Atmosphere-only GCM (ACCESS1.0) simulations with prescribed land surface temperatures

Duncan Ackerley, Dietmar Dommenget

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)


General circulation models (GCMs) are valuable tools for understanding how the global ocean-atmosphere-land surface system interacts and are routinely evaluated relative to observational data sets. Conversely, observational data sets can also be used to constrain GCMs in order to identify systematic errors in their simulated climates. One such example is to prescribe sea surface temperatures (SSTs) such that 70% of the Earth's surface temperature field is observationally constrained (known as an Atmospheric Model Intercomparison Project, AMIP, simulation). Nevertheless, in such simulations, land surface temperatures are typically allowed to vary freely, and therefore any errors that develop over the land may affect the global circulation. In this study therefore, a method for prescribing the land surface temperatures within a GCM (the Australian Community Climate and Earth System Simulator, ACCESS) is presented. Simulations with this prescribed land surface temperature model produce a mean climate state that is comparable to a simulation with freely varying land temperatures; for example, the diurnal cycle of tropical convection is maintained. The model is then developed further to incorporate a selection of "proof of concept" sensitivity experiments where the land surface temperatures are changed globally and regionally. The resulting changes to the global circulation in these sensitivity experiments are found to be consistent with other idealized model experiments described in the wider scientific literature. Finally, a list of other potential applications is described at the end of the study to highlight the usefulness of such a model to the scientific community.

Original languageEnglish
Pages (from-to)2077-2098
Number of pages22
JournalGeoscientific Model Development
Issue number6
Publication statusPublished - 7 Jun 2016

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