7.3 Orographic influences on the lake-effect snow of the Great Salt Lake

Friday, 11 August 2000: 9:00 AM
Daryl J. Onton, NOAA/Cooperative Institute for Regional Prediction and Univ. of Utah, Salt Lake City, UT

Among the most important wintertime weather phenomena of northern Utah is lake-effect snow produced by the Great Salt Lake (GSL) and enhanced by the surrounding mountainous topography. The so-called Great Salt Lake-Effect (GSLE) occurs several times each year, commonly produces snowfalls of 20-50 cm, and contributed to the state record lowland storm-total snowfall of 129 cm. Often characterized by extreme variability in snowfall accumulations over small distances, GSLE is also one of the most difficult weather features to forecast operationally.

In many ways the GSLE is similar to lake-effect snows of the Great Lakes, but the GSL is much smaller, highly saline, and surrounded by dramatic vertical relief. The small size and high salinity of the GSL reduce the availability of moisture available from surface fluxes, while four major mountain ranges rising over 2000 meters above the lake surface provide significant potential for orographic uplift and low-level flow blocking and channeling. The role of this topography on the formation and enhancement of GSLE snow has long been a source of uncertainty. To help determine the importance of topography in the case of a wind-parallel midlake GSLE snowband, similar to those which are generally responsible for the heaviest and most localized snowfalls, numerical simulations by the nonhydrostatic Penn State/NCAR mesoscale model MM5 were performed. Through the use of model sensitivity experiments altering topography, it was found that orographic effects caused local enhancements in precipitation exceeding 75% while only increasing domain average precipitation by 7%. However, orographic effects were not directly responsible for the formation of the snowband. This research highlights the importance of topographic effects in modifying a thermally-driven mesoscale precipitation feature.

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