Adding new evidence to the attribution puzzle of the recent water shortage over São Paulo (Brazil)

References

• Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P. and co-authors. 2003. The version 2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–Present). J. Hydrometeor. 4, 1147–1167. DOI:10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.
   Web of Science ®Google Scholar
• Barros, V. R., González, M., Liebmann, B. and Camilloni, I. 2000. Influence of the South Atlantic convergence zone and South Atlantic sea surface temperature on the interannual summer rainfall variability in southern South America. Theor. Appl. Climatol. 67, 123–183. DOI:10.1007/s007040070002.
   Web of Science ®Google Scholar
• Cabré, M. F., Solman, S. and Núñez, M. 2016. Regional climate change scenarios over southern South America for future climate (2080–2099) using the MM5 Model. Mean, interannual variability and uncertainties. ATM 29, 35–60. DOI:10.20937/ATM.2016.29.01.04.
   Web of Science ®Google Scholar
• Carvalho, L. M. V., Jones, C. and Liebmann, B. 2004. The South Atlantic convergence zone: intensity, form, persistence, and relationships with intraseasonal to interannual activity and extreme rainfall. J. Climate 17, 88–108. DOI:10.1175/1520-0442(2004)017<0088:TSACZI>2.0.CO;2.
   Web of Science ®Google Scholar
• Cavalcanti, I. F. A., Marengo, J. A., Alves, L. M. and Costa, D. F. 2017. On the opposite relation between extreme precipitation over west Amazon and southeastern Brazil: Observations and model simulations. Int. J. Climatol. 37, 3606–3618. DOI:10.1002/joc.4942.
   Web of Science ®Google Scholar
• Chou, S. C., Marengo, J. A., Lyra, A. A., Sueiro, G., Pesquero, J. F. and co-authors. 2012. Downscaling of South America present climate driven by 4-member HadCM3 runs. Clim. Dyn. 38, 635. DOI:10.1007/s00382-011-1002-8.
   Web of Science ®Google Scholar
• Coelho, C. A. S., Cardoso, D. H. F. and Firpo, M. A. F. 2016a. Precipitation diagnostics of an exceptionally dry event in São Paulo, Brazil. Theor. Appl. Climatol. 125, 769–784. DOI:10.1007/s00704-015-1540-9.
   Web of Science ®Google Scholar
• Coelho, C. A. S., de Oliveira, C. P., Ambrizzi, T., Reboita, M. S., Carpenedo, C. B. and co-authors. 2016b. The 2014 southeast Brazil austral summer drought: regional scale mechanisms and teleconnections. Clim. Dyn. 46, 3737–3752. DOI:10.1007/s00382-015-2800-1.
   Web of Science ®Google Scholar
• Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P. and co-authors. 2011. Development and evaluation of an earth system model HadGEM2. Geosci. Model Dev. 4, 1051–1062. DOI:10.5194/gmd-4-1051-2011.
   Web of Science ®Google Scholar
• Coutinho, R. M., Kraenkel, R. A. and Prado, P. I. 2015. Catastrophic regime shift in water reservoirs and São Paulo water supply crisis. PLoS ONE 10, e0138278. DOI:10.1371/journal.pone.0138278.
   Web of Science ®Google Scholar
• Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P. and co-authors. 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quar. J. Royal. Meteorol. Soc. 137, 553–597. DOI:10.1002/qj.828.
   Web of Science ®Google Scholar
• Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W. and co-authors. 2012. GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: physical formulation and baseline simulation characteristics. J. Climate 25, 6646–6665. DOI:10.1175/JCLI-D-11-00560.1.
   Web of Science ®Google Scholar
• Dunne, J. P., John, J. G., Shevliakova, E., Stouffer, R. J., Krasting, J. P. and co-authors. 2013. GFDL’s ESM2 global coupled climate–carbon earth system models. Part II: carbon system formulation and baseline simulation characteristics. J. Climate 26, 2247–2267. DOI:10.1175/JCLI-D-12-00150.1.
   Web of Science ®Google Scholar
• Escobar, H. 2015. Drought triggers alarms in Brazil’s biggest metropolis. Science 347, 812. DOI:10.1126/science.347.6224.812.
