MODEL CLIMATOLOGY OF THE MEXICAN MONSOON

Citation
Dj. Stensrud et al., MODEL CLIMATOLOGY OF THE MEXICAN MONSOON, Journal of climate, 8(7), 1995, pp. 1775-1794
Citations number
42
Categorie Soggetti
Metereology & Atmospheric Sciences
Journal title
ISSN journal
08948755
Volume
8
Issue
7
Year of publication
1995
Pages
1775 - 1794
Database
ISI
SICI code
0894-8755(1995)8:7<1775:MCOTMM>2.0.ZU;2-J
Abstract
The Mexican monsoon is a significant feature in the climate of the sou thwestern United States and Mexico during the summer months. Rainfall in northwestern Mexico during the months of July through September acc ounts for 60% to 80% of the total annual rainfall, while rainfall in A rizona 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 f orecast problem. Past numerical simulations frequently have been unabl e to reproduce the widespread, heavy rains over Mexico and the southwe stern United States associated with the monsoon. The Pennsylvania Stat e University/National Center for Atmospheric Research mesoscale model is used to simulate 32 successive 24-h periods during the monsoon seas on. Mean fields produced by the model simulations are compared against observations to validate the ability of the model to reproduce many o f the observed features, including the large-scale midtropospheric win d field, southerly low-level winds over the Gulf of California, and th e heavy rains over western Mexico: Preliminary analysis of the mean mo del fields also suggest that the Gulf of California is the dominant mo isture source for deep convection over Mexico and the southwestern Uni ted States, with upslope flow along the Sierra Madre Occidental advect ing low-level gulf moisture into western Mexico during the daytime and Southerly flow at the northern end of the gulf advecting gulf moistur e into Arizona on most days. These results illustrate the usefulness o f four-dimensional data assimilation techniques to create proxy datase ts containing realistic mesoscale features that can be used fbr detail ed diagnostic studies.