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Consecutive dry and wet days over South America and their association with ENSO events, in CMIP5 simulations

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Abstract

The assessment of ENSO influence on extreme rainfall events over South America will provide useful information to climate services. This research analyzes the performance of eleven global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) using skill score metrics to simulate two climate extreme rainfall indices: maximum number of consecutive dry days (CDD) and wet days (CWD). Additionally, another objective of this study is to characterize the spatial relationship between different types of El Niño–Southern Oscillation (ENSO)–El Niño Modoki Index (EMI) and Oceanic Niño Index (ONI)– and those indices of climate extremes of rainfall. The development of this research is carried out in South America, in the trimester October–December from “historical” experiment for the period 1979–2005. In general terms, the mean fields of CDD and CWD indices tend to be opposite, with main differences in Amazonas, Atacama Desert, and northeast of Brazil. The CDD–EMI and CDD–ONI correlations show a greater signal than CWD in South America. The CDD–EMI correlation is negative; nevertheless, the CDD-El Niño Modoki composite shows positive values in the northeast of Buenos Aires province. It can be concluded that most models are able to reproduce the gridded observed spatial pattern of extreme rainfall indices and their association with ENSO events. The results of this investigation could be a tool for new studies to analyze and compare the “historical” period with future projections in a context of climate change.

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Funding

This work has been supported by the projects UBA-20020170100357BA from the University of Buenos Aires and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) PIP 0137.

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Correspondence to M. Florencia Iacovone.

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Iacovone, M.F., Pántano, V.C. & Penalba, O.C. Consecutive dry and wet days over South America and their association with ENSO events, in CMIP5 simulations. Theor Appl Climatol 142, 791–804 (2020). https://doi.org/10.1007/s00704-020-03324-y

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