| description abstract | This study presents results from an experiment conducted to measure the impact of locally initializing a numerical weather prediction model on that model?s ability to predict precipitation and other surface parameters. The study consisted of quantifying the impact of initializing the Weather and Research Forecast (WRF) model with the Advanced Weather Interactive Processing System (AWIPS) Local Analysis and Prediction System (LAPS) diagnostic analyses. In the experiment, WRF was run for two different initial times: 0600 and 1800 UTC. For each initial time, the model was run twice, once using LAPS for the initial conditions, and once using the North American Mesoscale model (NAM; also known as the Eta Model at the time of the experiment). The impact of the local LAPS initialization on the model forecast of surface parameters is presented. Additionally, the model?s quantitative precipitation forecast (QPF) skill is compared for three different model configurations: 1) WRF initialized with LAPS, 2) WRF initialized with NAM, and 3) the standard NAM/Eta Model. The experiment ran from 1 June 2005 to 31 July 2005. Results show that WRF forecasts initialized by LAPS have a more accurate representation of convection in the short range. LAPS-initialized forecasts also offer more accurate forecasts of 2-m temperature and dewpoint, 10-m wind, and sea level pressure, particularly in the short range. Most significantly, precipitation forecasts from WRF runs initialized by LAPS are more accurate than WRF runs initialized by NAM. WRF initialized with LAPS also demonstrates higher QPF skill than does the NAM/Eta Model, particularly in the short range when the precipitation thresholds are higher (0.25 in. in 3 h versus 0.10 in. in 3 h), and when forecasts are initialized at 0600 UTC rather than initialized at 1800 UTC. | |
