Simulating the effects of the St. Louis urban center on mesoscale convective systems using WRF
Date
2012
Authors
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Journal ISSN
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Publisher
University of Delaware
Abstract
The potential of an urban center to modify convective storms has long been
theorized. An urban center has been shown to deflect small storms around it while
enhancing deep, moist convection downwind of the city. We used the Advanced
Research Weather Research and Forecasting (WRF-ARW) model to investigate urban
influences on mesoscale convective systems (MCS) using case studies. St. Louis was
chosen as the urban center of interest for this study, making use of the substantial
observational data for the city from the Metropolitan Meteorological Experiment
(METROMEX). A series of six events, including three MCS events and three isolated
thunderstorm events, in the vicinity of St. Louis, Missouri was modeled. The National
Center for Environmental Prediction’s (NCEP) operational Eta 212 grid model output
analyses were used for the initial and boundary conditions. In each case study, the
‘urban’ simulation (control) couples an Urban Canopy Model (UCM) to the WRF
model for better representation of urban surface fluxes. The ‘no-urban’ simulation
(perturbation) uses only the Noah Land Surface model to determine surface fluxes. In
addition, all urban land use in the ‘no-urban’ simulation was replaced with an
aggregate of crops, woods, and deciduous forest, essentially removing the city of
St. Louis.
A comparison of the urban and no-urban simulations shows minor but
discernible effects on tracking and intensity of isolated thunderstorms and MCS. All
events reveal greater total moisture in the low-level column in the urban configuration
before the onset of precipitation. In addition, five of the six events showed increases in precipitation over and downwind of the city, including all three MCS events. It is
suspected that the city acts as a mechanism for moisture convergence, leading to more
precipitation over and downwind of the city, consistent with previous observational
and modeling studies.