thermodynamic and dielectric properties of oil-contaminated sea ice through scatterometer and lidar measurements
thermodynamic and dielectric properties of oil-contaminated sea ice through scatterometer and lidar measurements
Microwave remote sensing is an effective tool for detection of oil spills in ice-covered waters. The presence of oil as either a separate layer beneath/above the sea ice or encapsulated within the sea ice, changes the profile’s thermodynamic properties and hence, its dielectric values. On the other hand, these changes in the oil-contaminated sea ice change the microwave radar signature of the profile, e.g., its normalized radar cross section (NRCS). The NRCS values associated with such profile can be measured remotely via ground-based/airborne radar systems, or SAR satellites. The investigation of NRCS associated with oil-contaminated sea ice is scarce in the literature. This is mainly due to environmental concerns about releasing crude oil in the Arctic waters to perform research experiments. To tackle this, we take advantage of the state-of-art Sea-ice Environmental Research Facility (SERF). SERF is equipped with an oil tank designed for oil release beneath an artificially-grown sea ice under controlled conditions. During this project, our objectives are as follows. (i) To measure the time-series thermodynamic (e.g., temperature and salinity) changes of the sea ice due to the presence of oil beneath it, and to observe the effects of the migration of oil through the brine channels and how this affects its thermodynamic parameters. (These data are subsequently utilized to calculate the changes of the temporal dielectric profile.) (ii) To scan the sea ice surface utilizing a lidar system to track the change in surface roughness characterization due to an altered sea ice thermodynamics by oil presence. (iii) To measure the time-series NRCS of the oil-contaminated sea ice through a C-band scatterometer. Such measured NRCS data during this project can be utilized for oil detection via electromagnetic prediction algorithms.
Fieldwork site: Sea Ice Environmental Research Facility (SERF), University of Manitoba, Winnipeg (Canada)
Project Lead: N. Firoozy
Project Participants: Nariman Firoozy (CEOS, ECE), Tyler Tiedet (CEOS, ECE), Thomas Neustizer (CEOS, ECE), Durell Desmond (CEOS), Jack Landy (CEOS), Dr. David Barber (CEOS), Dr. Puyan Mojabi (CEOS, ECE), Dr. Monkia Pucko (CEOS)