@Article{PattnayakGTBBBSCC:2018:AdNeEv,
author = "Pattnayak, K. C. and Gloor, E. and Tindall, J. C. and Brienen, R.
J. W. and Barichivich, J. and Baker, J. C. A. and Spracklen, D. V.
and Cintra, B. B. L. and Coelho, Caio Augusto dos Santos",
affiliation = "{University of Leeds} and {University of Leeds} and {University of
Leeds} and {University of Leeds} and {University of Leeds} and
{University of Leeds} and {University of Leeds} and {University of
Leeds} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Adding new evidence to the attribution puzzle of the recent water
shortage over S{\~a}o Paulo (Brazil)",
journal = "Tellus Series A: Dynamic Meteorology and Oceanography",
year = "2018",
volume = "70",
pages = "e1481690",
month = "June",
keywords = "water shortages, deforestation, pattern recognition algorithm,
climate change, sea surface temperature anomaly.",
abstract = "Sao 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 Sao 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 Sao Paulo
region and moisture flux divergence over Sao 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 Sao 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 preindustrial levels (280 ppm CO2) or varying over
time. These simulations exhibit similar precipitation deficits
over the Sao 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.",
doi = "10.1080/16000870.2018.1481690",
url = "http://dx.doi.org/10.1080/16000870.2018.1481690",
issn = "0280-6495",
language = "en",
targetfile = "pattnayak_adding.pdf",
urlaccessdate = "27 abr. 2024"
}