Drivers and physical processes of drought events over the State of São Paulo, Brazil

Abayomi A Abatan,Rafael C De Abreu,Conrado M Rudorff,Christopher Cunningham,Nicholas P Klingaman,Buwen Dong,Simon F B Tett

doi:10.1007/s00382-021-06091-2

Abstract

The State of São Paulo, Brazil (SSP) was impacted by severe water shortages during the intense austral summer drought of 2013/2014 and 2014/2015 (1415SD). This study seeks to understand the features and physical processes associated with these summer droughts in the context of other droughts over the region during 1961–2010. Thus, this study examines the spatio-temporal characteristics of anomalously low precipitation over SSP and the associated large-scale dynamics at seasonal timescales, using an observation-based dataset from the Climatic Research Unit (CRU) and model simulation outputs from the Met Office Hadley Centre Global Environment Model (HadGEM3-GA6 at N216 resolution). The study analyzes Historical and Natural simulations from the model to examine the role of human-induced climate forcing on droughts over SSP. Composites of large-scale fields associated with droughts are derived from ERA-20C and ERA-Interim reanalysis and the model simulations. HadGEM3-GA6 simulations capture the observed interannual variability of normalized precipitation anomalies over SSP, but with biases. Drought events over SSP are related to subsidence over the region. This is associated with reduced atmospheric moisture over the region as indicated by the analysis of the vertically integrated moisture flux convergence, which is dominated by reduced moisture flux convergence. The Historical simulations simulate the subsidence associated with droughts, but there are magnitude and location biases. The similarities between the circulation features of the severe 1415SD and other drought events over the region show that understanding of the dynamics of the past drought events over SSP could guide assessment of changes in risk of future droughts and improvements of model performance. The study highlights the merits and limitations of the HadGEM3-GA6 simulations. The model possesses the skills in simulating the large-scale atmospheric circulations modulating precipitation variability, leading to drought conditions over SSP.

Highlights

The State of São Paulo (Fig. 1; SSP) is located between 20o and 25o S and 53o and 45o W in southeastern Brazil and bordered by the states of Paraná, Mato Grosso do Sul, Minas Gerais, Rio de Janeiro, and the South Atlantic Ocean (SAO) in the tropics
This study examines the spatio-temporal characteristics of anomalously low precipitation over SSP and the associated large-scale dynamics at seasonal timescales, using an observation-based dataset from the Climatic Research Unit (CRU) and model simulation outputs from the Met Office Hadley Centre Global Environment Model (HadGEM3-GA6 at N216 resolution)
This is associated with reduced atmospheric moisture over the region as indicated by the analysis of the vertically integrated moisture flux convergence, which is dominated by reduced moisture flux convergence

Summary

Introduction

The State of São Paulo (Fig. 1; SSP) is located between 20o and 25o S and 53o and 45o W in southeastern Brazil and bordered by the states of Paraná, Mato Grosso do Sul, Minas Gerais, Rio de Janeiro, and the South Atlantic Ocean (SAO) in the tropics. SSP is home to the largest metropolitan area of Brazil, named São Paulo, located on a plateau about 800 m above sea level and about 50 km away from the SAO. As a result of its location, the city and the state experience a humid subtropical climate and both are vulnerable to the seasonal variability in winds and moisture impacting weather and climate. The seasonal variability in precipitation, leading in particular to droughts, can severely affect the water supply system, agriculture, tourism, energy, and other water resource sectors with considerable socioeconomic impacts (Pampuch et al 2016). Given the high population density of the region and its economic importance for Brazil, a better understanding of the climate variability and

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