Several recent observational studies suggest that precipitation may be increasing at a much faster rate than currently predicted by GCMs. These discrepancies appear at time-scales ranging from interannual, to decadal, to centennial and have important implications for future projections of climate change, the reliability of the observing system and the monitoring of the global water cycle. If true, such a bias in model projections would have substantial repercussions – not only for the modeling of the atmospheric energy and water budgets, but also for the model projections of the response of the atmospheric and oceanic circulation to increased CO2. However, the veracity of the satellite-observed changes in precipitation remains in question due, in large part, to uncertainties in the retrieval of precipitation from passive microwave sensors. The PIs propose to better understand the cause of these discrepancies by performing a detailed comparison of SSMI observations and GFDL GCM simulations using a “model-to-satellite” approach in which model output is used to directly simulate the radiances which would be observed by the satellite under those conditions. The advantages of this strategy are that it avoids many of the assumptions that are required when performing retrievals and it provides a model-simulated quantity that is directly comparable to what is actually observed by the satellite. Any assumptions involved in the performing forward radiance simulation are made explicit and can be varied in a controlled framework to examine their sensitivity. They propose to apply this strategy for comparing model-simulated microwave radiances from the GFDL GCM to the satellite-observed radiances from SSMI. From this comparison they hope to better understand the cause of bias between observed and model-simulated precipitation response to a warming climate.