| description abstract | The sensitivity of numerical model forecasts of coastal cyclogenesis and frontogenesis to the choice of model cumulus parameterization (CP) scheme is examined for the 17 February 2004 southeastern U.S. winter weather event. This event featured a complex synoptic and mesoscale environment, as the presence of cold-air damming, a developing coastal surface cyclone, and an upper-level trough combined to present a daunting winter weather forecast scenario. The operational forecast challenge was further complicated by erratic numerical model predictions. The most poignant area of disagreement between model runs was the treatment of a coastal cyclone and an associated coastal front, features that would affect the location and timing of precipitation and influence the precipitation type. At the time of the event, it was hypothesized that the Betts?Miller?Janji? (BMJ) CP scheme was dictating the location and intensity of the initial coastal cyclone center in operational Eta Model forecasts. For this reason, forecasts for this case were rerun with the workstation Eta Model using the Kain?Fritsch (KF) CP scheme to further examine the sensitivity to this parameterization choice. Results confirm that the model CP scheme played a major role in the forecast for this case, affecting the quantitative precipitation forecast as well as the strength, location, and structure of coastal cyclogenesis and coastal frontogenesis. The Eta Model forecast using the KF CP scheme produced a relatively uniform distribution of convective precipitation oriented along the axis of an inverted trough and strong coastal front. In contrast, the BMJ forecasts resulted in a weaker coastal front and the development of multiple distinct closed cyclonic circulations in association with more localized convective precipitation centers. An additional BMJ forecast in which the shallow mixing component of the scheme was disabled bore a closer semblance to the KF forecasts relative to the original BMJ forecast. Suggestions are provided to facilitate the identification of CP-driven cyclones using standard operational model output parameters. | |
