Abstract

Abstract A new bulk microphysical parameterization (BMP) scheme is presented that includes a diagnosed riming intensity and its impact on ice characteristics. As a result, the new scheme represents a continuous spectrum from pristine ice particles to heavily rimed particles and graupel using one prognostic variable [precipitating ice (PI)] rather than two separate variables (snow and graupel). In contrast to most existing parameterization schemes that use fixed empirical relationships to describe ice particles, general formulations are proposed to consider the influences of riming intensity and temperature on the projected area, mass, and fall velocity of PI particles. The proposed formulations are able to cover the variations of empirical coefficients found in previous observational studies. The new scheme also reduces the number of parameterized microphysical processes by ∼50% as compared to conventional six-category BMPs and thus it is more computationally efficient. The new scheme (called SBU-YLIN) has been implemented in the Weather Research and Forecasting (WRF) model and compared with three other schemes for two events during the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) over the central Oregon Cascades. The new scheme produces surface precipitation forecasts comparable to more complicated BMPs. The new scheme reduces the snow amounts aloft as compared to other WRF schemes and compares better with observations, especially for an event with moderate riming aloft. Sensitivity tests suggest both reduced snow depositional growth rate and more efficient fallout due to the contribution of riming to the reduction of ice water content aloft in the new scheme, with a larger impact from the partially rimed snow and fallout.

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