Association between El Niño and extreme temperatures in southern South America in CMIP5 models. Part 1: model evaluation in the present climate

Abstract

Climate variability might temporarily improve or mitigate the effects of increasing global warming. Understanding and estimating internal variability is just as important as understanding the role of anthropogenic forcing, as the combination of both drives climate events in the real world. The objective of this work is to analyze the relationship between the SST of the equatorial Pacific and 4 extreme temperature indices in southern South America considering gridded observational data (HadEX3), reanalyses (ERA-Interim, NCEP1, NCEP2), and global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) in the historical period 1979-2005. For this, correlations and quantile regression for the 90th percentile were estimated between the variables. Moreover, to assess the performance of the reanalysis and CMIP5 models, multiple metrics were calculated. The observations showed that warm conditions in the equatorial Pacific are mainly associated with a higher occurrence of warm nights in the north and center of Argentina and Chile in winter and spring. However, the different reanalyses considered in this study showed discrepancies in representing these relationships. Several CMIP5 models were generally able to simulate correlation patterns for the warm extremes of the minimum and maximum temperature in comparison to HadEX3. These types of studies are critical to understanding whether climate models simulate temperature extremes in association with physical processes, providing greater confidence in their future projections.

Association between El Niño and extreme temperatures in southern South America in CMIP5 models. Part 2: future climate projections

“…To represent the ENSO teleconnection in the past and the future, we employed sealevel pressure (SLP) anomalies in the southern hemisphere for the same GCMs in Collazo et al (2021)(Table S1). The anomalies were estimated for the climatological period 1981-2010.…”

“…These extremes were simulated by CMIP5 models in both near and far future periods. These indices are based on a percentile threshold, i.e., they describe the exceedance rates above or below a threshold defined as the 10th or 90th percentile derived from the We regridded the extreme temperature indices from all GCMs to a common grid of 2.5°x2.5° in southern South America to compare the different models, as Collazo et al (2021). We applied a first-order conservative remapping procedure (Jones 1999),…”

“…In order to study the link between the ENSO and extreme temperature events in southern South America in the near and far future, we calculated the Spearman correlation (Spearman 1904) and the quantile regression for the 90th percentile (Koenker 2005) between SST3.4 and extreme temperature indices for the four seasons, as Collazo et al (2021). The statistical significance of the correlations and regressions was evaluated at a 5% significant level.…”

“…On the other hand, quantile regression explores different aspects of the relationship between adependent variable and independent variables, for example, the impact of one variable on the tails of the distribution of another by considering the lowest or the highest percentiles. More details can be found in Collazo et al (2021).…”

“…ENSO can affect the intensity and occurrence of extreme events such as heatwaves, droughts, and floods (King et al 2016). In the first part of this work (Collazo et al 2021), we analyzed ENSO association with four extreme temperature climate indices in southern South America. We showed that warm SST in the El Niño3.4 region is associated with a higher occurrence of warm extremes of minimum temperature in northern and central Argentina and Chile, southern Brazil, and Uruguay during the winter and spring.…”