Assessing Raindrop Breakup Parameterizations Using Disdrometer Observations

Autor: Stephen M. Saleeby, Brenda Dolan, Jennie Bukowski, Kristen Van Valkenburg, Susan C. van den Heever, Steven A. Rutledge
Rok vydání: 2022
Předmět:
Zdroj: Journal of the Atmospheric Sciences. 79:2949-2963
ISSN: 1520-0469
0022-4928
Popis: An intercomparison of raindrop mean diameter frequency distribution (RDFD) is performed for numerical simulations of precipitating cloud systems using an array of models and microphysics schemes. This includes results from the Regional Atmospheric Modeling System (RAMS) double-moment microphysics, the Hebrew University Cloud Model bin microphysics (HUCM) interfaced to the RAMS parent model, and the Weather Research and Forecasting (WRF) Model with the Thompson, Morrison, double-moment 6-class (WDM6), and National Severe Storms Laboratory (NSSL) double-moment schemes. Simulations are examined with respect to the raindrop size distribution (DSD) volume-number mean diameter (Dm) and intercept parameter (Nw). When compared to a suite of disdrometer observations, the RDFD resulting from each microphysics scheme exhibits varying degrees of mean drop size constraints and peaks in the frequency distribution of Dm. A more detailed investigation of the peaked RDFD from the RAMS simulations suggests that the parameterization of raindrop collisional breakup can impose strong limitations on the evolution of simulated drop growth. As such, a summary and comparison of the drop breakup parameterizations among the aforementioned microphysics schemes is presented. While some drop breakup parameterizations are adjusted toward the observations by modifying the threshold diameter for the onset of breakup, this study explores the use of a modified maximum breakup efficiency. This method permits the parameterization to retain its threshold breakup diameter, while limiting the strength of drop breakup and permitting a broader range of drop sizes. As a result, the simulated mean drop sizes are in better agreement with observations.
Databáze: OpenAIRE
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