67 citations as recorded by crossref.

1. On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data L. Zhou et al. https://doi.org/10.5194/tc-12-993-2018
2. Assessment with Controlled In-Situ Data of the Dependence of L-Band Radiometry on Sea-Ice Thickness P. Sánchez-Gámez et al. https://doi.org/10.3390/rs12040650
3. Simultaneous estimation of wintertime sea ice thickness and snow depth from space-borne freeboard measurements H. Shi et al. https://doi.org/10.5194/tc-14-3761-2020
4. Triple Collocation-Based Merging of Winter Snow Depth Retrievals on Arctic Sea Ice Derived From Three Different Algorithms Using AMSR2 L. He et al. https://doi.org/10.1109/TGRS.2023.3290073
5. Snow thickness retrieval from L-band brightness temperatures: a model comparison N. Maass et al. https://doi.org/10.3189/2015AoG69A886
6. 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
7. Regional distribution and variability of model-simulated Arctic snow on sea ice K. Castro-Morales et al. https://doi.org/10.1016/j.polar.2017.05.003
8. Effects of decimetre-scale surface roughness on L-band brightness temperature of sea ice M. Miernecki et al. https://doi.org/10.5194/tc-14-461-2020
9. Thin Sea Ice, Thick Snow, and Widespread Negative Freeboard Observed During N‐ICE2015 North of Svalbard A. Rösel et al. https://doi.org/10.1002/2017JC012865
10. Space‐Based Observations for Understanding Changes in the Arctic‐Boreal Zone B. Duncan et al. https://doi.org/10.1029/2019RG000652
11. Reconstructing Pre-SMAP Archives of Polarized Brightness Temperatures in Arctic Sea Ice Leveraging ResNet-Based Conditional GANs S. Jo et al. https://doi.org/10.1109/TGRS.2025.3645345
12. 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
13. Potential for estimation of snow depth on Arctic sea ice from CryoSat-2 and SARAL/AltiKa missions K. Guerreiro et al. https://doi.org/10.1016/j.rse.2016.07.013
14. Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean–sea ice modelling system S. Fritzner et al. https://doi.org/10.5194/tc-13-491-2019
15. Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme M. Mäkynen et al. https://doi.org/10.3390/rs12071214
16. An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data L. He et al. https://doi.org/10.1007/s13131-023-2280-9
17. ESA's Soil Moisture and Ocean Salinity mission: From science to operational applications S. Mecklenburg et al. https://doi.org/10.1016/j.rse.2015.12.025
18. Essential gaps and uncertainties in the understanding of the roles and functions of Arctic sea ice S. Gerland et al. https://doi.org/10.1088/1748-9326/ab09b3
19. Retrieval of Snow Depth on Arctic Sea Ice from the FY3B/MWRI L. Li et al. https://doi.org/10.3390/rs13081457
20. X- and Ku-Band SAR Backscattering Signatures of Snow-Covered Lake Ice and Sea Ice K. Veijola et al. https://doi.org/10.3390/rs16020369
21. 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
22. Exploring non-Gaussian sea ice characteristics via observing system simulation experiments C. Riedel & J. Anderson https://doi.org/10.5194/tc-18-2875-2024
23. Estimation of Arctic Basin-Scale Sea Ice Thickness From Satellite Passive Microwave Measurements S. Lee et al. https://doi.org/10.1109/TGRS.2020.3026949
24. MOSAiC drift expedition from October 2019 to July 2020: sea ice conditions from space and comparison with previous years T. Krumpen et al. https://doi.org/10.5194/tc-15-3897-2021
25. An RFI-suppressed SMOS L-band multi-angular brightness temperature dataset spanning over a decade (since 2010) Z. Peng et al. https://doi.org/10.1038/s41597-023-02499-z
26. Assessment of contemporary satellite sea ice thickness products for Arctic sea ice H. Sallila et al. https://doi.org/10.5194/tc-13-1187-2019
27. Inter-comparisons of Arctic snow depth products M. Li et al. https://doi.org/10.1080/17538947.2024.2376286
28. Estimating snow depth on Arctic sea ice using satellite microwave radiometry and a neural network A. Braakmann-Folgmann & C. Donlon https://doi.org/10.5194/tc-13-2421-2019
29. A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications A. Schmitt & L. Kaleschke https://doi.org/10.3390/rs10040553
30. 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
31. Weekly gridded Aquarius L-band radiometer/scatterometer observations and salinity retrievals over the polar regions – Part 2: Initial product analysis L. Brucker et al. https://doi.org/10.5194/tc-8-915-2014
32. New insight from CryoSat-2 sea ice thickness for sea ice modelling D. Schröder et al. https://doi.org/10.5194/tc-13-125-2019
33. An Attempt to Improve Snow Depth Retrieval Using Satellite Microwave Radiometry for Rough Antarctic Sea Ice S. Kern & B. Ozsoy https://doi.org/10.3390/rs11192323
34. The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise S. Kern et al. https://doi.org/10.5194/tc-9-37-2015
35. Microwave Radiometry at Frequencies From 500 to 1400 MHz: An Emerging Technology for Earth Observations J. Johnson et al. https://doi.org/10.1109/JSTARS.2021.3073286
