SGER: Observing the Interdependence of Precipitation and Precipitable Water Vapor during the North American Monsoon Experiment (NAME)

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The overall scientific objective of this investigation is to understand the interdependence of the summertime precipitation and vertically integrated precipitable water vapor (PWV) in the Sierra Madre Occidental (SMO) Mountains in Northwestern Mexico during the North American Monsoon (NAM). The focus is on characterizing and understanding, at several time scales, the PWV, boundary layer moisture, winds, convective storm environment and precipitation and evaporation within the SMO and how they are modulated by larger-scale weather features, such as inverted troughs, tropical storms, and Gulf surges as well as how they are affected by the previous day's convective activity. The PI hypothesizes that a strong diurnal cycle in PWV exists within the NAME region that leads to maximum convective available potential energy (CAPE) and minimum convective inhibition (CIN) over the middle elevations, SMO foothills and the Mexican thorn forest region, west of the divide of the SMO, coinciding with the area of observed maximum summer rainfalls and convective storm intensities. It is further hypothesized that this diurnal cycle of PWV is modulated significantly by transient mesoscale and large-scale weather features that frequently affect the NAME region during summer, e.g., organized and large mesoscale convective systems (MCSs), northward surges of low-level moisture up the Gulf of California, westward moving middle and upper-level cyclones and inverted troughs, and northward moving tropical disturbances. To accomplish his goals, the PI will place a network of 6 GPS receivers (that provide continuous measurements of PWV) and surface meteorological instrumentation at locations across the SMO to make observations during the NAME field campaign (summer 2004). Broader impacts include improved understanding of the processes that regulate summer rainfall over the North American monsoon region, which can lead to more accurate precipitation forecasts of benefit to societal activities including water management.