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Global Precipitation Diagnostic Studies PA

PI: Phillip Arkin
Institution: University of Maryland
Abstract:
I plan to examine the AR4 20th Century simulations and compare them to several global and near-global observed precipitation data sets. The observed data sets will include the Global Precipitation Climatology Project (GPCP), the Climate Prediction Center Merged Analysis of Precipitation (CMAP), a new global analysis with a more complete error budget being developed here at the University of Maryland, and several near-global higher resolution precipitation products including CMORPH, PERSIANN, TRMM 3B42 and GSMAP.

The objectives of the study will be to evaluate the fidelity of simulated precipitation changes over the past 25 years and to learn more about the errors in the observed global data sets. We hypothesize that, while many properties of global precipitation variability in models are constrained to match observations in the development process, other properties are not so constrained, and should have errors that are uncorrelated with the errors in the observed data sets.

Our methodology will be to compare large scale properties of global precipitation over the period of record of the observed data sets (1979-2006), such as the mean global annual cycle and its hemispheric components, temporal changes in land versus oceanic precipitation and others in models and observation-based analyses.

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