res 19:193–212

    Article  Google Scholar 

  • Füssel HM, Klein RJT (2006) Climate change vulnerability assessments: an evolution of conceptual thinking. Clim Change 75:301–329

    Article  Google Scholar 

  • Giorgi F (2005) Climate change prediction. Clim Change 73:239–265

    Article  Google Scholar 

  • Giorgi F (2006) Climate change hot-spots. Geophys Res Lett 33:L08707

    Article  Google Scholar 

  • Giorgi F, Bi XQ (2005) Updated regional precipitation and temperature changes for the 21st century from ensembles of recent AOGCM simulations. Geophys Res Lett 32:L21715

    Article  Google Scholar 

  • Goldewijk KK (2005) Three centuries of global population growth: a spatial referenced population (density) database for 1700–2000. Popul Environ 26:343–367

    Article  Google Scholar 

  • IBGE (Brazilian Institute of Geography and Statistics) (2009) Censo agropecuário 2006. Primeiros resultados: Agricultura Familiar Brasil, grandes regiões e unidades da federação. Instituto Brasileiro de Geografia e Estatística Rep., 267pp. Available at: http://www.ibge.gov.br/home/estatistica/economia/agropecuaria/censoagro/agri_familiar_2006/familia_censoagro2006.pdf

  • Ionescu C, Klein RJT, Hinkel J, Kumar KSK, Klein R (2009) Towards a formal framework of vulnerability to climate change. Environ Model Assess 14:1–16

    Article  Google Scholar 

  • IPCC (2007) Summary for policymakers. In: Solomon S, Qin D, Mamming M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA

    Google Scholar 

  • IPEA (Institute for Applied Economic Research) (2011) O comércio internacional e a sustentabilidade socioambiental no Brasil. Available at: http://www.ipea.gov.br/portal/images/stories/PDFs/comunicado/110222_comunicadoipea79.pdf, acess in 03.05.2011

  • IPEA (Institute for Applied Economic Research), United Nations Development Programme Brazil, Joao Pinheiro Foundation (2003) Atlas do Desenvolvimento Humano no Brasil. Available at: www.pnud.org.br/atlas, access in 13.04.2011

  • Jones PW (1999) First- and second-order conservative remapping schemes for grids in spherical coordinates. Mon Wea Rev 127:2204–2210

    Article  Google Scholar 

  • Kabat P, van Schaik, Appleton B, Eds (2003) Climate changes the water rules: how water managers can cope with today’s climate variability and tomorrow’s climate change. Dialogue on Water and Climate, NL, 106p

  • Knutti R (2008) Should we believe model predictions of future climate change? Phil Trans R Soc 366:4647–4664

    Article  Google Scholar 

  • Lewis SL, Brando PM, Phillips OL, Geertje MF, van der Heijden ND (2011) The 2010 Amazon drought. Science 331:554

    Article  Google Scholar 

  • Lucena AFP, Szklo AS, Schaeffer R, Souza RR, Borba BSMC, Costa IVL, Pereira Júnior AO, Cunha SHF (2009) The vulnerability of renewable energy to climate change in Brazil. Energy Policy 37:879–889

    Article  Google Scholar 

  • Magrin G, Gay García C, Cruz Choque D, Giménez JC, Moreno AR, Nagy GJ, Nobre C, Villamizar A (2007) Latin America. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE, Eds., Cambridge University Press, Cambridge, UK, 581–615

  • Malhi Y, Roberts JT, Betts RA, Killeen TJ, Li W, Nobre CA (2008) Climate change, deforestation and the fate of the Amazon. Science 319:169–172

    Article  Google Scholar 

  • Marengo JA, Jones R, Alves L, Valverde M (2009) Future change of temperature and precipitation extremes in South America as derived from the PRECIS regional climate modeling system. Int J Climatol 29:2241–2255

    Article  Google Scholar 

  • Marengo JA, Ambrizzi T, Rocha RP, Alves LM, Cuadra SV, Valverde M, Ferraz SET, Torres RR, Santos DC (2010a) Future change of climate in South America in the late XXI century: intercomparison of scenarios from three regional climate models. Clim Dyn 35:1073–1097

    Article  Google Scholar 

  • Marengo JA, Rusticucci M, Penalba O, Renom M (2010b) An intercomparison of observed and simulated extreme rainfall and temperature events during the last half of the twentieth century. Part 2: historical trends. Clim Change 98:509–529

    Article  Google Scholar 

  • Marengo JA, Chou SC, Kay G, Alves LM, Pesquero JF, Soares WR, Santos DC, Lyra AA, Sueiro G, Betts R, Chagas DJ, Gomes JL, Bustamante JF, Tavares P (2011a) Development of regional future climate change scenarios in South America using the Eta CPTEC/HadCM3 climate change projections: climatology and regional analyses for the Amazon, São Francisco and the Parana River Basins. Clim Dyn: on line first

  • Marengo JA, Nobre CA, Chou SH, Tomasella J, Sampaio G, Alves LM, Obregón GO, Soares WR, Betts R, Kay G (2011b) Dangerous Climate Change. A Brazil-UK analysis of climate change and deforestation impacts in the Amazon. 55pp. Available at: http://mudancasclimaticas.cptec.inpe.br/~rmclima/pdfs/destaques/relatorio_ingl.pdf

