Simulation of St. Louis, Missouri, Land Use Impacts on Thunderstorms

Abstract

A storm-resolving version of the Regional Atmospheric Modeling System is executed over St. Louis, Missouri, on 8 June 1999, along with sophisticated boundary conditions, to simulate the urban atmosphere and its role in deep, moist convection. In particular, surface-driven low-level convergence mechanisms are investigated. Sensitivity experiments show that the urban heat island (UHI) plays the largest role in initiating deep, moist convection downwind of the city. Surface convergence is enhanced on the leeward side of the city. Increased momentum drag over the city induces convergence on the windward side of the city, but this convergence is not strong enough to initiate storms. The nonlinear interaction of urban momentum drag and the UHI causes downwind convection to erupt later, because momentum drag over the city regulates the strength of the UHI. In all simulations including a UHI, precipitation totals are enhanced downwind of St. Louis. Topography around St. Louis also affects storm development. There is a large sensitivity of simulated urban-enhanced convection to the details of the urban surface model.

Air quality forecasting system for Southeastern Brazil

“…This version of the model is being called the BRAMS-SPM and is running in an operational mode at the Institute of Astronomy, Geophysics and Atmospheric Sciences of the University of São Paulo (IAG-USP), with the goal of forecasting the concentrations of tropospheric ozone, nitrogen oxides, VOCs, sulfur dioxide, and small particles (PM 10 and PM 2.5 ) over the MASP, in a 48-72 h time frame. Considering its application over very large urban regions, the BRAMS-SPM is also capable of representing in a very consistent way the effects of the urban structure, as well as those of anthropogenic heat and moisture emissions, by using the Town Energy Budget parameterization, as initially proposed by Masson (2000) and first introduced into the RAMS model by Rozoff et al (2003), in conjunction with the soil-vegetationatmosphere transfer scheme, the Land Ecosystem-Atmosphere Feedback model, version 2 (Walko et al, 2000). This is a very important feature, because urban air quality is highly dependent on mesoscale circulations generated by anomalous urban heating and roughness, creating the so called urban heat island effect, mentioned in studies conducted in various countries (Oke, 1987;Yoshikado and Tsuchida, 1996;Ichinose et al, 1999;Baik et al, 2001;Cenedese and Monti, 2003;Gedzelman et al, 2003;Childs and Raman, 2005;Jonsson, 2005;Freitas et al, 2007;Roth, 2007).…”

“…Soil-vegetation-atmosphere transfer Walko et al, 2000 Urban features Masson, 2000;Rozoff et al, 2003;Freitas et al, 2007 as the time step, simulation period, grid configuration, output time, and types of emissions (such as biogenic, anthropogenic, biomass burning, dust, and industrial stack emissions). The last step is the post processing, which can be done using the ARW program or a similar program in order to visualize the outputs.…”

Water vapour variability induced by urban/rural surface heterogeneities during convective conditions

“…Moreover, the peculiarity of urban areas may enhance convective precipitation (Thielen et al, 2000;Shepherd et al, 2002;Collier, 2006). The enhancement of convergence and convection above large urban area (Atlanta, New York, Saint Louis, Seoul) have indeed been used by several authors to explain the enhancement of precipitation (Baik et al, 2001;Rozoff et al, 2002;Dixon and Mote, 2003). However, the urban area can also create a barrier effect which reduces frontal precipitation (Bornstein and Lin, 2000).…”

Numerical Simulation of Urban Heat Island Effect by the WRF Model with 4-km Grid Increment: An Inter-Comparison Study between the Urban Canopy Model and Slab Model

“…In the urban climate study fields, a number of UCM schemes have been developed (e.g., Brown and Williams 1998, Masson 2000, Kusaka et al 2001, Martilli et al 2002, Harman et al 2004, Kondo et al 2005, Best 2005, Kanda et al 2005, Lee and Park 2008, Oleson et al 2008, Ikeda and Kusaka 2009, Porson et al 2009, Aoyagi and Seino 2011. Some researchers have coupled a UCM to a global climate model (GCM) (McCarthy et al 2010, Oleson et al 2011, and others couple the UCM to a regional climate model (RCM) (e.g., Lemonsu and Masson 2002, Rozo¤ et al 2003, Dandou et al 2005, Holt and Pullen 2007, Zhang et al 2007, Aoyagi and Seino 2011.…”