Evaluation of model performance and possible improvements of microphysical parameterizations by using radar data

Rainfall within Mesoscale Convective Systems (MCSs) is a major source of warm-season precipitation for the agriculturally important American Midwest, and dangerous flash flooding is often associated with these systems. Therefore the accurate forecasting of precipitation for these events is essential. Accurate forecasting of MCS rainfall requires good predictions of the occurrence, timing, location of the systems, and the rainfall amount.

The main focus of the present study is on an objective evaluation of performance of various microphysics schemes available in the WRF-ARW numerical model by using available radar data. These results will be used to estimate individual contributions of parameterized processes that represent generation and depletion of various hydrometeors. This is expected to provide basis for data assimilation for objectively adjusting critical parameters in microphysics schemes, which would consequently lead to precipitation prediction improvement. For this purpose simulations of several events that occurred during the International H2O Project (IHOP) field experiment will be performed by using the WRF-ARW model with three different microphysics schemes. Results from this study will be used for developing a strategy for better definition of cost function measures in 4DVAR data assimilation approach.