Performance of the WRF Model at the Convection-Permitting Scale in Simulating Snowfall and Lake-Effect Snow Over the Tibetan Plateau

• This study investigated the performance of the Weather Research Forecasting (WRF) model at 4-km horizontal grid spacing in simulating precipitation, 2 m air temperature (T2), snowfall, and lake-effect snow (October 4-8, 2018) over the Tibetan Plateau (TP). Multiple simulations with different physical parameterization schemes (PPSs), including two planetary boundary layer schemes (Yonsei University and Mellor-Yamada-Janjic), no cumulus and multi-scale Kain-Fritsch, two land surface models (Noah and Noah-MP), and two microphysics schemes (Thompson and Milbrandt), were conducted and compared. Compared with gauge observations, all PPSs simulate mean daily precipitation with mean relative errors (MREs) of 27.7%-53.6%. Besides, spatial correlation coefficients (SCCs) between simulated and observed mean daily precipitation range from 0.56 to 0.71. For simulations of T2, all PPSs perform similarly well, even though the mean cold biases are up to about 3 degrees C. Meanwhile, all PPSs exhibit acceptable performance in simulating spatial distributions of snow depth, snow cover, and snowfall amount, with SCCs of 0.37-0.65 between simulations and observations. However, the WRF simulations significantly overestimate snow depth (similar to 0.4 cm mean error) and snowfall amount (MREs >372%). The Milbrandt scheme slightly outperforms the other PPSs in simulating snow-related variable magnitudes. Due to their inaccurate temperature and airflow modeling over the lake surface and its surroundings, none of the WRF simulations well reproduce the characteristics that more snow occurs over the lake and downwind area. Overall, this study provides a useful reference for future convection-permitting climate modeling of snow or other extreme events when using the WRF model in the TP and other alpine regions. Plain Language Summary Snow falls frequently in cold seasons, especially in alpine regions. When there is a lake, a very interesting snowfall phenomenon named lake-effect snow may happen, that is, more snow occurred over the lake and downwind areas. However, the lake-effect snow caused by large lakes over the Tibetan Plateau (TP) may induce snow disaster events. Thus, conducting reliable simulations of lake-effect snow events are essential for understanding the mechanism of these particular events over the TP. This study investigated the performance of the numerical model in simulating precipitation, 2 m air temperature (T2), snowfall, and lake-effect snow (October 4-8, 2018) over the TP. The results show that the simulated precipitation and T2 perform reasonably well, although wet and cold biases are observed. However, the investigated numerical model fails to reproduce the characteristics of this event well, which may be due to the inaccurate temperature and airflow modeling over the lake surface and its surroundings. Continued improvement is needed for future modeling. Hence, this study provides some suggestions for future numerical modeling of lake-effect snow or other snow events over the TP and other alpine regions.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Meteorologi och atmosfärforskning (hsv//swe)

NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Meteorology and Atmospheric Sciences (hsv//eng)

Nyckelord

WRF

convection-permitting

lake-effect

snow

bulk microphysics parameterization

orographic form drag

great-lakes

weather research

winter precipitation

effect snowstorms

part ii

resolution

basin

cover

Meteorology & Atmospheric Sciences

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art (ämneskategori)