   PubMed Web of Science ®Google Scholar
• Espinoza, J. C., Marengo, J. A., Ronchail, J., Carpio, J. M., Flores, L. N. and co-authors. 2014. The extreme 2014 flood in south-western Amazon basin: the role of tropical–subtropical South Atlantic SST gradient. Environ. Res. Lett. 9, 124007. DOI:10.1088/1748-9326/9/12/124007.
   Web of Science ®Google Scholar
• Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C. and co-authors. 2011. The community climate system model version 4. J. Climate 24, 4973–4991. DOI:10.1175/2011JCLI4083.1.
   Web of Science ®Google Scholar
• Getirana, A. 2016. Extreme water deficit in Brazil detected from space. J. Hydrometeor. 17, 591–599. DOI:10.1175/JHM-D-15-0096.1.
   Web of Science ®Google Scholar
• Herdies, D. L., DaSilva, A., Silva Dias, M. A. F. and Ferreira, R. N. 2002. The moisture budget of the bimodal pattern of the summer circulation over South America. J. Geophys. Res. 107, 8075.
   Web of Science ®Google Scholar
• Junquas, C., Vera, C., Li, L. and Le Treut, H. 2012. Summer precipitation variability over southeastern South America in a global warming scenario. Clim. Dyn. 38, 1867–1883. DOI:10.1007/s00382-011-1141-y.
   Web of Science ®Google Scholar
• Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D. and co-authors. 1996. The NMC/NCAR 40-year reanalysis project. Bull. Am. Meteor. Soc. 77, 437–471. DOI:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.
   Web of Science ®Google Scholar
• King, D., Schrag, D., Zhou, D., Ye, Q. and Ghosh, A. 2015. Climate change: a risk assessment—risk assessment part 3: systemic risks. In: Centre for Social Science and Policy (eds. J. Hynard and T. Rodger), London, pp. 110–111.
   Google Scholar
• Kodama, Y. M. 1993. Large-scale common features of sub-tropical precipitation zones (the Baiu Frontal Zone, the SPCZ, and the SACZ). Part I: characteristics of subtropical frontal zones. J. Meteorol. Soc. Jpn. 71, 581–835. DOI:10.2151/jmsj1965.71.5_581.
   Web of Science ®Google Scholar
• Kolusu, S. R., Marsham, J. H., Mulcahy, J., Johnson, B., Dunning, C., and co-authors. 2015. Impacts of Amazonia biomass burning aerosols assessed from short-range weather forecasts. Atmos. Chem. Phys. 15, 12251–12266. DOI:10.5194/acp-15-12251-2015.
   Web of Science ®Google Scholar
• Liebmann, B. and Smith, C. A. 1996. Description of a complete (Interpolated) outgoing longwave radiation dataset. Bull. Am. Meteorol. Soc. 77, 1275–1277.
   Web of Science ®Google Scholar
• Marengo, J. A. and Alves, L. M. 2015. Crise hídrica em São Paulo em 2014: seca e desmatamento [Water crisis in São Paulo in 2014: drought and deforestation]. GEOUSP, USP- São Paulo.
   Google Scholar
• Meiyappan, P. and Jain, A. K. 2012. Three distinct global estimates of historical land-cover change and land-use conversions for over 200 years. Front. Earth Sci. 6, 122–139. DOI:10.1007/s11707-012-0314-2.
   Web of Science ®Google Scholar
• Munich, R. 2015. Natural catastrophes 2014. analyses, assessments, positions. TOPICS-GEO 2014, Munich, 67 p.
   Google Scholar
• Nazareno, A. G. and Laurance, W. F. 2015. Brazil’s drought: beware deforestation. Science 347, 1427. DOI:10.1126/science.347.6229.1427-a.
   Web of Science ®Google Scholar
• Nobre, C. A., Marengo, J. A., Seluchi, M. E., Cuartas, L. A. and Alves, L. M. 2016. Some characteristics and impacts of the drought and water crisis in Southeastern Brazil during 2014 and 2015. J. Water Res. Protect. 8, 2.
