Publication: Influence of decadal sea surface temperature variability on northern Brazil rainfall in CMIP5 simulations
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2018-07
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Springer
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Abstract
The Amazonia and Northeast regions of northern Brazil are characterized by very different rainfall regimes but have certain similarities in terms of their variability. The precipitation variability in both regions is strongly linked to the tropical Atlantic sea surface temperature (SST) gradient and the tropical Pacific SST anomalies, which at decadal timescales are modulated by the Atlantic Multidecadal Variability (AMV) and the Interdecadal Pacific Oscillation (IPO) modes of SST, respectively. On the other hand, it has been found that state-of-the-art models from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are able to reproduce some of the characteristics of the low-frequency SST variability modes. In this work we analyze how CMIP5 models simulate the observed response of precipitation in the Amazonia and Northeast regions to the AMV and the IPO and the atmospheric mechanisms involved. Results show that, in both CMIP5 simulations and observations, Amazonia and Northeast rainfall response to the AMV is the opposite, due to the modulation of the intertropical convergence zone (ITCZ) position. Conversely, the IPO affects equally both regions as a consequence of anomalous subsidence over the entire northern Brazil triggered by warm SST anomalies in the tropical Pacific. Such results suggest that an improvement of the predictability of decadal SST modes will directly revert into a better prediction of changes in the Amazonia and Northeast rainfall at longer timescales.
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© 2018 Springer
The authors thank the editor Dr. Corti and the helpful comments of the two anonymous reviewers. This work is the result of a 3-month stay of J.V. in the University of Sao Paulo funded by the Spanish Ministry of Economy and Competitiveness (MINECO) with support for short stays (EEBB-I-15-09241-MINECO) within the scholarship he has been granted (BES-2013-063821-MINECO). Special thanks to Iracema F. A. Cavalcanti for making the stay possible and her helpful comments on the results. The research leading to these results has received funding from the projects PREFACE (EUFP7/2007-2013 Grant Agreement 603521) and MULCLIVAR (CGL2012-38923-C02-01-MINECO). T.A. had the financial support from FAPESP (Procs. Ns. 13/50521-7 and 08/58101-9) and CNPq. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and the climate modeling groups (listed in the supplementary Table S1) for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.