Articles | Volume 19, issue 15
https://doi.org/10.5194/gmd-19-7069-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-7069-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sensitivity of Arctic mixed-phase cloud simulations to ice microphysical modifications in the WDM6 scheme of WRF (v4.3.1)
Hyun-Joon Sung
Division of Earth Environmental System Sciences (Major of Environmental Atmospheric Sciences), Pukyong National University, 45 Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea
Kyo-Sun Lim
School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea
Song-You Hong
Mesoscale and Microscale Meteorology Laboratory (MMM), National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA
JiHoon Shin
Division of Earth Environmental System Sciences (Major of Environmental Atmospheric Sciences), Pukyong National University, 45 Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea
Baek-Min Kim
CORRESPONDING AUTHOR
Division of Earth Environmental System Sciences (Major of Environmental Atmospheric Sciences), Pukyong National University, 45 Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea
Ji-Hun Choi
Division of Earth Environmental System Sciences (Major of Environmental Atmospheric Sciences), Pukyong National University, 45 Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea
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Soorok Ryu, Joon Jin Song, Kyo Sun Lim, and GyuWon Lee
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-302, https://doi.org/10.5194/essd-2026-302, 2026
Preprint under review for ESSD
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We developed a detailed rainfall dataset for South Korea by combining weather radar data with ground rain measurements. This dataset provides rainfall information every ten minutes at a very fine spatial scale from 2016 to 2024. We created it to better understand rainfall patterns and improve applications such as flood forecasting and water management. By combining the strengths of both data sources, the dataset offers more accurate and consistent rainfall information over time and space.
Joonghyun Jo, Kyo-Sun Sunny Lim, Sun-Young Park, Juhee Kwon, Wonbae Bang, Hyang Suk Park, Jae-Young Byon, Hyun-Suk Kang, and Gyuwon Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-4548, https://doi.org/10.5194/egusphere-2025-4548, 2026
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This study implements the generalized double-moment scaling normalization method for raindrop size distribution in the WDM6 microphysics scheme. Numerical experiments for a convective summer rainfall event show that the modified scheme better captures precipitation cell propagation, spatial rainfall distribution, and vertical reflectivity structures compared to the original WDM6 and other bulk/bin schemes.
Pierre Grzegorczyk, Wolfram Wobrock, Antoine Canzi, Frédéric Tridon, Gyuwon Lee, Kwonil Kim, Kyo-Sun Sunny Lim, and Céline Planche
EGUsphere, https://doi.org/10.5194/egusphere-2025-3202, https://doi.org/10.5194/egusphere-2025-3202, 2025
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This study evaluates the implementation of predicted rime mass distribution in the bin microphysics scheme DESCAM. Based on the ‘fill-in’ concept, the model allows a smooth transition between unrimed and graupel ice particle properties. The implementation is tested for a heavy snowfall event observed during the ICE-POP 2018 field campaign. The new version of DESCAM gives a better agreement with the observations with significant changes in the precipitation amount and spatial distribution.
Jeonggyu Kim, Sungmin Park, Greg M. McFarquhar, Anthony J. Baran, Joo Wan Cha, Kyoungmi Lee, Seoung Soo Lee, Chang Hoon Jung, Kyo-Sun Sunny Lim, and Junshik Um
Atmos. Chem. Phys., 24, 12707–12726, https://doi.org/10.5194/acp-24-12707-2024, https://doi.org/10.5194/acp-24-12707-2024, 2024
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We developed idealized models to represent the shapes of ice particles found in deep convective clouds and calculated their single-scattering properties. By comparing these results with in situ measurements, we discovered that a mixture of shape models matches in situ measurements more closely than single-form models or aggregate models. This finding has important implications for enhancing the simulation of single-scattering properties of ice crystals in deep convective clouds.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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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.
Jeong-Su Ko, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, Gregory Thompson, and Alexis Berne
Geosci. Model Dev., 15, 4529–4553, https://doi.org/10.5194/gmd-15-4529-2022, https://doi.org/10.5194/gmd-15-4529-2022, 2022
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This study evaluates the performance of the four microphysics parameterizations, the WDM6, WDM7, Thompson, and Morrison schemes, in simulating snowfall events during the ICE-POP 2018 field campaign. Eight snowfall events are selected and classified into three categories (cold-low, warm-low, and air–sea interaction cases). The evaluation focuses on the simulated hydrometeors, microphysics budgets, wind fields, and precipitation using the measurement data.
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Zhao, X., Liu, X., Phillips, V. T. J., and Patade, S.: Impacts of secondary ice production on Arctic mixed-phase clouds based on ARM observations and CAM6 single-column model simulations, Atmos. Chem. Phys., 21, 5685–5703, https://doi.org/10.5194/acp-21-5685-2021, 2021.
Short summary
Arctic clouds containing both liquid droplets and ice crystals are difficult to simulate. We tested how ice-related changes in a weather model, designed for temperate regions, perform in the Arctic. Ice crystal shape is the dominant factor: making crystals spherical substantially reduces cloud ice and shifts it to snow. These modifications are moderate in temperate regions but stronger in the Arctic. As this rests on a single case, they should be validated across diverse cases and climates.
Arctic clouds containing both liquid droplets and ice crystals are difficult to simulate. We...