Abstract
The objective of this work is to assess changes in three metropolitan regions of Southeast Brazil (Rio de Janeiro, São Paulo, and Santos) based on the projections produced by the Eta Regional Climate Model (RCM) at very high spatial resolution, 5 km. The region, which is densely populated and extremely active economically, is frequently affected by intense rainfall events that trigger floods and landslides during the austral summer. The analyses are carried out for the period between 1961 and 2100. The 5-km simulations are results from a second downscaling nesting in the HadGEM2-ES RCP4.5 and RCP8.5 simulations. Prior to the assessment of the projections, the higher resolution simulations were evaluated for the historical period (1961–1990). The comparison between the 5-km and the coarser driver model simulations shows that the spatial patterns of precipitation and temperature of the 5-km Eta simulations are in good agreement with the observations. The simulated frequency distribution of the precipitation and temperature extremes from the 5-km Eta RCM is consistent with the observed structure and extreme values. Projections of future climate change using the 5-km Eta runs show stronger warming in the region, primarily during the summer season, while precipitation is strongly reduced. Projected temperature extremes show widespread heating with maximum temperatures increasing by approximately 9 °C in the three metropolitan regions by the end of the century in the RCP8.5 scenario. A trend of drier climate is also projected using indices based on daily precipitation, which reaches annual rainfall reductions of more than 50 % in the state of Rio de Janeiro and between 40 and 45 % in São Paulo and Santos. The magnitude of these changes has negative implications to the population health conditions, energy security, and economy.
Similar content being viewed by others
Change history
03 April 2017
An erratum to this article has been published.
References
Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109. doi:10.1029/2005JD006290
Barbosa JPM (2008) Avaliação de técnicas empíricas e estatísticas de identificação de extremos de precipitação para o litoral paulista e entorno. MSc dissertation. Universidade Estadual de Campinas: Campinas, SP, Brazil
Betts AK, Miller MJ (1986) A new convective adjustment scheme. Part II: single column tests using GATE wave, BOMEX, ATEX and arctic air-mass data sets. Q J R Meteorol Soc 112:693–709. doi:10.1002/qj.49711247308
Black TL (1994) NMC notes: the new NMC mesoscale Eta model: description and forecast samples. Weather Forecast 9:265–278
Bucchignani E, Montesarchio M, Zollo AL, Mercogliano P (2015) High-resolution climate simulations with COSMO-CLM over Italy: performance evaluation and climate projections for the 21st century. Int J Climatol 36:735–756. doi:10.1002/joc.4379
CEPED/UFSC (2013) Atlas brasileiro de desastres naturais 1991 a 2012. Universidade Federal de Santa Catarina. Centro Universitário de Estudos e Pesquisas sobre desastres, Florianópolis
CEPERJ (2010) Fundação Centro Estadual de Estatísticas, Pesquisas e Formação de Servidores Públicos do Rio de Janeiro, Centro de Estatísticas, Estudos e Pesquisas (CEEP). Rio de Janeiro. http://www.ceperj.rj.gov.br/ceep/Anuario2013/index.html. Accessed 04 Jan 2016
Chou SC, Marengo JA, Lyra AA, Sueiro G, Pesquero JF, Alves LM, Kay G, Betts R, Chagas DJ, Gomes JL, Bustamante JF (2012) Downscaling of South America present climate driven by 4-member HadCM3 runs. Clim Dyn 38:635–653. doi:10.1007/s00382-011-1002-8
Chou SC, Lyra AA, da Silva AJ, Sueiro G, Tavares P, Nunes, LH, Marengo, JA (2014a) 5-km resolution Eta model downscaling of present climate in the city of Santos, Brazil. In: Water management in transition countries as impacted by climate change and other global changes, lessons from paleoclimate, and regional Issues. 1 ed. Belgrado: Editors: Institute for the Development of Water Resources and Serbian Academy of Sciences, 2014, v. 1, p. 80–85. ISBN 978-86-82565-42-0
Chou SC, Lyra A, Mourão C, Dereczynski C, Pilotto I, Gomes J, Bustamante J, Tavares P, Silva A, Rodrigues D, Campos D, Chagas D, Sueiro G, Siqueira G, Nobre P, Marengo J (2014c) Evaluation of the eta simulations nested in three global climate models. Am J Clim Chang 3:438–454. doi:10.4236/ajcc.2014.35039
