Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 7, 545-567, 2014
https://doi.org/10.5194/gmd-7-545-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper
04 Apr 2014
Representation of climate extreme indices in the ACCESS1.3b coupled atmosphere–land surface model
R. Lorenz1, A. J. Pitman1, M. G. Donat1, A. L. Hirsch1, J. Kala1, E. A. Kowalczyk2, R. M. Law2, and J. Srbinovsky2 1ARC Centre of Excellence for Climate System Science and Climate Change Research Centre, University of New South Wales, Australia
2Centre for Australian Weather and Climate Research, CSIRO Marine and Atmospheric Research, Australia
Abstract. Climate extremes, such as heat waves and heavy precipitation events, have large impacts on ecosystems and societies. Climate models provide useful tools for studying underlying processes and amplifying effects associated with extremes. The Australian Community Climate and Earth System Simulator (ACCESS) has recently been coupled to the Community Atmosphere Biosphere Land Exchange (CABLE) model. We examine how this model represents climate extremes derived by the Expert Team on Climate Change Detection and Indices (ETCCDI) and compare them to observational data sets using the AMIP framework. We find that the patterns of extreme indices are generally well represented. Indices based on percentiles are particularly well represented and capture the trends over the last 60 years shown by the observations remarkably well. The diurnal temperature range is underestimated, minimum temperatures (TMIN) during nights are generally too warm and daily maximum temperatures (TMAX) too low in the model. The number of consecutive wet days is overestimated, while consecutive dry days are underestimated. The maximum consecutive 1-day precipitation amount is underestimated on the global scale. Biases in TMIN correlate well with biases in incoming longwave radiation, suggesting a relationship with biases in cloud cover. Biases in TMAX depend on biases in net shortwave radiation as well as evapotranspiration. The regions and season where the bias in evapotranspiration plays a role for the TMAX bias correspond to regions and seasons where soil moisture availability is limited. Our analysis provides the foundation for future experiments that will examine how land-surface processes contribute to these systematic biases in the ACCESS modelling system.

Citation: Lorenz, R., Pitman, A. J., Donat, M. G., Hirsch, A. L., Kala, J., Kowalczyk, E. A., Law, R. M., and Srbinovsky, J.: Representation of climate extreme indices in the ACCESS1.3b coupled atmosphere–land surface model, Geosci. Model Dev., 7, 545-567, https://doi.org/10.5194/gmd-7-545-2014, 2014.
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