Preprints
https://doi.org/10.5194/gmd-2023-241
https://doi.org/10.5194/gmd-2023-241
Submitted as: development and technical paper
 | 
19 Mar 2024
Submitted as: development and technical paper |  | 19 Mar 2024
Status: a revised version of this preprint is currently under review for the journal GMD.

Introduction of Prognostic Graupel Density 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

Abstract. The Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) scheme was modified by incorporating prognostic graupel density. Explicitly prognosed graupel density, in turn, modifies graupel characteristics such as the fall velocity–diameter and mass–diameter relationships of graupel. The modified WDM6 has been evaluated based on a two-dimensional (2D) idealized squall line simulation and winter snowfall events that occurred during the International Collaborative Experiment for Pyeongchang Olympics and Paralympics (ICE-POP 2018) field campaign over the Korean Peninsula. From the 2D simulation, we confirmed that the modified WDM6 can simulate varying graupel density, ranging from low values in an anvil clouds region to high values in the convective region at the mature stage of a squall line. Simulations with the modified WDM6 increase graupel amounts at the surface and decreased graupel aloft because of the faster sedimentation of graupel for two winter snowfall cases during the ICE-POP 2018 campaign, as simulated in the 2D idealized model. The altered graupel sedimentation in the modified WDM6 influenced the magnitude of the major microphysical processes of graupel and snow, subsequently reducing the surface snow amount and precipitation over the mountainous region. The reduced surface precipitation over the mountainous region mitigates the surface precipitation bias observed in the original WDM6, resulting in better statistical skill scores for the root mean square errors. Notably, the modified WDM6 reasonably captures the relationship between graupel density and its fall velocity, as retrieved from 2D video disdrometer measurements, thus emphasizing the necessity of including prognostic graupel density to realistically represent the microphysical properties of graupel in models.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2023-241', Anonymous Referee #1, 25 Apr 2024
    • AC1: 'Reply on RC1', Kyo-Sun Lim, 18 Jun 2024
  • RC2: 'Comment on gmd-2023-241', Anonymous Referee #2, 02 May 2024
    • AC2: 'Reply on RC2', Kyo-Sun Lim, 18 Jun 2024
  • RC3: 'Comment on gmd-2023-241', Minghui Diao, 03 May 2024
    • AC3: 'Reply on RC3', Kyo-Sun Lim, 19 Jun 2024
  • AC4: 'Comment on gmd-2023-241', Kyo-Sun Lim, 19 Jun 2024
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt

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Short summary
Researchers enhance the WDM6 scheme by incorporating prognostic 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 prognostic graupel density for a more realistic portrayal of microphysical properties in weather models.