Phillips, Thomas J. , Ann Henderson-Sellers, Parviz Irannejad, Kendal McGuffie, Huqiang Zhang, and the AMIP I Modeling Groups
The Atmospheric Model Intercomparison Project (AMIP), an initiative of the World Climate Research Programme since 1990, is a standard experimental protocol for testing the performance of global atmospheric models. One of the many studies facilitated by the AMIP is the evaluation of model simulation of processes at the land surface, a key locus of human interaction with the climate system. In particular, the relationship between different continental climate simulations and the properties of the respective coupled land-surface schemes (LSSs) may be investigated. Studies of this type have been coordinated by the Project for Intercomparison of Land-surface Parameterization Schemes (PILPS), organized as AMIP Diagnostic Subproject 12.
After recounting the history of the AMIP/PILPS collaboration to date, we describe a method for concisely displaying the spatio-temporal variability of a land-surface simulation relative to that of validation reference data. We apply this method to the continental simulation of 30 model entries in the first phase of the AMIP intercomparison.
We find that the overall agreement of simulated continental climate variability with that of selected reanalysis reference data is a function of the land-surface process considered. Of the monthly mean land-surface variables available from these AMIP simulations, the spatio-temporal variability of continental evaporation shows the greatest sensitivity to the LSS representation of hydrology. Moreover, in twin AMIP simulations where this representation is changed from a simple "bucket" scheme to a biophysically based formulation (while retaining the same atmospheric model and land-surface characteristics), there is a general reduction in the RMS errors of the continental climate simulation relative to the reference data. However, these LSS-related improvements are due almost exclusively to changes in the amplitude of the continental climate variability, suggesting that it is the atmospheric forcings and/or the land-surface characteristics that largely control the pattern of this variability. We plan to investigate such issues more fully in the second phase of the AMIP. (pdf file)