Validation of a Data Assimilation Technique for an Urban Wind Model

The QUIC (Quick Urban & Industrial Complex) dispersion modeling system has been developed to calculate wind and concentration fields in cities with buildings explicitly resolved. To improve the fast response 3D diagnostic urban wind model (QUIC-URB), a new data assimilation initialization scheme has been developed. The original QUIC-URB code initialized the flow field with horizontally uniform velocities based on wind speed and wind direction information obtained from a single sensor upwind of an urban area, but previous urban studies have shown that cities are often subject to large scale spatially varying inflows. To account for this spatial heterogeneity, a simple Quasi-3D Barnes Objective Map Analysis Scheme (a Gaussian weighted-averaging technique) which initializes the flow field based on multiple sensors and soundings located around the urban area. This wind field is then modified by QUIC-URB's empirical building flow parameterizations to model the flow around the individual buildings. The final flow field is then solved for by ensuring mass conservation.

This work is the first validation of the multi-sensor data assimilation QUIC-URB model. QUIC-URB mean 3D velocities are compared to the results of a FLUENT k-e solution of the same urban environment. Individual vertical velocity profiles at various strategic locations around the urban area were extracted from the FLUENT data set to simulate soundings around an actual urban environment. These velocity profiles were then used as input parameters for QUIC-URB's new initialization scheme. After applying QUIC-URBs building parameterizations and enforcing mass conservation, the final wind fields from QUIC-URB and FLUENT were quantitatively compared. This comparison illuminated areas of deficiencies in the data assimilation model that are being used to improvement the model.