59 citations as recorded by crossref.

1. 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
2. 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
3. Local-scale variability of snow density on Arctic sea ice J. King et al. https://doi.org/10.5194/tc-14-4323-2020
4. 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
5. The Scientific Legacy of NASA’s Operation IceBridge J. MacGregor et al. https://doi.org/10.1029/2020RG000712
6. 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
7. Version 1 of a sea ice module for the physics-based, detailed, multi-layer SNOWPACK model N. Wever et al. https://doi.org/10.5194/gmd-13-99-2020
8. 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
9. 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
10. Initial assessment of all-season Arctic sea ice thickness from ICESat-2 A. Petty et al. https://doi.org/10.1017/jog.2025.10119
11. 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
12. 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
13. 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
14. Retrieval of Snow Depth over Arctic Sea Ice Using a Deep Neural Network J. Liu et al. https://doi.org/10.3390/rs11232864
15. 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
16. Automated Calibration of a Snow‐On‐Sea‐Ice Model A. Cabaj et al. https://doi.org/10.1029/2022EA002655
17. 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
18. 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
19. Assessment of Satellite and Reanalysis Cold Season Snowfall Estimates Over Arctic Sea Ice Y. Song et al. https://doi.org/10.1029/2020GL088970
20. Evaluating Arctic Thin Ice Thickness Retrieved from Latest Version of Multisource Satellite Products H. Li et al. https://doi.org/10.3390/rs17101680
21. 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
22. Inter-comparisons of Arctic snow depth products M. Li et al. https://doi.org/10.1080/17538947.2024.2376286
23. 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
24. Advances in altimetric snow depth estimates using bi-frequency SARAL and CryoSat-2 Ka–Ku measurements F. Garnier et al. https://doi.org/10.5194/tc-15-5483-2021
25. 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
26. 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
27. 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
28. 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
29. 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
30. 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
31. 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
32. 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
33. 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
34. 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
35. 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
36. 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
37. 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
38. 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
39. 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
40. A multi-frequency altimetry snow depth product over Arctic sea ice A. Carret et al. https://doi.org/10.1038/s41597-024-04343-4
41. 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
42. 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
43. A Lagrangian Snow Evolution System for Sea Ice Applications (SnowModel‐LG): Part II—Analyses J. Stroeve et al. https://doi.org/10.1029/2019JC015900
44. 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
45. 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
46. Constraining CMIP6 sea ice simulations with ICESat-2 A. Petty et al. https://doi.org/10.5194/gmd-18-6313-2025
47. 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
48. 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
49. 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
50. Snowfall and snow accumulation during the MOSAiC winter and spring seasons D. Wagner et al. https://doi.org/10.5194/tc-16-2373-2022
51. 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
52. An Updated Assessment of the Changing Arctic Sea Ice Cover W. Meier & J. Stroeve https://doi.org/10.5670/oceanog.2022.114
53. 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
54. Meteorological effects on the Istok riometer cosmic noise measurements A. Oinats et al. https://doi.org/10.1016/j.asr.2026.04.113
55. Dye tracing of upward brine migration in snow R. Mallett et al. https://doi.org/10.1017/aog.2024.27
56. Arctic Ocean Precipitation From Atmospheric Reanalyses and Comparisons With North Pole Drifting Station Records A. Barrett et al. https://doi.org/10.1029/2019JC015415
57. 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
58. 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
59. 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