Comparison of a Spectral Bin and Two Multi-Moment Bulk Microphysics Schemes for Supercell Simulation: Investigation into Key Processes Responsible for Hydrometeor Distributions and Precipitation

Abstract

There are more uncertainties with ice hydrometeor representations and related processes than liquid hydrometeors within microphysics parameterization (MP) schemes because of their complicated geometries and physical properties. Idealized supercell simulations are produced using the WRF model coupled with “full” Hebrew University spectral bin MP (HU-SBM), and NSSL and Thompson bulk MP (BMP) schemes. HU-SBM downdrafts are typically weaker than those of the NSSL and Thompson simulations, accompanied by less rain evaporation. HU-SBM produces more cloud ice (plates), graupel, and hail than the BMPs, yet precipitates less at the surface. The limiting mass bins (and subsequently, particle size) of rimed ice in HU-SBM and slower rimed ice fall speeds lead to smaller melting-level net rimed ice fluxes than those of the BMPs. Aggregation from plates in HU-SBM, together with snow–graupel collisions, leads to a greater snow contribution to rain than those of the BMPs. Replacing HU-SBM’s fall speeds using the formulations of the BMPs after aggregating the discrete bin values to mass mixing ratios and total number concentrations increases net rain and rimed ice fluxes. Still, they are smaller in magnitude than bulk rain, NSSL hail, and Thompson graupel net fluxes near the surface. Conversely, the melting-layer net rimed ice fluxes are reduced when the fall speeds for the NSSL and Thompson simulations are calculated using HU-SBM fall speed formulations after discretizing the bulk particle size distributions (PSDs) into spectral bins. The results highlight precipitation sensitivity to storm dynamics, fall speed, hydrometeor evolution governed by process rates, and MP PSD design.

摘 要

由于具有复杂的几何和物理性质,微物理参数化(MP)方案中冰相物特征及相关过程比液相物不确定性更大。本文利用将WRF模式与“完整”版本的希伯来大学分档云微物理参数化方案(HU-SBM)、NSSL以及Thompson 体积水云微物理参数化方案(BMP)耦合,对理想超级单体进行模拟。HU-SBM模拟的下沉气流通常弱于NSSL和Thompson模拟的下沉气流,同时伴随着更少的雨水蒸发。HU-SBM比BMPs产生了更多的云冰(圆盘形冰粒)、霰和冰雹,但是在地表的降水较少。相比于BMPs,HU-SBM中冰粒的有限的质量分档(其次,粒径分档)和冰粒较慢的下降速度导致了更小的融化层冰粒净通量。在HU-SBM中,圆盘形冰粒的聚合以及雪-霰的碰并导致了雪对雨水的贡献比BMPs更大。在HU-SBM中,将离散的分档值聚合得到质量混合比和总数量浓度后,使用BMPs的公式来计算下降速度,可增加雨水和冰粒的净通量。尽管如此,总体雨水、NSSL冰雹和Thompson霰在近地面的净通量的量级上,HU-SBM仍较小。相反,将NSSL 和 Thompson中的整体粒径分布(PSDs)离散成谱段,并使用 HU-SBM 的公式计算下降速度时,融化层冰粒净通量减少。研究结果突出了降水对风暴动力条件、下降速度、微物理过程速率控制的水凝物演变,以及MP PSD设计的敏感性。