Srinivasan, G., M. Hulme, C. Jones, P. Jones and T.
Osborn, 1995a: An evaluation of the spatial and interannual variability
of tropical precipitation as simulated by GCMs (Diagnostic Subproject 21).
Abstracts of the First International AMIP Scientific Conference, Monterey,
California, 71.
Precipitation is one of the most difficult variables to
simulate in a General Circulation Model and arguably one of the most important.
The Atmospheric Model Intercomparison Project (AMIP) provides an opportunity
to examine the simulation of precipitation in a wide array of models. Monthly
precipitation fields produced by a subset of 19 currently available AMIP
model experiments are evaluated for the tropical region using a land-only
observed dataset for the period 1980-88. The models show large variations
in their ability to reproduce observed tropical precipitation, although
spatial correlations indicate that some of the models simulate the pattern
of observed precipitation fields fairly well. The correlations are strongest
during boreal winter (DJF) and weakest during the boreal summer (JJA).
Individual models also exhibit a consistent dry or wet bias as compared
to the observed precipitation fields. Comparison between model and observed
precipitation time series for two Central Pacific locations show that most
models are unable to reliably reproduce interannual precipitation variability
in this region. The exceptions are the MPI, ECM and JMA models which simulate
with a reasonable degree of fidelity the observed precipitation characteristics
of this region and generally over the whole tropics-as demonstrated by
their high spatial, and relatively good anomaly, correlations.