With the increased populations within urban areas and along coastlines severe weather events such as tropical cyclones and winter storms can have an increased impact on infrastructure and industrial operations. This paper will discuss how mesoscale models can be used as an analysis tool to assess the impact of severe weather events by developing realistic high-resolution data sets of meteorological fields for the time period of the event.

This study involved the use of the Penn State/NCAR Fifth Generation Mesoscale model (MM5) to simulate the landfall of Hurricane Katrina and its passage across the New Orleans urban area. The MM5 simulations were conducted with four dimensional data assimilation and thus were not forecasts of the storm but represent an analysis of the event. The model was configured with multiple two-way interactive nested grids down to a spatial resolution of 2 km and a tropical cyclone bogussing scheme was implemented to improve the representation of the hurricanes structure and position during model initialization. The model results showed that MM5 performed well, reproducing the overall structure of the storm on the 6 km resolution domain. The details of the inner core-structure of the storm were well represented by the 2 km resolution grid. The MM5 simulated maximum surface winds were close to the observed maximum sustained winds from the Tropical Prediction Center's Best Track Data. Vertical wind profiles within the planetary boundary layer as determined from the MM5 simulations were consistent with wind profiles taken from dropsondes within the northeast part of the hurricanes eye-wall as it crossed the coast. The wind data from the MM5 simulations were successfully used in CFD model simulations to determine that wind was the cause of structural damage to buildings during the event.

This analysis shows that mesoscale models such as MM5 are powerful post-event analysis tools that can develop high-resolution analysis data sets. The model data can supplement available observational data as well as provide realistic data when observations are missing. Use of mesoscale models such as MM5 can be extended to a wide range of meteorological events and other parameters can be examined as well such as precipitation to assess flooding events. Such information can be used by industry, urban planners and others to identify the causes of damage to buildings and other structures.