Toward the Detection of Oil Spills in Newly Formed Sea Ice Using C-Band Multipolarization RadarShow others and affiliations
2022 (English)In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 60, article id 4302615Article in journal (Refereed) Published
Abstract [en]
Oil spills in the Arctic are becoming more likely as shipping traffic increases in response to climate-related sea ice loss. To improve oil spill detection capability, we used a controlled mesocosm to analyze the multipolarized C-band backscatter response of oil in newly formed sea ice (NI). Artificial sea ice was grown in two cylindrical tubs at the Sea-ice Environmental Research Facility, University of Manitoba. The sea ice physical characteristics, including surface roughness, thickness, temperature, and salinity, were measured before and after oil injection below the ice sheet. Time-series C-band radar backscatter measurements detected the differences in the sea ice evolution and oil migration to the sea ice surface in the oil-contaminated tub, which was compared to uncontaminated ice in a control tub. Immediately prior to the presence of oil on the ice surface, the copolarized backscatter is increased by 13-dB local maximum, while the cross-polarized backscatter is decreased by 9-dB. Ice physical properties suggest that the local backscatter maximum and minimum, which occurred immediately before oil migrated onto the surface, were related to a combination of brine and oil upward migration. The findings of this work provide a baseline data interpretation for oil detection in the Arctic Ocean using current and future C-band multipolarization radar satellites.
Place, publisher, year, edition, pages
IEEE Geoscience and Remote Sensing Society , 2022. Vol. 60, article id 4302615
Keywords [en]
Sea ice, Oils, Ice, Ocean temperature, Sea surface, Backscatter, Spaceborne radar, Arctic, detection, oil spill, radar backscatter
National Category
Geosciences, Multidisciplinary
Identifiers
URN: urn:nbn:se:oru:diva-98185DOI: 10.1109/TGRS.2021.3123908ISI: 000756892900006Scopus ID: 2-s2.0-85118551506OAI: oai:DiVA.org:oru-98185DiVA, id: diva2:1646090
Note
Funding agencies:
Research Manitoba
Canada Research Chair (CRC) Programs
Natural Sciences and Engineering Research Council of Canada (NSERC)
Canada Foundation for Innovation
University of Manitoba GETS Program
GENICE
2022-03-212022-03-212022-03-21Bibliographically approved