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

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

Interannual variations in the sea surface temperature (SST) to the north of Australia are strongly linked to variations in Australian climate, including winter rainfall and tropical cyclone numbers. The north Australian SSTs are also closely linked to ENSO and tropical Pacific SSTs, with the relationship exhibiting a strong seasonal cycle. Credible predictions of Australian climate change therefore depend on climate models being able to represent ENSO and its connection to north Australian SSTs, the topic of this study.

First, the observational datasets of the Met Office Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) and the NOAA Extended Reconstructed Sea Surface Temperature (ERSST) are used to document the links between the Niño-3.4 index and a north Australian SST index, and the temporal evolution of north Australian SSTs during ENSO events. During austral autumn, the correlation between Niño-3.4 SST and north Australian SST is positive, while in austral spring it is strongly negative. During El Niño events, the north Australian SST anomalies become negative in the austral spring preceding the development of the positive Niño-3.4 SST anomalies.

The coupled models participating in the Coupled Model Intercomparison Project phase 3 (CMIP3) are evaluated in terms of this temporal evolution of Niño-3.4 SST and the relationship to north Australian SST for the twentieth-century simulations. Some of the models perform very well, while some do not capture the seasonal cycle of correlations at all. The way in which these relationships may change in the future is examined using the A2 emissions scenario in those models that do a reasonable job of capturing the present-day observed relationship, and very little change is found.

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

Abstract

Interannual variations in the sea surface temperature (SST) to the north of Australia are strongly linked to variations in Australian climate, including winter rainfall and tropical cyclone numbers. The north Australian SSTs are also closely linked to ENSO and tropical Pacific SSTs, with the relationship exhibiting a strong seasonal cycle. Credible predictions of Australian climate change therefore depend on climate models being able to represent ENSO and its connection to north Australian SSTs, the topic of this study.

First, the observational datasets of the Met Office Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) and the NOAA Extended Reconstructed Sea Surface Temperature (ERSST) are used to document the links between the Niño-3.4 index and a north Australian SST index, and the temporal evolution of north Australian SSTs during ENSO events. During austral autumn, the correlation between Niño-3.4 SST and north Australian SST is positive, while in austral spring it is strongly negative. During El Niño events, the north Australian SST anomalies become negative in the austral spring preceding the development of the positive Niño-3.4 SST anomalies.

The coupled models participating in the Coupled Model Intercomparison Project phase 3 (CMIP3) are evaluated in terms of this temporal evolution of Niño-3.4 SST and the relationship to north Australian SST for the twentieth-century simulations. Some of the models perform very well, while some do not capture the seasonal cycle of correlations at all. The way in which these relationships may change in the future is examined using the A2 emissions scenario in those models that do a reasonable job of capturing the present-day observed relationship, and very little change is found.

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