Constraining Model Uncertainties in Nested Simulations of Winter Storms in the Southern Great Plains

Esther White CIMMS/University of Oklahoma
Lance Leslie Ohio University
Peter Lamb University of Oklahoma

Category: Modeling

We have shown that the WRF-ARW model is able to reliably simulate the observed evolution of a number of thermodynamic and physical parameters within Southern Great Plains winter storms. However, our recent analysis of a number of cases has revealed uncertainties in the simulation of cloud and precipitation evolution. This makes evaluation of cloud properties difficult due to large displacement errors, both spatially and temporally. We will examine the role of input and boundary conditions in the evolution of the simulation of three winter storms. Three input and boundary data options are being considered: the NAM-AWIPs, NCEP-FNL, and NARR. We will then examine the effectiveness of WRF four-dimensional data assimilation (FDDA) options, including both grid (analysis) and observational nudging of the upper-level wind fields in constraining simulation error. Model output will be compared to ARM SGP data, along with NCEP Stage IV radar-derived precipitation and satellite observations. The role of input and boundary conditions on the evolution of cloud systems and structure also will be evaluated and compared to recent microphysics sensitivity studies.

This poster will be displayed at ASR Science Team Meeting.