Semi-Analytic Functions to Calculate the Deposition Coefficients for Ice Crystal Vapor Growth in Bin and Bulk Microphysical Models.
Semi-Analytic Functions to Calculate the Deposition Coefficients for Ice Crystal Vapor Growth in Bin and Bulk Microphysical Models.
复制标题
用于计算仓和体微物理模型中冰晶蒸气生长沉积系数的半解析函数。
DOI：
10.1175/jas-d-20-0307.1
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发表时间：
2021
影响因子：
3.1
通讯作者：
Morrison, Hugh
中科院分区：
文献类型：
--
作者：
Harrington, Jerry Y.;Sokolowsky, G. Alexander;Morrison, Hugh
数值云模型需要估计冰晶的蒸气生长速率。当前的体和料仓微物理参数化通常假设蒸气生长是扩散限制的，尽管一些参数化包括通过恒定沉积系数的表面附着动力学的影响。本文提供了可变沉积系数的参数化。参数化是环境冰过饱和度和温度的显式函数，以及晶体尺寸和压力的隐式函数。参数化对于可变表面类型有效，包括位错生长和逐步成核生长。预测晶体的两个主要生长方向的沉积系数，从而考虑到主要习性的演变。与瞬时质量增长基准计算的比较表明，参数化精确到相对误差在1%以内。使用拉格朗日微物理作为基准的包裹模型模拟表明，体参数化捕获了质量混合比和下落速度的演变，典型相对误差小于 10%，而平均轴长度的误差可能高达 20%。 bin 模型的准确度更高，相对误差通常小于 10%。如果提供等效体积球半径，则沉积系数参数化可用于任何体积和箱方案，且误差较低。
Numerical cloud models require estimates of the vapor growth rate for ice crystals. Current bulk and bin microphysical parameterizations generally assume that vapor growth is diffusion limited, though some parameterizations include the influence of surface attachment kinetics through a constant deposition coefficient. A parameterization for variable deposition coefficients is provided herein. The parameterization is an explicit function of the ambient ice supersaturation and temperature, and an implicit function of crystal dimensions and pressure. The parameterization is valid for variable surface types including growth by dislocations and growth by step nucleation. Deposition coefficients are predicted for the two primary growth directions of crystals, allowing for the evolution of the primary habits. Comparisons with benchmark calculations of instantaneous mass growth indicate that the parameterization is accurate to within a relative error of 1%. Parcel model simulations using Lagrangian microphysics as a benchmark indicate that the bulk parameterization captures the evolution of mass mixing ratio and fall speed with typical relative errors of less than 10%, whereas the average axis lengths can have errors of up to 20%. The bin model produces greater accuracy with relative errors often less than 10%. The deposition coefficient parameterization can be used in any bulk and bin scheme, with low error, if an equivalent volume spherical radius is provided.