Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

The Weather Research and Forecasting Model (WRF) is a numerical weather prediction model maintained by the National Center for Atmospheric Research (NCAR). The US Army Research Laboratory (ARL) has developed the Weather Running Estimate Nowcast (WRE N) model based on the Weather Research and Forecasting Model Advanced Research WRF (WRF ARW) to predict small-scale phenomena of interest to Warfighters, such as mountain/valley breezes and land/sea breezes. NCAR has developed the Model Evaluation Tools (MET) to evaluate the accuracy of WRF forecasts using observations of meteorological variables. The traditional use of MET calculates model performance over the entire model domain. High-resolution modeling requires more focused verification at subdomain levels. A Geographical Information System (GIS) enables consideration of terrain variables in model assessments using a location-based approach. We discuss our GIS approach to verify WRF-ARW with a 1-kilometer horizontal resolution inner domain centered near San Diego, California. We selected 5 case study days from February and March of 2012. The literature indicated that elevation is strongly correlated with meteorological parameters, which became our focus. We found that elevation accounts for a significant portion of the variance in the model error. The study demonstrated that a GIS can analyze spatially distributed point forecast errors over subdomains, to reveal the dependence of forecast errors on elevation. The original document contains color images.