Adding new evidence to the attribution puzzle of the recent water shortage over São Paulo (Brazil). Issue 1 (1st January 2018)

• Record Type: Journal Article
• Authors: Pattnayak, K.C.; Gloor, E.; Tindall, J.C.; Brienen, R.J.W.; Barichivich, J.; Baker, J.C.A.; Spracklen, D.V.; Cintra, B.B.L.; Coelho, C.A.S.
• Is Part Of: Tellus. Volume 70:Issue 1(2018)
• Page Start: 1
• Page End: 14
• Publication Date: 2018-01-01
• Subjects: water shortages -- deforestation -- pattern recognition algorithm -- climate change -- sea surface temperature anomaly; Dynamic meteorology -- Periodicals; Oceanography -- Periodicals; 551.5
• DOI: 10.1080/16000870.2018.1481690
• Languages: English
• ISSNs: 0280-6495

Abstract

Abstract: São Paulo, Brazil has experienced severe water shortages and record low levels of its water reservoirs in 2013–2014. We evaluate the contributions of Amazon deforestation and climate change to low precipitation levels using a modelling approach, and address whether similar precipitation anomalies might occur more frequently in a warming world. Precipitation records from INMET show that the dry anomaly extended over a fairly large region to the north of São Paulo. Unique features of this event were anomalous sea surface temperature (SST) patterns in the Southern Atlantic, an extension of the sub tropical high into the São Paulo region and moisture flux divergence over São Paulo. The SST anomalies were very similar in 2013/14 and 2014/15, suggesting they played a major role in forcing the dry conditions. The SST anomalies consisted of three zonal bands: a cold band in the tropics, a warm band to the south of São Paulo and another cold band poleward of 40 S. We performed ensemble climate simulations with observed SSTs prescribed, vegetation cover either fixed at 1870 levels or varying over time, and greenhouse gases (GHGs) either fixed at pre-industrial levels (280 ppm CO2 ) or varying over time. These simulations exhibit similar precipitation deficits over the São Paulo region in 2013/14. From this, we infer that SST patterns and the associated large-scale state of the atmosphere were important factors in determining the precipitation anomalies, while deforestation and increased GHGs only weakly modulated the signal. Finally, analyses of future climate simulations from CMIP5 models indicate that the frequency of such precipitation anomalies is not likely to change in a warmer climate.