36. Retrieval of Snow Depth over Arctic Sea Ice Using a Deep Neural Network J. Liu et al. https://doi.org/10.3390/rs11232864
37. Theoretical study of ice cover phenology at large freshwater lakes based on SMOS MIRAS data V. Tikhonov et al. https://doi.org/10.5194/tc-12-2727-2018
38. Predicting Melt Pond Fraction on Landfast Snow Covered First Year Sea Ice from Winter C-Band SAR Backscatter Utilizing Linear, Polarimetric and Texture Parameters S. Ramjan et al. https://doi.org/10.3390/rs10101603
39. Measurements of 540–1740 MHz Brightness Temperatures of Sea Ice During the Winter of the MOSAiC Campaign O. Demir et al. https://doi.org/10.1109/TGRS.2021.3105360
40. On the retrieval of sea-ice thickness using SMOS polarization differences M. GUPTA et al. https://doi.org/10.1017/jog.2019.26
41. Sea Ice Thickness Estimation Based on Regression Neural Networks Using L-Band Microwave Radiometry Data from the FSSCat Mission C. Herbert et al. https://doi.org/10.3390/rs13071366
42. On the Synergy of SMAP and AMSR2 for Estimating Snow Depth on Arctic Sea Ice L. He et al. https://doi.org/10.1109/LGRS.2022.3188001
43. Improving L-band radiation model and representation of small-scale variability to simulate brightness temperature of sea ice L. Zhou et al. https://doi.org/10.1080/01431161.2017.1371862
44. High-Resolution Snow Depth on Arctic Sea Ice From Low-Altitude Airborne Microwave Radar Data A. Jutila et al. https://doi.org/10.1109/TGRS.2021.3063756
45. Uncertainties in Arctic sea ice thickness and volume: new estimates and implications for trends M. Zygmuntowska et al. https://doi.org/10.5194/tc-8-705-2014
46. Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea N. Maaß et al. https://doi.org/10.3402/tellusa.v67.24617
47. The Scientific Legacy of NASA’s Operation IceBridge J. MacGregor et al. https://doi.org/10.1029/2020RG000712
48. Data Synergy between Altimetry and L-Band Passive Microwave Remote Sensing for the Retrieval of Sea Ice Parameters—A Theoretical Study of Methodology S. Xu et al. https://doi.org/10.3390/rs9101079
49. Assimilation of SMOS sea ice thickness in the regional ice prediction system M. Gupta et al. https://doi.org/10.1080/01431161.2021.1897183
50. Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance J. Yackel et al. https://doi.org/10.3390/rs11040417
51. Towards reliable Arctic sea ice prediction using multivariate data assimilation J. Liu et al. https://doi.org/10.1016/j.scib.2018.11.018
52. 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
53. Snow depth product over Antarctic sea ice from 2002 to 2020 using multisource passive microwave radiometers X. Shen et al. https://doi.org/10.5194/essd-14-619-2022
54. SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification X. Tian-Kunze et al. https://doi.org/10.5194/tc-8-997-2014
55. Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models F. Richter et al. https://doi.org/10.5194/tc-12-921-2018
56. Satellite Microwave Radiometry for the Observation of Land Surfaces: A General Review C. Vittucci & M. Picchiani https://doi.org/10.3390/s26051638
57. A Suitable Retrieval Algorithm of Arctic Snow Depths with AMSR-2 and Its Application to Sea Ice Thicknesses of Cryosat-2 Data Z. Dong et al. https://doi.org/10.3390/rs14041041
58. Remote Sensing of Sea Surface Salinity: Comparison of Satellite and In Situ Observations and Impact of Retrieval Parameters E. Dinnat et al. https://doi.org/10.3390/rs11070750
59. Seasonal Variability of Sea Ice Bulk Density During the MOSAiC Expedition: Results From Synergistic In Situ, Airborne, and Satellite Observations Y. Zhou et al. https://doi.org/10.1109/TGRS.2025.3650353
60. 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
61. Snow Depth Retrieval on Arctic Sea Ice From Passive Microwave Radiometers—Improvements and Extensions to Multiyear Ice Using Lower Frequencies P. Rostosky et al. https://doi.org/10.1029/2018JC014028
62. Quantifying the influence of snow over sea ice morphology on L-band passive microwave satellite observations in the Southern Ocean L. Zhou et al. https://doi.org/10.5194/tc-18-4399-2024
63. Estimating the snow depth, the snow–ice interface temperature, and the effective temperature of Arctic sea ice using Advanced Microwave Scanning Radiometer 2 and ice mass balance buoy data L. Kilic et al. https://doi.org/10.5194/tc-13-1283-2019
64. Evaluation and Application of SMRT Model for L-Band Brightness Temperature Simulation in Arctic Sea Ice Y. Fan et al. https://doi.org/10.3390/rs15153889
65. Estimating snow depth over Arctic sea ice from calibrated dual-frequency radar freeboards I. Lawrence et al. https://doi.org/10.5194/tc-12-3551-2018
66. 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
67. First results of the ARIEL L-band radiometer on the MOSAiC Arctic Expedition during the late summer and autumn period C. Gabarró et al. https://doi.org/10.1525/elementa.2022.00031