Articles | Volume 19, issue 17
https://doi.org/10.5194/gmd-19-8149-2026
© 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-19-8149-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
02 Sep 2026
Development and technical paper |
| 02 Sep 2026
| 02 Sep 2026
Implementation of the Generalized Double-Moment scaling Normalization method for raindrop size distribution in a WRF 4.3.1 bulk-type cloud microphysics scheme: a case study over the Korean Peninsula
Joonghyun Jo
National Institute of Meteorological Sciences, Korea Meteorological Administration, Seogwipo, Republic of Korea
Kyo Sun Lim
CORRESPONDING AUTHOR
School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea
Sun-Young Park
Climate Prediction Research Center, Seoul National University, Seoul, Republic of Korea
Juhee Kwon
School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea
Wonbae Bang
BK21 Weather Extremes Education & Research Team, Department of Atmospheric Sciences, Center for Atmospheric REmote sensing (CARE), Kyungpook National University, Daegu, Republic of Korea
HyangSuk Park
National Institute of Meteorological Sciences, Korea Meteorological Administration, Seogwipo, Republic of Korea
Jae-Young Byon
National Institute of Meteorological Sciences, Korea Meteorological Administration, Seogwipo, Republic of Korea
Gyuwon Lee
CORRESPONDING AUTHOR
BK21 Weather Extremes Education & Research Team, Department of Atmospheric Sciences, Center for Atmospheric REmote sensing (CARE), Kyungpook National University, Daegu, Republic of Korea
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Pierre Grzegorczyk, Wolfram Wobrock, Antoine Canzi, Frédéric Tridon, Sun-Young Park, Gyuwon Lee, Kwonil Kim, Kyo-Sun Lim, and Céline Planche
Geosci. Model Dev., 19, 8025–8051, https://doi.org/10.5194/gmd-19-8025-2026, https://doi.org/10.5194/gmd-19-8025-2026, 2026
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This study evaluates the implementation of predicted rime mass distribution a bin microphysics scheme. Based on the ‘fill-in’ concept, the model allows a smooth transition between unrimed and graupel ice particles. The implementation is tested for an idealized squall-line system and a heavy snowfall event observed by ground-based instruments in the Korean Peninsula. The new model version gives a better agreement with the observations with significant changes for precipitation.
Hyun-Joon Sung, Kyo-Sun Lim, Song-You Hong, JiHoon Shin, Baek-Min Kim, and Ji-Hun Choi
Geosci. Model Dev., 19, 7069–7088, https://doi.org/10.5194/gmd-19-7069-2026, https://doi.org/10.5194/gmd-19-7069-2026, 2026
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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.
Jong-Hoon Jeong, Seung Hee Kim, Su-Bin Oh, Jeong-Eun Lee, Chia-Lun Tasi, and Gyuwon Lee
EGUsphere, https://doi.org/10.5194/egusphere-2026-1878, https://doi.org/10.5194/egusphere-2026-1878, 2026
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This study examines why extreme rainfall can persist near coastal regions by analyzing a severe storm over western South Korea. Using advanced radar observations, we identify how interactions between airflow, precipitation processes, and coastal land–sea contrasts enhance storm organization. Our results show that these coupled processes play a critical role in sustaining heavy rainfall and support efforts to mitigate hazards in densely populated coastal areas.
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.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, and GyuWon Lee
Atmos. Meas. Tech., 18, 6371–6392, https://doi.org/10.5194/amt-18-6371-2025, https://doi.org/10.5194/amt-18-6371-2025, 2025
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The Wind Synthesis System using Doppler Measurements (WISSDOM) is a practical scheme to derive 3D winds by using 11 radars in this study. The observations of shot-wavelength radars can be attributed to lower level precipitation and wind information in WISSDOM, which allowed for the capture of stronger updrafts in the convection areas of the squall line. Overall, these results highlight the advantages of using radars with multiple wavelengths in WISSDOM, especially shot-wavelength radars.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
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.
