The cryospheric advanced sensor (CAS) is a developmental airborne (and, potentially, spaceborne) radar based instrumentation system for measuring and mapping the thickness of sea ice. A planned future version of the system would also provide data on the thickness of snow covering sea ice. Frequent measurements of the thickness of polar ocean sea ice and its snow cover on a synoptic scale are critical to understanding global climate change and ocean circulation.
The CAS system includes two relatively narrow-band chirped radar subsystems that operate about two different nominal middle frequencies in the very-high-frequency (VHF) range (e.g., 137 and 162 MHz). The radar targets the same surface area from two slightly different directions (see figure). The radar backscatter signals are processed to extract angular- and frequency-domain correlation functions (ACF/FCF) so that the system acts, in effect, as a combined spatial- and frequency-domain interferometric radar system.
The phase of the ACF/FCF varies with the thickness of the sea ice. To enable the utilization of the phase information to compute this thickness, the interactions between the radar waves and the seawater, ice, and snow cover are represented by a mathematical model: The snow, sea ice (including air bubbles and brine inclusions), and seawater are represented as layers, each characterized by an assumed thickness and a known or assumed complex-number index of refraction. Each interface (air/snow, snow/ice, and ice/water) is modeled as deviating from a plane by a surface roughness characterized by a Gaussian spectrum. The scattering of the radar waves from the interfaces is computed by use of small perturbation and Kirchhoff rough-surface submodels. The scattering from within the layers is computed by a Rayleigh volume scattering model. The ACF/FCF is computed from the scattered signals.
Assuming that the ACF/FCF obeys the model, the interferometric phase information can be inverted by use of a suitable computational inversion technique (e.g., a genetic algorithm or gradient descent or other least-squares technique) to obtain the thickness of the sea ice. In essence, the inversion amounts to seeking whichever value of sea-ice thickness used in the model yields the best match between (1) the ACF/FCF interferometric phase computed from the model and (2) the ACF/FCF measured interferometric phase.
This work was done by Ziad Hussein, Rolando Jordan, Kyle McDonald, Benjamin Holt, and John Huang of Caltech; Yasuo Kugo, Akira Ishimaru, and Sermsak Jaruwatanadilok of the University of Washington, Seattle; and Torry Akins and Prasad Gogineni of the University of Kansas, Lawrence, for NASA’s Jet Propulsion Laboratory. For further information, access the Technical Support Package (TSP) free on-line at www.techbriefs.com/tsp under the Physical Sciences category. NPO-42391