Tropical climate variability in ACCESS-CM2 coupled climate model — Australian Meteorological and Oceanographic Society

Tropical climate variability in ACCESS-CM2 coupled climate model (#2017)

Harun A Rashid 1
  1. CSIRO Oceans and Atmosphere, CSIRO, Aspendale, VIC, Australia

Climate models are important for understanding the dynamics of the atmosphere and ocean and for predicting and projecting the future climate variability and change. Recently, version 2 of the Australian Community Climate and Earth System Simulator (ACCESS-CM2) has been developed to participate in the Climate Model Inter-comparison Project phase 6 (CMIP6). Climate simulations from ACCESS-CM2 are now being submitted to the CMIP6 archive to be analysed for the sixth Assessment Report (AR6). In this presentation, I examine the tropical interannual climate variability simulated by ACCESS-CM2. In particular, I investigate to what extent ACCESS-CM2 simulates the observed features of the important tropical variability modes, such as El Niño–Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD). I also compare the ACCESS-CM2 simulated ENSO and IOD features with those simulated by the UK Met Office HadGEM3 GC3.1 model. The latter model shares the same atmosphere model with ACCESS-CM2, but has different ocean and land surface models. It is of interest to learn to what extent a different ocean model can influence the simulated ENSO and IOD modes.   

We find that ACCESS-CM2 simulates all the major features of observed mean climate and of ENSO and IOD. However, there are systematic errors of varying degree in both the simulated mean climate and interannual variability modes. For example, the ENSO-driven sea-surface temperature (SST) variability in the equatorial eastern Pacific is almost biennial in ACCESS-CM2 simulations, in contrast to the observed 3–7-year variability. Also, the simulated zonal wind stress variability in the equatorial Pacific is notably weaker than the observed. We’ll discuss the possible causes of these and other systematic model biases.

#amos2020