SERF2017: Thin Sea Ice Multivariate Physical & Radar Time Series sea ice time series Dataset 1.1 Complete Not planned 2025-08-10 10.34992/01GA-DT35 2025 CanWIN Dadjoo, Mehran Personal dadjoom@myumanitoba.ca Centre for Earth Observation Science - University of Manitoba 0009-0000-4322-5224 ORCID http://orcid.org/ Isleifson, Dustin Personal Dustin.Isleifson@umanitoba.ca Centre for Earth Observation Science - University of Manitoba 0000-0002-9349-8076 ORCID http://orcid.org/ Dadjoo, Mehran dadjoom@myumanitoba.ca Centre for Earth Observation Science - University of Manitoba 2017-01-12 2017-01-14 Methods Alternative Title C-band NRCS values (dB), C-band NRCS values in HH polarization (dB), C-band NRCS values in HV polarization (dB), air temperature (°C), surface temperature (°C), Cumulative Freezing Degree Moments (CFDM), humidity (%), wind speed (m/s), surface cover salinity (PSU), ice surface salinity (PSU), bulk ice salinity (PSU), frost flower height (cm), ice thickness (cm) Creative Commons Attribution 4.0 International Open https://spdx.org/licenses CanWIN datasets are licensed individually, however most are licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) Public License. Details for the licence applied can be found using the Licence URL link provided with each dataset. By using data and information provided on this site you accept the terms and conditions of the License. Unless otherwise specified, the license grants the rights to the public to use and share the data and results derived therefrom as long as the proper acknowledgment is given to the data licensor (citation), that any alteration to the data is clearly indicated, and that a link to the original data and the license is made available. By accessing this data you agree to [CanWIN's Terms of Use](/data/publication/canwin-data-statement/resource/5b942a87-ef4e-466e-8319-f588844e89c0). Online Resource Dadjoo, M., & Isleifson, D. (2025, July). Thin Sea Ice Thickness Prediction Using C-band Polarimetric Radar and Physical Observations Via Multivariate Random Forest Algorithm. In 2025 IEEE 20th International Symposium on Antenna Technology and Applied Electromagnetics (ANTEM) (pp. 74-77). IEEE. Online Resource ConferenceProceeding Cryosphere Remote Sensing Environmental Parameters Polarimetric Radar Observation Remote Sensing of Sea Ice Sea Ice Thickness Sea-ice Environmental Research Facility 2017 Experiment Data_SERF2017_Multivariate Sea Ice Time Series.xlsx XLSX application/vnd.openxmlformats-officedocument.spreadsheetml.sheet 71040.0 743e30c81842429c843f794a388e99d3