Articles | Volume 19, issue 3
https://doi.org/10.5194/gmd-19-1261-2026
© 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-19-1261-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
11 Feb 2026
Model evaluation paper |
| 11 Feb 2026
| 11 Feb 2026
Implementation of a multi-layer snow scheme in the GloSea6 seasonal forecast system: impacts on land–atmosphere interactions and climatological biases
Eunkyo Seo
CORRESPONDING AUTHOR
Department of Environmental Atmospheric Sciences, Pukyong National University, Busan, 48513, Republic of Korea
Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, Virginia, 22030, USA
Paul A. Dirmeyer
Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, Virginia, 22030, USA
Sunlae Tak
Department of Civil, Urban, Earth, and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea
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This study developed a system that assimilates multi-sensor into a land surface model to obtain accurate soil moisture globally. Combining multiple satellites provides wider spatial coverage than a single satellite, which directly improves accuracy across sub-daily and daily time scales. Our system performs better by using individual satellites rather than pre-mixed data. Expanding our view with multiple satellites leads to much more accurate and reliable soil moisture.
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Soil moisture sensors can be distorted by daytime heating, creating false diurnal rises when soils are actually drying. We developed a Long Short-Term Memory network that learns realistic diurnal cycles from observations and land surface models and uses them to correct these false signals. The corrected records more clearly show daytime soil drying and improve our understanding of how water in the soil influences heat and moisture exchange between the land and atmosphere.
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This study developed a system that assimilates multi-sensor into a land surface model to obtain accurate soil moisture globally. Combining multiple satellites provides wider spatial coverage than a single satellite, which directly improves accuracy across sub-daily and daily time scales. Our system performs better by using individual satellites rather than pre-mixed data. Expanding our view with multiple satellites leads to much more accurate and reliable soil moisture.
Eunkyo Seo, Seongjun Bae, Junnyeong Han, Cheolhee Yoo, and Paul A. Dirmeyer
EGUsphere, https://doi.org/10.5194/egusphere-2026-3001, https://doi.org/10.5194/egusphere-2026-3001, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
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Soil moisture sensors can be distorted by daytime heating, creating false diurnal rises when soils are actually drying. We developed a Long Short-Term Memory network that learns realistic diurnal cycles from observations and land surface models and uses them to correct these false signals. The corrected records more clearly show daytime soil drying and improve our understanding of how water in the soil influences heat and moisture exchange between the land and atmosphere.
Gyuyeon Choi, Eunkyo Seo, and Paul A. Dirmeyer
EGUsphere, https://doi.org/10.5194/egusphere-2026-2867, https://doi.org/10.5194/egusphere-2026-2867, 2026
Short summary
Short summary
This study evaluates five satellite and four reanalysis products against 6,824 ground-based observations for diurnal cycle fidelity. Satellites show a 1 to 2 hour phase delay from upper-level ice detection, while reanalyses peak 3 to 6 hours early from premature convective onset. Contrasting performances are linked to specific design choices in retrieval algorithms and convective parameterization, offering physically grounded guidance for dataset selection in hydrological and climate studies.
Junnyeong Han, Eunkyo Seo, and Paul A. Dirmeyer
Hydrol. Earth Syst. Sci., 30, 2207–2223, https://doi.org/10.5194/hess-30-2207-2026, https://doi.org/10.5194/hess-30-2207-2026, 2026
Short summary
Short summary
Soil moisture sensors often exhibit misleading daytime peaks because they are sensitive to temperature. This study proposes a method to correct the spurious diurnal cycle of surface soil moisture, using Fourier analysis with land reanalyses. The diurnally adjusted time series better captures realistic soil moisture behavior and provides more reliable insight into land–atmosphere interactions on a diurnal timescale.
Iris Mužić, Øivind Hodnebrog, Yeliz A. Yilmaz, Terje K. Berntsen, Jana Sillmann, David M. Lawrence, and Paul A. Dirmeyer
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Joonlee Lee, Myong-In Lee, Sunlae Tak, Eunkyo Seo, and Yong-Keun Lee
Geosci. Model Dev., 17, 8799–8816, https://doi.org/10.5194/gmd-17-8799-2024, https://doi.org/10.5194/gmd-17-8799-2024, 2024
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We developed an advanced snow water equivalent (SWE) data assimilation framework using satellite data based on a land surface model. The results of this study highlight the beneficial impact of data assimilation by effectively combining land surface model and satellite-derived data according to their relative uncertainty, thereby controlling not only transitional regions but also the regions with heavy snow accumulation that are difficult to detect by satellite.
Gaoyun Wang, Rong Fu, Yizhou Zhuang, Paul A. Dirmeyer, Joseph A. Santanello, Guiling Wang, Kun Yang, and Kaighin McColl
Atmos. Chem. Phys., 24, 3857–3868, https://doi.org/10.5194/acp-24-3857-2024, https://doi.org/10.5194/acp-24-3857-2024, 2024
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This study investigates the influence of lower-tropospheric humidity on land–atmosphere coupling (LAC) during warm seasons in the US Southern Great Plains. Using radiosonde data and a buoyancy model, we find that elevated LT humidity is crucial for generating afternoon precipitation events under dry soil conditions not accounted for by conventional LAC indices. This underscores the importance of considering LT humidity in understanding LAC over dry soil during droughts in the SGP.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
Short summary
Short summary
We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Zun Yin, Kirsten L. Findell, Paul Dirmeyer, Elena Shevliakova, Sergey Malyshev, Khaled Ghannam, Nina Raoult, and Zhihong Tan
Hydrol. Earth Syst. Sci., 27, 861–872, https://doi.org/10.5194/hess-27-861-2023, https://doi.org/10.5194/hess-27-861-2023, 2023
Short summary
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Land–atmosphere (L–A) interactions typically focus on daytime processes connecting the land state with the overlying atmospheric boundary layer. However, much prior L–A work used monthly or daily means due to the lack of daytime-only data products. Here we show that monthly smoothing can significantly obscure the L–A coupling signal, and including nighttime information can mute or mask the daytime processes of interest. We propose diagnosing L–A coupling within models or archiving subdaily data.
Eunkyo Seo and Paul A. Dirmeyer
Hydrol. Earth Syst. Sci., 26, 5411–5429, https://doi.org/10.5194/hess-26-5411-2022, https://doi.org/10.5194/hess-26-5411-2022, 2022
Short summary
Short summary
This study presents the climatology of the observed land–atmosphere interactions on a subdaily timescale during the warm season from flux site observations. Multivariate metrics are employed to examine the land, atmosphere, and combined couplings, and a mixing diagram is adopted to understand the coevolution of the moist and thermal energy budget within the atmospheric mixed layer. The diurnal cycles of both mixing diagrams and hourly land–atmosphere couplings exhibit hysteresis.
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Short summary
This study examines a multi-layer snow scheme in seasonal forecasts. Compared to a single-layer scheme, it better captures snow insulation, delaying spring snowmelt by 1–2 weeks. This postpones evaporation and slows soil moisture depletion, which promotes evaporative cooling due to increasing energy partitioning into latent heat flux and enhances precipitation occurrence. This leads to realistic land-atmosphere interactions and reduced biases across Northern Hemisphere mid- and high-latitudes.
This study examines a multi-layer snow scheme in seasonal forecasts. Compared to a single-layer...
