Semi-Analytic Functions to Calculate the Deposition Coefficients for Ice Crystal Vapor Growth in Bin and Bulk Microphysical Models

Journal Article · Mon May 10 04:00:00 EDT 2021 · Journal of the Atmospheric Sciences

DOI:https://doi.org/10.1175/jas-d-20-0307.1· OSTI ID:1784523

Harrington, Jerry Y. ^[1]; Sokolowsky, G. Alexander ^[2]; Morrison, Hugh ^[3]

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1. Pennsylvania State Univ., University Park, PA (United States)
2. Colorado State Univ., Fort Collins, CO (United States)
3. National Center for Atmospheric Research, Boulder, CO (United States)

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 that 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.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF)
• Contributing Organization: PNNL, BNL, ANL, ORNL
• Grant/Contract Number: SC0021001; SC0012827
• OSTI ID: 1784523
• Journal Information: Journal of the Atmospheric Sciences, Journal Name: Journal of the Atmospheric Sciences Journal Issue: 5 Vol. 78; ISSN 0022-4928
• Publisher: American Meteorological Society
• Country of Publication: United States
• Language: English

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