Utilizing Idealized Mesoscale Model Simulations to Aid the Prediction of Lake-Effect Snowstorms
Neil F. Laird, University of Illinois, Urbana, IL; and D. A. R. Kristovich
Forecasters in the Great Lakes region have for several decades recognized a general relationship of wind speed and over-lake fetch to lake-effect snowstorm morphology. A recent study using idealized mesoscale model simulations of lake-effect conditions over circular and elliptical lakes showed the ratio of wind speed to maximum fetch distance (U/L) may be used to effectively predict lake-effect snowstorm morphology. The current investigation provides an assessment of the U/L criteria using observational data sets. Previously published Great Lakes lake-effect snowstorm observational studies were used to identify events of known mesoscale morphology. Hindcasts of nearly 640 lake-effect events were performed using historical observations and U/L as the predictor.
Results show that the quantity U/L contains important information on the different mesoscale lake-effect morphologies, however it provides only a limited benefit when being used to predict mesoscale morphology in real lake-effect situations. The U/L criteria exhibited the greatest probability of detecting lake-effect shoreline band events, often the most intense, but also experienced a relatively large number of false hindcasts.
In addition, the Great Lakes Environmental Research Laboratory ice cover digital data set was used in combination with observations from past lake-effect events to account for regions of significant ice cover and assess the impact of ice cover on the use of U/L as a predictor. Results show that hindcasts of lake-effect morphology using the U/L criteria were slightly improved when the reduction of open-water areas due to lake ice cover was taken into account.
Extended Abstract (404K)
Session 18, Cyclogenesis and Winter Weather (ROOM 607)
Wednesday, 14 January 2004, 4:00 PM-5:30 PM, Room 607
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