Numerical modeling evaluation demonstrates that refining riming parameterizations reduces precipitation error by 23.8% across complex terrain, highlighting the role of liquid-ice mixing.
The Tibetan Plateau (TP) is characterized by frequent mixed-phase clouds, in which riming exerts a crucial control on precipitation formation. However, conventional bulk microphysics schemes generally ignore the regulatory impact of sub-grid liquid-ice mixing state on riming processes. This study improves the riming parameterization within the WRF Morrison scheme by adopting constant reduction coefficients and introducing a diagnostic mixing homogeneity parameter χ for snow and graupel, which varies with condensed water content and temperature. Reduced riming coefficients correct simulated precipitation distribution and spatial deviation, while χ -based dynamic regulation further optimizes temporal variation of regional precipitation, reducing RMSE by 23.8%. The modified scheme shows superior performance across all rainfall grades, particularly for heavy and torrential rain. Physically, χ inhibits excessive riming, maintains supercooled liquid droplets, and effectively alleviates the overestimation of surface precipitation. One-month simulations validate that considering liquid-ice mixing homogeneity markedly improves WRF precipitation simulation capability over the TP.
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Yang et al. (2026) studied this question.
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