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North Australian Sea Surface Temperatures and the El Niño–Southern Oscillation in the CMIP5 Models

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  • 1 School of Geography and Environmental Science, Monash University, Melbourne, Australia
  • | 2 School of Mathematical Science, Monash University, Melbourne, Australia
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Abstract

Aspects of the climate of Australia are linked to interannual variability of the sea surface temperatures (SSTs) to the north of the country. SST anomalies in this region have been shown to exhibit strong, seasonally varying links to ENSO and tropical Pacific SSTs.

Previously, the models participating in phase 3 of the Coupled Model Intercomparison Project (CMIP3) have been evaluated and found to vary in their abilities to represent both the seasonal cycle of correlations between the Niño-3.4 and north Australian SSTs and the evolution of SSTs during composite El Niño and La Niña events. In this study, the new suite of models participating in the CMIP5 is evaluated using the same method. In the multimodel mean, the representation of the links is slightly improved, but generally the models do not capture the strength of the negative correlations during the second half of the year. The models also still struggle to capture the SST evolution in the north Australian region during El Niño and La Niña events.

Corresponding author address: Jennifer Catto, School of Geography and Environmental Science, Monash University, Clayton Campus, Melbourne VIC 3800, Australia. E-mail: jennifer.catto@monash.edu

Abstract

Aspects of the climate of Australia are linked to interannual variability of the sea surface temperatures (SSTs) to the north of the country. SST anomalies in this region have been shown to exhibit strong, seasonally varying links to ENSO and tropical Pacific SSTs.

Previously, the models participating in phase 3 of the Coupled Model Intercomparison Project (CMIP3) have been evaluated and found to vary in their abilities to represent both the seasonal cycle of correlations between the Niño-3.4 and north Australian SSTs and the evolution of SSTs during composite El Niño and La Niña events. In this study, the new suite of models participating in the CMIP5 is evaluated using the same method. In the multimodel mean, the representation of the links is slightly improved, but generally the models do not capture the strength of the negative correlations during the second half of the year. The models also still struggle to capture the SST evolution in the north Australian region during El Niño and La Niña events.

Corresponding author address: Jennifer Catto, School of Geography and Environmental Science, Monash University, Clayton Campus, Melbourne VIC 3800, Australia. E-mail: jennifer.catto@monash.edu
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