Abstract
The Mexican monsoon is a significant feature in the climate of the southwestern United States and Mexico during the summer months. Rainfall in northwestern Mexico during the months of July through September accounts for 60% to 80% of the total annual rainfall, while rainfall in Arizona for these same months accounts for over 40% of the total annual rainfall. Deep convection during the monsoon season produces frequent damaging surface winds, flash flooding, and hail and is a difficult forecast problem. Past numerical simulations frequently have been unable to reproduce the widespread, heavy rains over Mexico and the southwestern United States associated with the monsoon. The Pennsylvania State University/National Center for Atmospheric Research mesoscale model is used to simulate 32 successive 24-h periods during the monsoon season. Mean fields produced by the model simulations are compared against observations to validate the ability of the model to reproduce many of the observed features, including the large-scale midtropospheric wind field, southerly low-level winds over the Gulf of California, and the heavy rains over western Mexico. Preliminary analysis of the mean model fields also suggest that the Gulf of California is the dominant moisture source for deep convection over Mexico and the southwestern United States, with upslope flow along the Sierra Madre Occidental advecting low-level gulf moisture into western Mexico during the daytime and southerly flow at the northern end of the gulf advecting gulf moisture into Arizona on most days. These results illustrate the usefulness of four-dimensional data assimilation techniques to create proxy datasets containing realistic mesoscale features that can be used for detailed diagnostic studies.
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