Articles | Volume 11, issue 11
https://doi.org/10.5194/gmd-11-4577-2018
© Author(s) 2018. 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-11-4577-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
16 Nov 2018
Model description paper |
| 16 Nov 2018
| 16 Nov 2018
The NASA Eulerian Snow on Sea Ice Model (NESOSIM) v1.0: initial model development and analysis
Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
Melinda Webster
Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Linette Boisvert
Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
Thorsten Markus
Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
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57 citations as recorded by crossref.
- Impact assessment of snow thickness, sea ice density and water density in CryoSat-2-derived sea ice thickness I. Sievers et al. https://doi.org/10.5194/tc-18-5985-2024
- AdaSA-SD (v1.0): An Adaptive Seasonal Algorithm for Snow Depth Retrieval Over Arctic Sea Ice Y. Zhou et al. https://doi.org/10.1109/TGRS.2025.3593433
- Local-scale variability of snow density on Arctic sea ice J. King et al. https://doi.org/10.5194/tc-14-4323-2020
- Impacts of a layered snow density evolution scheme on Arctic snow and sea ice simulation in the CICE sea ice model H. Yin et al. https://doi.org/10.1016/j.ocemod.2025.102640
- The Scientific Legacy of NASA’s Operation IceBridge J. MacGregor et al. https://doi.org/10.1029/2020RG000712
- Reconstructing Long-Term Arctic Sea Ice Freeboard, Thickness, and Volume Changes from Envisat, CryoSat-2, and ICESat-2 Y. Zhang et al. https://doi.org/10.3390/jmse11050979
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- Toward improved sea ice freeboard observation with SAR altimetry using the physical retracker SAMOSA+ A. Laforge et al. https://doi.org/10.1016/j.asr.2020.02.001
- Faster decline and higher variability in the sea ice thickness of the marginal Arctic seas when accounting for dynamic snow cover R. Mallett et al. https://doi.org/10.5194/tc-15-2429-2021
- Sea Ice Remote Sensing—Recent Developments in Methods and Climate Data Sets S. Sandven et al. https://doi.org/10.1007/s10712-023-09781-0
- Arctic Snow Depth and Sea Ice Thickness From ICESat‐2 and CryoSat‐2 Freeboards: A First Examination R. Kwok et al. https://doi.org/10.1029/2019JC016008
- Winter Snow Depth on Arctic Sea Ice From Satellite Radiometer Measurements (2003–2020): Regional Patterns and Trends S. Lee et al. https://doi.org/10.1029/2021GL094541
- Retrieval of Snow Depth over Arctic Sea Ice Using a Deep Neural Network J. Liu et al. https://doi.org/10.3390/rs11232864
- Impacts of snow data and processing methods on the interpretation of long-term changes in Baffin Bay early spring sea ice thickness I. Glissenaar et al. https://doi.org/10.5194/tc-15-4909-2021
- Automated Calibration of a Snow‐On‐Sea‐Ice Model A. Cabaj et al. https://doi.org/10.1029/2022EA002655
- Effects of Increasing the Category Resolution of the Sea Ice Thickness Distribution in a Coupled Climate Model on Arctic and Antarctic Sea Ice Mean State M. Smith et al. https://doi.org/10.1029/2022JC019044
- Sub-kilometre scale distribution of snow depth on Arctic sea ice from Soviet drifting stations R. Mallett et al. https://doi.org/10.1017/jog.2022.18
- Assessment of Satellite and Reanalysis Cold Season Snowfall Estimates Over Arctic Sea Ice Y. Song et al. https://doi.org/10.1029/2020GL088970
- Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products H. Li et al. https://doi.org/10.3390/rs17101680
- Evaluating the impact of blowing-snow sea salt aerosol on springtime BrO and O3 in the Arctic J. Huang et al. https://doi.org/10.5194/acp-20-7335-2020
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- Improving snow depth simulations on Arctic Sea ice by assimilating a passive microwave-derived record H. Li et al. https://doi.org/10.1016/j.coldregions.2023.103929
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- A decade-plus of Antarctic sea ice thickness and volume estimates from CryoSat-2 using a physical model and waveform fitting S. Fons et al. https://doi.org/10.5194/tc-17-2487-2023
- Arctic Sea Ice Thickness Estimation From Passive Microwave Satellite Observations Between 1.4 and 36 GHz C. Soriot et al. https://doi.org/10.1029/2022EA002542
- Implementation of an intermediate-complexity snow-physics scheme (ISBA-Explicit Snow) into a sea ice model (SI3): 1D thermodynamic coupling and validation T. Brivoal et al. https://doi.org/10.5194/gmd-18-6885-2025
- Combining observational data and numerical models to obtain a seamless high-temporal-resolution seasonal cycle of snow and ice mass balance at the MOSAiC Central Observatory P. Itkin & G. Liston https://doi.org/10.5194/tc-19-5111-2025
