Publicación:
Influence of the Coupling South Atlantic Convergence Zone-El Nino-Southern Oscillation (SACZ-ENSO) on the Projected Precipitation Changes over the Central Andes

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Fecha
2021
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Espinoza, Jhan-Carlo
Junquas, Clementine
Saavedra, Miguel
Silva, Yamina
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MDPI
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Abstracto
There are no studies related to the influence of the coupling between the South Atlantic Convergence Zone (SACZ) and El Nino-Southern Oscillation (ENSO) pattern variability on future changes in the austral summer (December-February, DJF) precipitation over the central Andes. Therefore, we evaluated the historical simulations (1980-2005) and projections (2070-2099) for the Representative Concentration Pathway 8.5 (RCP 8.5) scenario of 25 global climate models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5). Moreover, we also consider the Regional Climate Model version 4 (RegCM4) projections nested in three CMIP5 GCMs (GFDL-ESM2M, MPI-ESM-MR, and HadGEM2-ES) under RCP 8.5. We separate the CMIP5 GCMs according to their abilities to simulate the nonlinear characteristics of ENSO and the SACZ for the historical period. We found that only three out of 25 CMIP5 GCMs (hereafter group A) simulate the nonlinear characteristics of ENSO and the SACZ during the historical period. Although most CMIP5 GCM project DJF precipitation decreases over the central Andes, group A project precipitation increases related to the projected increase in deep convection over the central Peruvian Amazon. On the regional scale, only RegGFDL (nested in a group A CMIP5 GCM) projects a statistically significant increase in DJF precipitation (similar to 5-15%) over the northern central Andes and the central Peruvian Amazon. Conversely, all RegCM4 simulations project a decrease in DJF precipitation (similar to-10%) over the southern central Andes.
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Juan Sulca was funded by Peruvian PPR068 program Reduccion de vulnerabilidad y atencion de emergencias por desastres. The work was performed using computational resources, HPC-Linux-Cluster, from Laboratorio de Dinamica de Fluidos Geofisicos Computacionales at Instituto Geofisico del Peru (grants 101-2014-FONDECYT). R. P. da Rocha thanks to CNPq-Brazil (#304949/2018-3 and 430314/2018-3). Moreover, the authors thank Enciso for his help with the production of some figures. We are very grateful to three anonymous reviewers who provided us with valuable comments, which helped us to advance our results significantly and to improve the paper.
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climate change
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