Articles | Volume 13, issue 2
The Cryosphere, 13, 675–691, 2019
https://doi.org/10.5194/tc-13-675-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Cryosphere, 13, 675–691, 2019
https://doi.org/10.5194/tc-13-675-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 28 Feb 2019
Research article | 28 Feb 2019
Combined SMAP–SMOS thin sea ice thickness retrieval
Cătălin Paţilea et al.
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Cited
13 citations as recorded by crossref.
- Assessment with Controlled In-Situ Data of the Dependence of L-Band Radiometry on Sea-Ice Thickness P. Sánchez-Gámez et al. 10.3390/rs12040650
- Sea Ice and Atmospheric Parameter Retrieval From Satellite Microwave Radiometers: Synergy of AMSR2 and SMOS Compared With the CIMR Candidate Mission R. Scarlat et al. 10.1029/2019JC015749
- Estimates of spectral wave attenuation in Antarctic sea ice, using model/data inversion W. Rogers et al. 10.1016/j.coldregions.2020.103198
- Circumpolar Thin Arctic Sea Ice Thickness and Small-Scale Roughness Retrieval Using Soil Moisture and Ocean Salinity and Soil Moisture Active Passive Observations S. Jo et al. 10.3390/rs11232835
- The 2018 North Greenland polynya observed by a newly introduced merged optical and passive microwave sea-ice concentration dataset V. Ludwig et al. 10.5194/tc-13-2051-2019
- Regional suitability prediction of soil salinization based on remote-sensing derivatives and optimal spectral index Z. Wang et al. 10.1016/j.scitotenv.2021.145807
- Study of changes of vessel’s speed in ice conditions on the Northern Sea Route E. Ol’khovik 10.1088/1755-1315/378/1/012096
- Remote Sensing of Sea Ice Thickness and Salinity With 0.5–2 GHz Microwave Radiometry K. Jezek et al. 10.1109/TGRS.2019.2922163
- Toward a Data Assimilation System for Seamless Sea Ice Prediction Based on the AWI Climate Model L. Mu et al. 10.1029/2019MS001937
- Sea Ice Thickness Estimation Based on Regression Neural Networks Using L-Band Microwave Radiometry Data from the FSSCat Mission C. Herbert et al. 10.3390/rs13071366
- Polar Ocean Observations: A Critical Gap in the Observing System and Its Effect on Environmental Predictions From Hours to a Season G. Smith et al. 10.3389/fmars.2019.00429
- Gaps Analysis and Requirements Specification for the Evolution of Copernicus System for Polar Regions Monitoring: Addressing the Challenges in the Horizon 2020–2030 E. Lancheros et al. 10.3390/rs10071098
- Selection of the Key Earth Observation Sensors and Platforms Focusing on Applications for Polar Regions in the Scope of Copernicus System 2020–2030 E. Lancheros et al. 10.3390/rs11020175
11 citations as recorded by crossref.
- Assessment with Controlled In-Situ Data of the Dependence of L-Band Radiometry on Sea-Ice Thickness P. Sánchez-Gámez et al. 10.3390/rs12040650
- Sea Ice and Atmospheric Parameter Retrieval From Satellite Microwave Radiometers: Synergy of AMSR2 and SMOS Compared With the CIMR Candidate Mission R. Scarlat et al. 10.1029/2019JC015749
- Estimates of spectral wave attenuation in Antarctic sea ice, using model/data inversion W. Rogers et al. 10.1016/j.coldregions.2020.103198
- Circumpolar Thin Arctic Sea Ice Thickness and Small-Scale Roughness Retrieval Using Soil Moisture and Ocean Salinity and Soil Moisture Active Passive Observations S. Jo et al. 10.3390/rs11232835
- The 2018 North Greenland polynya observed by a newly introduced merged optical and passive microwave sea-ice concentration dataset V. Ludwig et al. 10.5194/tc-13-2051-2019
- Regional suitability prediction of soil salinization based on remote-sensing derivatives and optimal spectral index Z. Wang et al. 10.1016/j.scitotenv.2021.145807
- Study of changes of vessel’s speed in ice conditions on the Northern Sea Route E. Ol’khovik 10.1088/1755-1315/378/1/012096
- Remote Sensing of Sea Ice Thickness and Salinity With 0.5–2 GHz Microwave Radiometry K. Jezek et al. 10.1109/TGRS.2019.2922163
- Toward a Data Assimilation System for Seamless Sea Ice Prediction Based on the AWI Climate Model L. Mu et al. 10.1029/2019MS001937
- Sea Ice Thickness Estimation Based on Regression Neural Networks Using L-Band Microwave Radiometry Data from the FSSCat Mission C. Herbert et al. 10.3390/rs13071366
- Polar Ocean Observations: A Critical Gap in the Observing System and Its Effect on Environmental Predictions From Hours to a Season G. Smith et al. 10.3389/fmars.2019.00429
2 citations as recorded by crossref.
- Gaps Analysis and Requirements Specification for the Evolution of Copernicus System for Polar Regions Monitoring: Addressing the Challenges in the Horizon 2020–2030 E. Lancheros et al. 10.3390/rs10071098
- Selection of the Key Earth Observation Sensors and Platforms Focusing on Applications for Polar Regions in the Scope of Copernicus System 2020–2030 E. Lancheros et al. 10.3390/rs11020175
Latest update: 03 Dec 2021
Short summary
Sea ice thickness is important for representing atmosphere–ocean interactions in climate models. A validated satellite sea ice thickness measurement algorithm is transferred to a new sensor. The results offer a better temporal and spatial coverage of satellite measurements in the polar regions. Here we describe the calibration procedure between the two sensors, taking into account their technical differences. In addition a new filter for interference from artificial radio sources is implemented.
Sea ice thickness is important for representing atmosphere–ocean interactions in climate models....
