Development of a Snow Growth Model for Rimed Snowfall

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Authors

Ehsan Erfani, David Mitchell

Abstract

A snow growth model for rimed snowfall (SGMR) was developed based on the growth processes of vapor deposition, aggregation, and riming. The SGMR is initialized by radar reflectivity (Z) at the cloud top and thereafter simulates the vertical evolution of size spectra. The SGMR is based on the zeroth- and second-moment conservation equations with respect to mass, and thus conserves the number concentration and Z, respectively. New mass- and area-dimension expressions suitable for synoptic clouds are utilized in the model, and therefore the assumption of specific ice particle shapes is not required. In addition, the new approach to parameterizing riming has the advantage of a smooth and gradual growth of mass and area by riming. In general, the processes of vapor deposition and aggregation lead to larger ice particles that fall faster and therefore, produce a larger snowfall rate (rs). The rs and ice water content with the inclusion of riming are significantly greater than that produced by the vapor deposition and aggregation alone. Moreover, rs is sensitive to the cloud drop size distribution. The size spectra predicted by the SGMR were compared with those from two cases of Lagrangian spiral descent through frontal and cirrus clouds, and good agreement is seen between the vertical profiles of SGMR and observations. This analytical SGMR, due to its accuracy and short running time, can be used in climate models and remote sensing.

DOI

https://doi.org/10.31223/X5QM51

Subjects

Earth Sciences, Physical Sciences and Mathematics

Keywords

ice cloud microphysics, cloud modeling, snow growth model, mixed-phase clouds, aggregation, vapor deposition, riming, particle size distribution

Dates

Published: 2024-04-04 00:08

Last Updated: 2024-04-04 07:08

License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International

Additional Metadata

Conflict of interest statement:
None