Wei-Yu Chang, Yung-Chuan Yang, Chen-Yu Hung, Kwonil Kim, Gyuwon Lee, and Ali Tokay
Atmos. Chem. Phys., 24, 11955–11979, https://doi.org/10.5194/acp-24-11955-2024, https://doi.org/10.5194/acp-24-11955-2024, 2024
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Snow density is derived by collocated Micro-Rain Radar (MRR) and Parsivel (ICE-POP 2017/2018). We apply the particle size distribution from Parsivel to a T-matrix backscattering simulation and compare with ZHH from MRR. Bulk density and bulk water fractions are derived from comparing simulated and calculated ZHH. Retrieved bulk density is validated by comparing snowfall rate measurements from Pluvio and the Precipitation Imaging Package. Snowfall rate consistency confirms the algorithm.
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.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, and GyuWon Lee
Atmos. Meas. Tech., 16, 845–869, https://doi.org/10.5194/amt-16-845-2023, https://doi.org/10.5194/amt-16-845-2023, 2023
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Since the winds in clear-air conditions usually play an important role in the initiation of various weather systems and phenomena, the modified Wind Synthesis System using Doppler Measurements (WISSDOM) synthesis scheme was developed to derive high-quality and high-spatial-resolution 3D winds under clear-air conditions. The performance and accuracy of derived 3D winds from this modified scheme were evaluated with an extreme strong wind event over complex terrain in Pyeongchang, South Korea.
Xuanli Li, Jason B. Roberts, Jayanthi Srikishen, Jonathan L. Case, Walter A. Petersen, Gyuwon Lee, and Christopher R. Hain
Geosci. Model Dev., 15, 5287–5308, https://doi.org/10.5194/gmd-15-5287-2022, https://doi.org/10.5194/gmd-15-5287-2022, 2022
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This research assimilated the Global Precipitation Measurement (GPM) satellite-retrieved ocean surface meteorology data into the Weather Research and Forecasting (WRF) model with the Gridpoint Statistical Interpolation (GSI) system. This was for two snowstorms during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games' (ICE-POP 2018) field experiments. The results indicated a positive impact of the data for short-term forecasts for heavy snowfall.
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.
Ki-Hong Min, Kao-Shen Chung, Ji-Won Lee, Cheng-Rong You, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-18, https://doi.org/10.5194/gmd-2022-18, 2022
Revised manuscript not accepted
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LETKF underestimated the water vapor mixing ratio and temperature compared to 3DVAR due to a lack of a water vapor mixing ratio and temperature observation operator. Snowfall in GWD was less simulated in LETKF. The results signify that water vapor assimilation is important in radar DA and significantly impacts precipitation forecasts, regardless of the DA method used. Therefore, it is necessary to apply observation operators for water vapor mixing ratio and temperature in radar DA.
Paul Joe, Gyuwon Lee, and Kwonil Kim
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-620, https://doi.org/10.5194/acp-2021-620, 2021
Preprint withdrawn
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Strong gusty wind events were responsible for poor performance of competitors and schedule changes during the PyeongChang 2018 Olympic and Paralympic Winter Games. Three events were investigated and documented to articulate the challenges confronting forecasters which is beyond what they normally do. Quantitative evidence of the challenge and recommendations for future Olympics are provided.
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Short summary
This study improves rainfall simulation by applying the Generalized Double-moment scaling Normalization (GDMN) method to the rain Drop Size Distribution (DSD) in the Weather Research and Forecasting Double-Moment 6-class (WDM6) microphysics scheme. Using observed raindrop data, GDMN better represents variations in raindrop sizes. The modified WDM6 improves precipitation patterns, radar reflectivity, and storm movement, with benefits also demonstrated in a month-long East Asian simulation.
This study improves rainfall simulation by applying the Generalized Double-moment scaling...
