Articles | Volume 15, issue 13
https://doi.org/10.5194/gmd-15-5287-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-15-5287-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
12 Jul 2022
Development and technical paper |
| 12 Jul 2022
| 12 Jul 2022
Assimilation of GPM-retrieved ocean surface meteorology data for two snowstorm events during ICE-POP 2018
Xuanli Li
CORRESPONDING AUTHOR
Earth System Science Center, University of Alabama in Huntsville, Huntsville, Alabama, USA
Jason B. Roberts
NASA Marshall Space Flight Center, Huntsville, Alabama, USA
Jayanthi Srikishen
Science and Technology Institute, Universities Space Research Association, Huntsville, Alabama, USA
Jonathan L. Case
ENSCO, Inc./NASA SPoRT Center, Huntsville, Alabama, USA
Walter A. Petersen
NASA Marshall Space Flight Center, Huntsville, Alabama, USA
Gyuwon Lee
Department of Astronomy and Atmospheric Sciences, Center for Atmospheric REmote sensing (CARE), Kyungpook National University, Daegu, Republic of Korea
Christopher R. Hain
NASA Marshall Space Flight Center, Huntsville, Alabama, USA
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Joonghyun Jo, Kyo Sun Lim, Sun-Young Park, Juhee Kwon, Wonbae Bang, HyangSuk Park, Jae-Young Byon, and Gyuwon Lee
Geosci. Model Dev., 19, 8149–8166, https://doi.org/10.5194/gmd-19-8149-2026, https://doi.org/10.5194/gmd-19-8149-2026, 2026
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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.
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.
Sadegh Ranjbar, Danielle Losos, Sophie Hoffman, Yafang Zhong, Jason A. Otkin, Ankur R. Desai, Martha C. Anderson, Christopher R. Hain, and Paul C. Stoy
Hydrol. Earth Syst. Sci., 30, 4927–4955, https://doi.org/10.5194/hess-30-4927-2026, https://doi.org/10.5194/hess-30-4927-2026, 2026
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Water moves from land to air in a process called evapotranspiration, which affects weather, crops, and water supply. Using satellites and AI, we created a system that tracks this water movement every five minutes, day and night, even through clouds. This provides continuous insights that can help manage water, predict weather, and better understand the water cycle.
Yun Yang, Martha Anderson, Charles Morton, Yanghui Kang, Feng Gao, Weina Duan, Hui Liu, John Volk, and Christopher Hain
Geosci. Model Dev., 19, 6967–6989, https://doi.org/10.5194/gmd-19-6967-2026, https://doi.org/10.5194/gmd-19-6967-2026, 2026
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Evapotranspiration (ET) describes the transfer of water from land to the atmosphere and is fundamental to understanding agriculture, ecosystems, and drought. We implemented the established DisALEXI model on Google Earth Engine (GEE-DisALEXI), enabling scalable, high-resolution ET mapping over large regions. This paper evaluates this version's accuracy, highlights example applications, discusses limitations, and outlines opportunities for future improvements.
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.
Franklin Robertson, Michael Bosilovich, Matthew Rodell, Richard Allan, Bryant Loomis, Hiroko Beaudoing, Joaquin Munoz-Sabater, and Jason Roberts
EGUsphere, https://doi.org/10.5194/egusphere-2026-2539, https://doi.org/10.5194/egusphere-2026-2539, 2026
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Water availability for societies and ecosystems depends upon Terrestrial Water Storage (TWS). By exploiting Gravity Recovery and Climate Experiment gravimetric measurements and TWS reconstructions from reanalysis, global hydrologic modeling and machine learning approaches, we provide evidence that previously documented TWS decline since 2002 extends back to the 1980s and is explained by coincident decline in regional precipitation combined with a growing influence of human water management.
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.
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
Short summary
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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.
R. Bradley Pierce, Monica Harkey, Allen Lenzen, Lee M. Cronce, Jason A. Otkin, Jonathan L. Case, David S. Henderson, Zac Adelman, Tsengel Nergui, and Christopher R. Hain
Atmos. Chem. Phys., 23, 9613–9635, https://doi.org/10.5194/acp-23-9613-2023, https://doi.org/10.5194/acp-23-9613-2023, 2023
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We evaluate two high-resolution model simulations with different meteorological inputs but identical chemistry and anthropogenic emissions, with the goal of identifying a model configuration best suited for characterizing air quality in locations where lake breezes commonly affect local air quality along the Lake Michigan shoreline. This analysis complements other studies in evaluating the impact of meteorological inputs and parameterizations on air quality in a complex environment.
Jason A. Otkin, Lee M. Cronce, Jonathan L. Case, R. Bradley Pierce, Monica Harkey, Allen Lenzen, David S. Henderson, Zac Adelman, Tsengel Nergui, and Christopher R. Hain
Atmos. Chem. Phys., 23, 7935–7954, https://doi.org/10.5194/acp-23-7935-2023, https://doi.org/10.5194/acp-23-7935-2023, 2023
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We performed model simulations to assess the impact of different parameterization schemes, surface initialization datasets, and analysis nudging on lower-tropospheric conditions near Lake Michigan. Simulations were run with high-resolution, real-time datasets depicting lake surface temperatures, green vegetation fraction, and soil moisture. The most accurate results were obtained when using high-resolution sea surface temperature and soil datasets to constrain the model simulations.
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
Short summary
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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.
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
Short summary
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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
Short summary
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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
Short summary
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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 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.
This research assimilated the Global Precipitation Measurement (GPM) satellite-retrieved ocean...