Chou SC, Lyra A, Mourão C, Dereczynski C, Pilotto I, Gomes J, Bustamante J, Tavares P, Silva A, Rodrigues D, Campos D, Chagas D, Sueiro G, Siqueira G, Marengo J (2014b) Assessment of climate change over South America under RCP 4.5 and 8.5 downscaling scenarios. Am J Clim Chang 3:512–527. doi:10.4236/ajcc.2014.35043
Coelho Netto AL, Sato AM, Avelar AS, Vianna GG, Araujo IS, Ferreira DLC, Lima PH, Silva APA, Silva RP (2011) January 2011: the extreme landslide disaster in Brazil. The Second World Landslide Forum, October 2011, Rome
Collins WJ, Belloin N, Doutriaux-Boucher M et al (2011) Development and evaluation of an earth-system model—HadGEM2. Geosci Model Dev 4:1051–1075. doi:10.5194/gmd-4-1051-2011
Dereczynski C, Silva WL, Marengo J (2013) Detection and projections of climate change in Rio de Janeiro, Brazil. Am J Clim Chang 2:25–33. doi:10.4236/ajcc.2013.21003
Dorman JL, Sellers PJ (1989) A global climatology of albedo, roughness length and stomatal resistance for atmospheric general circulation models as represented by the simple biosphere model (SiB). Jounal of Applied Meteorology 28:833–855
Ek MB, Mitchell KE, Lin Y, Rogers E, Grummen P, Koren V, Gayno G, Tarpley JD (2003) Implementation of NOAH land surface advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res 108:D22–D8851. doi:10.1029/2002JD003246
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978. doi:10.1002/joc.1276
IBGE (2010) Instituto Brasileiro de Geografia e Estatística – Rio de Janeiro. Contagem da População. http://www.ibge.gov.br/home/estatistica/populacao/censo2010/. Accessed 04 Jan 2016
IPCC (2013) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds). Cambridge University Press, Cambridge
Janjic ZI (1979) Forward-backward scheme modified to prevent two-grid-interval noise and its application in sigma coordinate models. Contrib Atmos Phys 52:69–84
Janjic ZI (1984) Nonlinear advection schemes and energy cascade on semi-staggered grids. Mon Weather Rev 112:1234–1245
Janjic ZI, Gerrity JP Jr, Nickovic S (2001) An alternative approach to nonhydrostatic modeling. Mon Wea Rev 129:1164–1178
Kendon E, Roberts N, Senior C, Roberts M (2012) Realism of rainfall in a very high-resolution regional climate model. J Clim 25:5791–5806. doi:10.1175/JCLI-D-11-00562.1
Kodama Y (1992) Large-scale common features of subtropical precipitation zones (the Baiu frontal zones, the SPCZ, and the SACZ) part I: characteristics of subtropical frontal zones. Journal of Meteorological Society of Japan 70(4):813–835
Kusaka H, Takata T, Takane Y (2010) Reproducibility of regional climate in central Japan using the 4-km resolution WRF model. SOLA 6:113–116. doi:10.2151/sola.2010-029
Lacis AA, Hansen JE (1974) A parameterization of the absorption of solar radiation in the earth’s atmosphere. J Atmos Sci 31:118–133
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 (2012) 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 Paraná River basins. Clim Dyn 38:1829–1848
Marengo JA, Valverde MC, Obregón GO (2013) Observed and projected changes in rainfall extremes in the metropolitan area of São Paulo. Clim Res 57:61–72
Marengo JA, Muller-Karger FE, Pelling M, Reynolds CJ, Merril SB et al (2016) An integrated framework to analyze local decision making and adaptation to sea-level rise in coastal regions in Santos-Brazil, Broward County-USA and Selsey-UK. AGU Fall Conference 2016, San Francisco
Martin GM, Bellouin N, Collins WJ, Culverwell ID, Halloran PR, Hardiman SC et al (2011) The had-GEM2 family of Met Office unified model climate configurations. Geosci Model Dev 4:723–757. doi:10.5194/gmd-4-723-2011
Mesinger F, Chou SC, Gomes JL, Jovic D, Lyra AA, Bustamante JF, Bastos PR, Lazic L, Morelli S, Ristic I (2012) An upgraded version of the Eta model. Meteorog Atmos Phys 116:63–79. doi:10.1007/s00703-012-0182-z
Mesinger FA (1984) Blocking technique for representation of mountains in atmospheric models. Riv Meteor Aeronáutica 44:195–202
Mesinger F, Janjic ZI, Nickovic S, Gavrilov D, Deaven DG (1988) The step-mountain coordinate: model description and performance for cases of Alpine lee cyclogenesis and for a case of an Appalachian redevelopment. Mon Weather Rev 116:1493–1518
