A radar-based climatology of 91 unique summertime (May 2000-August 2009) thunderstorm cases was examined over the Indianapolis, Indiana, urban area. The study hypothesis is that urban regions alter the intensity and composition/structure of approaching thunderstorms because of land surface heterogeneity. Storm characteristics were studied over the Indianapolis region and four peripheral rural counties approximately 120 km away from the urban center. Using radar imagery, the time of event, changes in storm structure (splitting, initiation, intensification, and dissipation), synoptic setting, orientation, and motion were studied. It was found that more than 60% of storms changed structure over the Indianapolis area as compared with only 25% over the rural regions. Furthermore, daytime convection was most likely to be affected, with 71% of storms changing structure as compared with only 42% at night. Analysis of radar imagery indicated that storms split closer to the upwind urban region and merge again downwind. Thus, a larger portion of small storms (50-200 km 2 ) and large storms (.1500 km 2 ) were found downwind of the urban region, whereas midsized storms (200-1500 km) dominated the upwind region. A case study of a typical storm on 13 June 2005 was examined using available observations and the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5), version 3.7.2. Two simulations were performed with and without the urban land use/Indianapolis region in the fourth domain (1.33-km resolution). The storm of interest could not be simulated without the urban area. Results indicate that removing the Indianapolis urban region caused distinct differences in the regional convergence and convection as well as in simulated base reflectivity, surface energy balance (through sensible heat flux, latent heat flux, and virtual potential temperature changes), and boundary layer structure. Study results indicate that the urban area has a strong climatological influence on regional thunderstorms.

[1] The urban canopy of excess heat, water vapor, and roughness can affect the evolution of weather systems, as can land vegetative processes. High-resolution simulations were conducted using the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS Experiments assessed the impact of land vegetative processes by (1) adding a canopy resistance scheme including photosynthesis (GEM) to the Noah LSM and (2) replacing the UCP with a simpler urban surface characterization of roughness, albedo, and moisture availability (NOUCP). The three sets of simulations showed different behaviors for the storm event. The CONTROL simulation propagated two storm cells through the OKC urban region. The NOUCP also resulted in two cells, although the convective intensity was weaker. The GEM simulation produced one storm cell west of the downtown region, whose intensity and timing were closer to the observed. To understand the relative roles of the urban and vegetation interaction processes, a factor separation experiment was performed. The urban model improved the ability to represent the MCS, and the enhanced representation of vegetation further improved the model performance. The enhanced performance may be attributed to better representation of the urban-rural heterogeneities and improved simulation of the moisture fluxes and upstream inflow boundaries.

The flux-adjusting surface data assimilation system (FASDAS) is developed to provide continuous adjustments for initial soil moisture and temperature and for surface air temperature and water vapor mixing ratio for mesoscale models. In the FASDAS approach, surface air temperature and water vapor mixing ratio are directly assimilated by using the analyzed surface observations. Then, the difference between the analyzed surface observations and model predictions of surface layer temperature and water vapor mixing ratio are converted into respective heat fluxes, referred to as adjustment heat fluxes of sensible and latent heat. These adjustment heat fluxes are then used in the prognostic equations for soil temperature and moisture via indirect assimilation in the form of several new adjustment evaporative fluxes. Thus, simulated surface fluxes for the subsequent model time step are affected such that the predicted surface air temperature and water vapor mixing ratio conform more closely to observations. The simultaneous application of indirect and direct data assimilation maintains greater consistency between the soil temperature-moisture and the surface layer mass-field variables. The FASDAS is coupled to a land surface submodel in a three-dimensional mesoscale model and tests are performed for a 10-day period with three one-way nested domains. The FASDAS is applied in the analysis nudging mode for two coarse-resolution nested domains and in the observational nudging mode for a fine-resolution nested domain. Further, the effects of FASDAS on two different initial specifications of a three-dimensional soil moisture field are also studied. Results indicate that the FASDAS consistently improved the accuracy of the model simulations.