The Dependence of QPF on the Choice of Boundary- and Surface-Layer Parameterization for a Lake-Effect Snowstorm

Abstract

AbstractSix forecasts of a lake-effect-snow event off Lake Erie were conducted using the Weather Research and Forecasting Model to determine how the quantitative precipitation forecast (QPF) was affected when the boundary- and surface-layer parameterization schemes were changed. These forecasts showed strong variability, with differences in liquid-equivalent precipitation maxima in excess of 20 mm over a 6-h period. The quasi-normal scale elimination (QNSE) schemes produced the highest accumulations, and the Mellor–Yamada–Nakanishi–Niino (MYNN) schemes produced the lowest. Differences in precipitation were primarily due to different sensible heat flux FH and moisture flux FQ off the lake, with lower FH and FQ in MYNN leading to comparatively weak low-level instability and, consequently, reduced ascent and production of hydrometeors. The different FH and FQ were found to have two causes. In QNSE, the higher FH and FQ were due to the decision to use a Prandtl number PR of 0.72 (all other schemes use a PR of 1). In MYNN, the lower FH and FQ were due to the manner in which the similarity stability function for heat ψh is functionally dependent on the temperature gradient between the surface and the lowest model layer. It is not known what assumptions are more accurate for environments that are typical for lake-effect snow, but comparisons with available observations and Rapid-Update-Cycle analyses indicated that MYNN had the most accurate results.