Articles | Volume 17, issue 18
https://doi.org/10.5194/gmd-17-7199-2024
https://doi.org/10.5194/gmd-17-7199-2024
Development and technical paper
 | 
27 Sep 2024
Development and technical paper |  | 27 Sep 2024

Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign

Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt

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Cited articles

Adams-Selin, R. D., van den Heever, S. C. and Johnson, R. H.: Impact of Graupel Parameterization Schemes on Idealized Bow Echo Simulations, Mon. Weather Rev., 141, 1241–1262, https://doi.org/10.1175/MWR-D-12-00064.1, 2013. 
Bae, S. Y., Hong, S. Y., and Tao, W. K.: Development of a single-moment cloud microphysics scheme with prognostic hail for the Weather Research and Forecasting (WRF) model, Asia-Pac. J. Atmos. Sci., 55, 233–245, https://doi.org/10.1007/s13143-018-0066-3, 2019. 
Böhm, H. P.: A General Equation for the Terminal Fall Speed of Solid Hydrometeors, J. Atmos. Sci., 46, 2419–2427, https://doi.org/10.1175/1520-0469(1989)046<2419:AGEFTT>2.0.CO;2, 1989. 
Bryan, G. H. and Morrison, H.: Sensitivity of a Simulated Squall Line to Horizontal Resolution and Parameterization of Microphysics, Mon. Weather Rev., 140, 202–225, https://doi.org/10.1175/MWR-D-11-00046.1, 2012. 
Chen, F. and Dudhia, J.: Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity, Mon. Weather Rev., 129, 569–585, https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001. 
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Short summary
We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.