Abstract

Abstract This study examines the capabilities and limitations of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) in predicting the precipitation and circulation features that accompanied the 2004 North American monsoon (NAM). When the model is reinitialized every 5 days to restrain the growth of modeling errors, its results for precipitation checked at subseasonal time scales (not for individual rainfall events) become comparable with ground- and satellite-based observations as well as with the NAM’s diagnostic characteristics. The modeled monthly precipitation illustrates the evolution patterns of monsoon rainfall, although it underestimates the rainfall amount and coverage area in comparison with observations. The modeled daily precipitation shows the transition from dry to wet episodes on the monsoon onset day over the Arizona–New Mexico region, and the multiday heavy rainfall (>1 mm day−1) and dry periods after the onset. All these modeling predictions agree with observed variations. The model also accurately simulated the onset and ending dates of four major moisture surges over the Gulf of California during the 2004 monsoon season. The model reproduced the strong diurnal variability of the NAM precipitation, but did not predict the observed diurnal feature of the precipitation peak’s shift from the mountains to the coast during local afternoon to late night. In general, the model is able to reproduce the major, critical patterns and dynamic variations of the NAM rainfall at intraseasonal time scales, but still includes errors in precipitation quantity, pattern, and timing. The numerical study suggests that these errors are due largely to deficiencies in the model’s cumulus convective parameterization scheme, which is responsible for the model’s precipitation generation.

Highlights

  • This study investigated the capacity of a regional climate model (RCM) to reproduce the major elements of the 2004 North American monsoon (NAM) system

  • Following the first approach in the 2004 NAM modeling and through a set of pretests, we found that by reinitializing every five model days—the longest updating time interval in our tests, the 2004 NAM simulation was comparable with observations and consistent with the NAM’s diagnostic features when checked at intraseasonal time scales

  • In July, the model still underestimates rainfall, it shows that the NAM precipitation regime reaches northwestern Mexico and continues extending northeastward, passing Arizona and New Mexico into the high plains of Colorado and Kansas

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Summary

Introduction

NAM system characteristics that were exposed by diagnostic studies based on historic observations and data-assimilation reanalysis. We used a currently available, physically based numerical model to check the agreement and disagreement between the model results, the statistical diagnoses, and the observations; to examine which types of features are predictable or unpredictable; and to identify the possible reasons that are associated with the model’s physics. The diagnostic analysis and numerical modeling are distinct research strategies. The former is used to summarize the mean features of the NAM system based on long-term observation and reanalysis; the latter is used to simulate and predict individual NAMs under the circumstances of specific years. From the viewpoint of model improvement, it is important to examine how the diagnostic features and their variations can be captured by a numerical model in its case-by-case predictions. This study intends to evaluate the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model’s (MM5) capabilities and limitations in reproducing intraseasonal vari-

MAY 2007
Model description
Precipitation observation data
Summary
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