Extracting sea ice geophysical parameters from multisource data

Abstract:

Sea ice monitoring is an important field of scientific research and relevant to marine operational applications. Remote sensing imagery is useful for monitoring sea ice, identifying and tracking ice features over broad spatial scales. At the same time the current satellites have limited capabilities in providing some of the important sea ice characteristics with required temporal frequency and coverage. This work investigates possibilities of model-based estimation of sea ice geophysical parameters from multisource data. The Los Alamos sea ice model (CICE) was implemented on a high resolution regional scale (up to 2km) taking model advantages, such as the possibility of including oceanographic and climatological information, in order to extract parameters and to determine the dynamic and thermodynamic behaviour of sea ice. The sea ice simulation was performed over the Baffin Bay region and the Labrador Sea demonstrating a good agreement with remote sensing measurements acquired by the microwave radiometer and altimeter satellites. The number of geophysical parameters, such as ice thickness, age, concentration, floes statistics, and ridging were extracted using model and imaging satellite data. Information on characteristics of sea ice pressure ridges was also derived from synthetic aperture radar (SAR) imagery. The method to study ice ridges was validated with detailed information from very high resolution (0.5m) optical satellites and involved 3D modelling and visualization of ridge information. The identification of various ice types, including ice deformation features and glacier ice, was performed using medium and low resolution SAR and optical satellite data as well as their fusion product.