Skill Assessment and Benefits on Applying the New Weather Research and Forecast Model to National Weather Service Forecast Operations

Under the auspices of a nationwide effort led by NOAA, known as the Coastal Storms Initiative (CSI), the new Weather Research and Forecast (WRF) mesoscale model has been installed at the Jacksonville, FL (JAX) National Weather Service (NWS) Weather Forecast Office (WFO). The purpose of the CSI project is to lessen the impacts of storms on coastal communities. This research focuses on the local modeling component to determine the added skill of implementing the WRF model for improved forecasts of precipitation, coastal winds, and visibility. This marks first the time that this model has been applied operationally in an NWS WFO. A detailed evaluation is performed to determine whether the WRF model can serve as the local modeling component in the WFO in a manner similar to how the workstation Eta has in other WFOs. As decided by the NOAA entities involved, two simulations of the WRF model are run, one that is initialized using NOAA's Local Analysis and Prediction System (LAPS) and the other is initialized from NCEP's Eta 218 forecast grids. Thus, this project also seeks to address whether the use of a data assimilation component can improve local model forecasts. Both simulations are initialized at 06 UTC which allows for a direct comparison to the 12 km Eta model. The forecasts of the WRF version 1.3 and Eta model output are statistically evaluated for both the summer and fall seasons of 2003. Systematic errors of precipitation entities are studied with use of a modified Ebert & McBride precipitation verification technique based on morphology. The Contour Error Mapping method is applied to compare the skill of the WRF model to the Eta for the detection, transition timing, and propagation of sea breeze fronts for the entire model domain. This phenomelogical evaluation is performed for 58 days during the initial test period of the WRF model from the 2003 warm season. In addition, the performance of the WRF-LAPS is examined for tropical storm Henri. The WRF-LAPS outperforms the 12 km Eta model for sea breeze detection by a considerable margin. In addition, the ability of the WRF model to correctly forecast sea breeze, frontal, and pop-up convective rain entities through twenty-four hours helps to aide the JAX forecasters in issuing more accurate short term precipitation forecasts. The WRF-LAPS has superior visibility forecasts compared to the RUC2 and improved wind forecasts over both the Eta and WRF-Eta models. However, a strong warm temperature bias near the top of the boundary layer is routinely forecast, which results in an atmosphere forecast too stable and an aggressive cold bias near the surface. This bias disrupts the modeled sea breeze from experiencing accurate propagation and results in sea breeze convection with significant displacement errors. In July of 2004 the WRF version 2.0 was installed at the JAX WFO with the intention of correcting the afternoon temperature bias problem. Initial evaluations of the short term forecast reveals that the WRF-LAPS version 2.0 results in a drastic improvement for temperature forecasts and improves the performance for precipitation and sea breeze propagation. The encouraging forecast capability for important mesoscale features suggest that the WRF model could serve as a powerful tool for operational coastal forecasting.