- Estimating Early Summer Snow Depth on Sea Ice Using a Radiative Transfer Model and Optical Satellite Data M. Wang & N. Oppelt https://doi.org/10.3390/rs15205016
- Investigating the impact of reanalysis snow input on an observationally calibrated snow-on-sea-ice reconstruction A. Cabaj et al. https://doi.org/10.5194/tc-19-3033-2025
- Snow Loss Into Leads in Arctic Sea Ice: Minimal in Typical Wintertime Conditions, but High During a Warm and Windy Snowfall Event D. Clemens‐Sewall et al. https://doi.org/10.1029/2023GL102816
- Toward Daily Snow Depth Estimation on Arctic Sea Ice During the Whole Winter Season From Passive Microwave Radiometer Data L. He et al. https://doi.org/10.1109/TGRS.2024.3358340
- Brief communication: Conventional assumptions involving the speed of radar waves in snow introduce systematic underestimates to sea ice thickness and seasonal growth rate estimates R. Mallett et al. https://doi.org/10.5194/tc-14-251-2020
- Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval L. Zhou et al. https://doi.org/10.5194/tc-15-345-2021
- A combined multi-source data and deep learning approach for retrieving snow depth on Antarctic Sea ice during the melting season Z. Yan et al. https://doi.org/10.1080/17538947.2024.2376260
- A deep learning approach to retrieve cold-season snow depth over Arctic sea ice from AMSR2 measurements H. Li et al. https://doi.org/10.1016/j.rse.2021.112840
- Investigating snow sinks on level sea ice: A case study in the western Arctic I. Merkouriadi et al. https://doi.org/10.1017/jog.2025.34
- Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean Y. Nie et al. https://doi.org/10.5194/gmd-16-1395-2023
- Two Decades of Arctic Sea-Ice Thickness from Satellite Altimeters: Retrieval Approaches and Record of Changes (2003–2023) S. Kacimi & R. Kwok https://doi.org/10.3390/rs16162983
- A multi-frequency altimetry snow depth product over Arctic sea ice A. Carret et al. https://doi.org/10.1038/s41597-024-04343-4
- A Sea Ice Concentration Estimation Methodology Utilizing ICESat-2 Photon-Counting Laser Altimeter in the Arctic J. Liu et al. https://doi.org/10.3390/rs14051130
- A Simulation of Snow on Antarctic Sea Ice Based on Satellite Data and Climate Reanalyses I. Lawrence et al. https://doi.org/10.1029/2022JC019002
- A Lagrangian Snow Evolution System for Sea Ice Applications (SnowModel‐LG): Part II—Analyses J. Stroeve et al. https://doi.org/10.1029/2019JC015900
- A Multi-Sensor and Modeling Approach for Mapping Light Under Sea Ice During the Ice-Growth Season J. Stroeve et al. https://doi.org/10.3389/fmars.2020.592337
- An improved optical flow method to estimate Arctic sea ice velocity (winter 2014–2016) H. Li et al. https://doi.org/10.1007/s13131-021-1867-2
- Constraining CMIP6 sea ice simulations with ICESat-2 A. Petty et al. https://doi.org/10.5194/gmd-18-6313-2025
- A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description G. Liston et al. https://doi.org/10.1029/2019JC015913
- Suppression of Arctic Sea Ice Growth in the Eurasian–Pacific Seas by Winter Clouds and Snowfall W. Lim et al. https://doi.org/10.1175/JCLI-D-21-0282.1
- Assessment of radar freeboard, radar penetration rate, and snow depth for potential improvements in Arctic sea ice thickness retrieved from CryoSat-2 Y. Zhou et al. https://doi.org/10.1016/j.coldregions.2024.104408
- Snowfall and snow accumulation during the MOSAiC winter and spring seasons D. Wagner et al. https://doi.org/10.5194/tc-16-2373-2022
- Winter Arctic sea ice thickness from ICESat-2: upgrades to freeboard and snow loading estimates and an assessment of the first three winters of data collection A. Petty et al. https://doi.org/10.5194/tc-17-127-2023
- Estimation of Arctic Winter Snow Depth, Sea Ice Thickness and Bulk Density, and Ice Freeboard by Combining CryoSat-2, AVHRR, and AMSR Measurements H. Shi et al. https://doi.org/10.1109/TGRS.2023.3265274
- Meteorological effects on the Istok riometer cosmic noise measurements A. Oinats et al. https://doi.org/10.1016/j.asr.2026.04.113
- Dye tracing of upward brine migration in snow R. Mallett et al. https://doi.org/10.1017/aog.2024.27
- Arctic Ocean Precipitation From Atmospheric Reanalyses and Comparisons With North Pole Drifting Station Records A. Barrett et al. https://doi.org/10.1029/2019JC015415
- A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition A. Macfarlane et al. https://doi.org/10.1038/s41597-023-02273-1
- Sensitivity of Passive Microwave Satellite Observations to Snow Density and Grain Size Over Arctic Sea Ice Y. Kwon et al. https://doi.org/10.1109/TGRS.2023.3322401
- Spatially distributed simulations of the effect of snow on mass balance and flooding of Antarctic sea ice N. Wever et al. https://doi.org/10.1017/jog.2021.54
Saved (final revised paper)
Latest update: 03 Jun 2026