   Google Scholar
• Otto, F. E. L., Coelho, C. A. S., King, A., De Perez, E. C., Wada, Y. and co-authors. 2015. Factors other than climate change, main drivers of 2014/15 water shortage in Southeast Brazil [in “Explaining extremes of 2014 from a climate perspective”]. Bull. Am. Meteor. Soc. 96, S35–S40. DOI:10.1175/BAMS-D-15-00120.1.
   Web of Science ®Google Scholar
• Peterson, T. C. and Vose, R. S. 1997. An overview of the global Historical Climatology Network temperature database. Bull. Am. Meteor. Soc. 78, 2837–2849.
   Web of Science ®Google Scholar
• Pope, V., GallanI, M., Rowntree, P. and Stratton, R. 2000. The impact of new physical parametrizations in the Hadley Centre climate model: HadAM3. Clim. Dyn. 16, 123–146. DOI:10.1007/s003820050009.
   Web of Science ®Google Scholar
• Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., and co-authors. 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407.
   Web of Science ®Google Scholar
• Reboita, M. S., da Rocha, R. P., Dias, C. G. and Ynoue, R. Y. 2014. Climate projections for South America: RegCM3 driven by HadCM3 and ECHAM5. Adv. Meteorol. 2014, 1. DOI:10.1155/2014/376738.
   Web of Science ®Google Scholar
• SABESP – COMPANHIA DE SANEAMENTO BÁSICO DO ESTADO DE SÃO PAULO. 2008. Dossiê – Sistema Guarapiranga. São Paulo: Sabesp, setembro de. 16 p. Online at: http://memoriasabesp.sabesp.com.br/acervos/dossies/pdf/9_sistema_guarapiranga.pdf
   Google Scholar
• Santer, B. D., Taylor, K. E., Wigley, T. M. L., Penner, J. E., Jones, P. D. and Cubasch, U. 1995. Towards the detection and attribution of an anthropogenic effect on climate. Clim. Dyn. 12, 77–100. DOI:10.1007/BF00223722.
   Web of Science ®Google Scholar
• Seth, A., Fernandes, K. and Camargo, S. J. 2015. Two summers of São Paulo drought: origins in the western tropical Pacific. Geophys. Res. Lett. 42, 816–823.
   Web of Science ®Google Scholar
• Shepherd, J. M., Pierce, H. and Negri, A. J. 2002. Rainfall modification by major urban areas: Observations from spaceborne rain radar on the TRMM satellite. J. Appl. Meteorol. 41, 689–701. DOI:10.1175/1520-0450(2002)041<0689:RMBMUA>2.0.CO;2.
   Google Scholar
• Silva, W. L., Nascimento, M. A. and Menezes, W. F. 2015. Atmospheric blocking in the South Atlantic during the summer 2014: a synoptic analysis of the phenomenon. ACS. 5, 386–393. DOI:10.4236/acs.2015.54030.
   Google Scholar
• Swiss-Re. 2015. Natural catástrofes and man-made disasters in 2014: convective and winter storms generate most losses. Swiss Re Ltd-Economic Research and Consulting, Zurich, Swiss Re-Sigma No. 2/2015, 52 p.
   Google Scholar
• Taylor, K. E., Stouffer, R. J. and Meehl, G. A. 2012. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498. DOI:10.1175/BAMS-D-11-00094.1.
   Web of Science ®Google Scholar
• UNICA 2015. Centre for Food Storage and Market Distribution of the State of São Paulo (CEAGESP), the Brazilian Citrus Association, the Cereal Stock Market of São Paulo and the Brazilian Union of Sugar Cane Producers. Online at: http://www.unica.com.br/
   Google Scholar
• United Nations, Department of Economic and Social Affairs, Population Division. 2015. World Urbanization Prospects: The 2014 Revision, (ST/ESA/SER.A/366).
   Google Scholar
• Zhang, H., Delworth, T., Zeng, F., Vecchi, G., Paffendorf, K. and Jia, L. 2016. Detection, attribution, and projection of regional rainfall changes on (multi-) decadal time scales: a focus on southeastern South America. J. Climate 29, 8515–8534. DOI:10.1175/JCLI-D-16-0287.1.
   Web of Science ®Google Scholar