  • Marengo JA, Tomasella J, Alves LM, Soares W, Rodriguez DA (2011c) The drought of 2010 in the context of historical droughts in the Amazon region. Geophys Res Lett 38:L12703

    Article  Google Scholar 

  • Marengo JA, Tomasella J, Soares W, Alves LM, Nobre C (2011d) Extreme climatic events in the Amazon basin: climatological and hydrological context of recent floods. Theor Appl Climatol 107:73–85

    Article  Google Scholar 

  • Meehl GA, Arblaster JM, Tebaldi C (2005) Understanding future patterns of increased precipitation intensity in climate model simulations. Geophys Res Lett 32:L18719

    Article  Google Scholar 

  • Meehl GA, Covey C, Delworth T, Mojib L, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394

    Article  Google Scholar 

  • Nakicenovic N, Alcamo J, Davis G, De Vries B, Fenhann J, Gaffin S, Gregory K, Grubler A, Jung TY, Kram T, La Rovere EL, Michaelis L, Mori S, Morita T, Pepper W, Pitcher H, Price L, Riahi K, Roehrl A, Rogner HH, Sankovski A, Schlesinger M, Shukla P, Smith S, Swart R, Van Rooijen S, Victor N, Dadi Z (2000) Special report on emissions scenarios. Cambridge University Press, UK

    Google Scholar 

  • Nobre CA, Borma LS (2009) ‘Tipping points’ for the Amazon forest. Curr Opin Environ Sustain 1:28–36

    Article  Google Scholar 

  • Nobre CA, Young AF, Saldiva P, Marengo JA, Nobre AD, Alves Júnior SP, Silva GCM, Lombardo M (2010) Vulnerabilidades das megacidades brasileiras às mudanças climáticas: região metropolitana de São Paulo. Availabe at: http://www.inpe.br/noticias/arquivos/pdf/megacidades.pdf, access in 04.05.2011

  • Pidgeon N, Fischhoff B (2011) The role of social and decision sciences in communicating uncertain climate risks. Nature Clim Change 1:35–41

    Article  Google Scholar 

  • Ponce VM (1995) Management of droughts and floods in the semiarid Brazilian Northeast – the case for conservation. J Soil Water Conservat 50:422–431

    Google Scholar 

  • Preston BL, Yuen EJ, Westaway RM (2011) Putting vulnerability to climate change on the map: a review of approaches, benefits, and risks. Sustain Sci 6:177–202

    Article  Google Scholar 

  • Räisänen J (2002) CO2-induced changes in interannual temperature and precipitation variability in 19 CMIP2 experiments. J Clim 15:2395–2411

    Article  Google Scholar 

  • Rusticucci M, Marengo JA, Penalba O, Renom M (2010) An intercomparison of observed and simulated extreme rainfall and temperature events during the last half of the twentieth century: Part 1: mean values and variability. Clim Change 98:493–508

    Article  Google Scholar 

  • Sahota GS (1968) An economic analysis of internal migration in Brazil. J Polit Econ 2:218–245

    Article  Google Scholar 

  • Sheffield J, Wood EF (2008) Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations. Clim Dyn 31:79–105

    Article  Google Scholar 

  • Tebaldi C, Hayhoe K, Arblaster JM, Meehl G (2006) Going to the extremes. An intercomparison of model-simulated historical and future changes in extreme events. Clim Change 79:185–211

    Article  Google Scholar 

  • Vera C, Silvestri G, Liebmann B, González P (2006) Climate change scenarios for seasonal precipitation in South America from IPCC-AR4 models. Geophys Res Lett 33:L13707

    Article  Google Scholar 

  • Xu Y, Xuejie G, Giorgi F (2009) Regional variability of climate change hot-spots in East Asia. Adv Atmos Sci 26(4):783–792

    Article  Google Scholar 

  • Yap L (1976) Internal migration and economic development in Brazil. Q J Econ 90(1):119–137

    Article  Google Scholar 

  • Yohe G, Malone E, Brenkert A, Schlesinger M, Meij H, Xing X (2006) Global distributions of vulnerability to climate change. Integ Assess J 6:35–44

    Google Scholar 

  • Yusuf AA, Francisco H (2009) Climate change vulnerability mapping for Southeast Asia. Economy and Environment Program for Southeast Asia, Singapore

    Google Scholar 

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Acknowledgments

We are thankful to M. D. Oyama and C. A. Nobre for their helpful comments on the early drafts of this manuscript. Three anonymous reviewers provided suggestions that considerably improved the quality of the manuscript. The first author was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and by Brazil’s Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Additional support was provided by FAPESP through the “Assessment of impacts and vulnerability to climate change in Brazil and strategies for adaptation options” project (Proc. # 2008/58161-1). We also thank the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP's Working Group on Coupled Modelling (WGCM) for making the CMIP3 multi-model dataset available.

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Correspondence to Roger R. Torres.

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Torres, R.R., Lapola, D.M., Marengo, J.A. et al. Socio-climatic hotspots in Brazil. Climatic Change 115, 597–609 (2012). https://doi.org/10.1007/s10584-012-0461-1

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