Mourão CEF (2010) Testes com o esquema Kain Fritsch de parametrização de convecção. MSc dissertation. Instituto Nacional de Pesquisas Espaciais: São José dos Campos, Brazil
Nakicenovic N, Alcamo J, Davis G, de Vries B, Fenhann J, Gaffin S et al (2000) Special report on emissions scenarios: A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, 570 pp
Nobre CA, Young AF, Saldiva P, Marengo, JA, Nobre AD, Ales Jr S, da Silva GCM, Lombardo M (2010) Vulnerabilidade das Megacidades Brasileiras ás Mudanças Climáticas: Região Metropolitana de São Paulo. INPE/UNICAMP/USP/IPT/UNESP. Junho 2010, 31 pp
Obregón G, Marengo J, Nobre CA (2014) Rainfall and climate variability: long-term trends in the metropolitan area of São Paulo in the 20th century. Clim Res 61:93–107. doi:10.3354/cr01241
Paulson CA (1970) The mathematical representation of wind speed and temperature profiles in the unstable atmospheric surface layer. J Appl Meteor 9:857–861
Pesquero JF, Chou SC, Nobre CA, Marengo JA (2009) Climate downscaling over South America for 1961-1970 using the Eta Model. Theor Appl Climatol 99:75–93. doi:10.1007/s00704-009-0123-z
Rockel B, Will A, Hense A (2008) The regional climate model COSMO-CLM (CCLM). Meteorol Z 17:347–348. doi:10.1127/0941-2948/2008/0309
Sasaki H, Kurihara K, Takayabu I, Uchiyama T (2008) Preliminary experiments of reproducing the present climate using the non-hydrostatic regional climate model. SOLA 4:25–28
Schwarzkopf MD, Fels SB (1991) The simplified exchange method revisited: an accurate, rapid method for computation of infrared cooling rates and fluxes. J Geophys Res 96:9075–9096
Silva Dias MAF, Silva Dias J, Carvalho LMV, Freitas ED, Silva Dias PL (2013) Changes in extreme daily rainfall for São Paulo, Brazil. Clim Chang 116:705–722
Silva WL, Dereczynski CP (2014) Caracterização Climatológica e Tendências Observadas em Extremos Climáticos no Estado do Rio de Janeiro. Anu Inst Geocienc 37:123–138 http://www.anuario.igeo.ufrj.br/2014_2/2014_2_123_138.pdf
Silva W, Dereczynski C, Chou SC, Cavalcanti I (2014) Future changes in temperature and precipitation extremes in the state of Rio de Janeiro (Brazil). Am J Clim Chang 3:353–365. doi:10.4236/ajcc.2014.34031
Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG et al. (2008) A description of the advanced research WRF version 3. NCAR/TN-475 + STR, 113 pp
Torres RR, Marengo JA, Valverde MC (2009) Projeções de Extremos Climáticos nas Regiões Metropolitanas de São Paulo e Rio de Janeiro para o Final do Século XXI. In III Simpósio Internacional de Climatologia. Canela, Brasil
UN (2014) World urbanization prospects: the 2014 revision. United Nations, New York. http://esa.un.org/unpd/wup/Publications/Files/WUP2014-PressRelease.pdf. Accessed 04 Jan 2016
Van Vuuren DP, Edmonds J, Kainuma M et al (2011) The representative concentration pathways: an overview. Clim Chang 109:5–31. doi:10.1007/s10584-011-0148-z
Vieira RMSP, Alvalá RCS, Ponzoni FJ, Ferraz Neto S, Canavesi V (2010) Mapa de uso e cobertura da terra do Estado de São Paulo. INPE: São José dos Campos. (INPE ePrint sid.inpe.br/mtc-m19@80/2010/01.22.12.32)
Xavier TMBS, Xavier A, Silva Dias MAF (1994) Evolução da precipitação diária num ambiente urbano: o caso da cidade de São Paulo. Revista Brasileira de Meteorologia 9(1):44–53
Zhao Q, Carr FH (1997) A prognostic cloud scheme for operational NWP models. Mon Wea Rev 125:1931–1953. doi:10.1175/1520-0493(1997)125<1931:APCSFO>2.0.CO;2
Zobler L (1986) A world soil file for global climate modeling. NASA Tech. Memo. 87802, NASA, 33 pp
Acknowledgements
This work was partially funded by MCTI/UNDP [BRA/10/G32], FAPESP [2014/00192-0], Belmont Forum 2012/51876-0], and CNPq [457874/2014-7, Universal 400792/2012-5, and scholarships 168933/2014-4 and 308035/2013-5].
Author information
Authors and Affiliations
Corresponding author
Additional information
An erratum to this article is available at https://doi.org/10.1007/s00704-017-2110-0.
Rights and permissions
About this article
Cite this article
Lyra, A., Tavares, P., Chou, S.C. et al. Climate change projections over three metropolitan regions in Southeast Brazil using the non-hydrostatic Eta regional climate model at 5-km resolution. Theor Appl Climatol 132, 663–682 (2018). https://doi.org/10.1007/s00704-017-2067-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00704-017-2067-z