Evaluation of WRF model output for severe-weather forecasting from the 2008 NOAA Hazardous Weather Testbed Spring Experiment

The result is that the deterministic CAMs do not predict the environment as well as the NAM. It is suggested that parameterized processes used at convection-allowing grid lengths, particularly in the boundary layer, may be contributing to these errors. It is also shown that mean forecasts from an ensemble of CAMs were substantially more accurate than forecasts from deterministic CAMs.

If the improvement seen in the CAM forecasts when going from a deterministic framework to an ensemble framework is comparable to improvements in mesoscale model forecasts when going from a deterministic to an ensemble framework, then an ensemble of mesoscale model forecasts could predict the environment even better than an ensemble of CAMs. Therefore, it is suggested that the combination of mesoscale (convection parameterizing) and CAM configurations is an appropriate avenue to explore for optimizing the use of limited computer resources for severe weather forecasting applications.