Knowledge Bank

This plan describes laboratory and theoretical research to be carried out under the Sea Ice Electromagnetics Accelerated Research Initiative of the Office of Naval Research. The plan is built around three broad objectives: 1) to understand the mechanisms and processes that link the orphological/physical and the electromagnetic properties of sea ice; 2) to further develop and verify predictive models for the interaction of visible, infrared and microwave radiation with sea ice; 3) to develop and verify selected techniques in the mathematical theory of inverse scattering that are applicable to problems arising in the interaction of EM radiation with sea ice. The plan will be executed by over 30 investigators from 15 institutions. Research includes measuring and quantifying the physical properties of sea ice, collecting radiometric signatures of different ice types and morphologies, developing and testing forward models of scattering and emission from sea ice, and developing and testing inverse models to extract geophysical data about sea ice from remotely sensed data. Experiments will begin in January of 1993 at the Cold Regions Research and Engineering Laboratory in Hanover, New Hampshire. Work will focus around studies on the Geophysical Research Facility which is a new, concrete lined pool filled with saline water. The facility can be shielded from local fluctuations in weather by using a movable roof and refrigerated blanket. Three measurement series are planned for the winter of 1993. These will focus on collecting data on the microwave and optical properties of an undeformed ice sheet grown from the melt. Measurements to resolve the contributions of volume and surface scattering to sea ice signatures will be performed on an artificially roughened ice sheet. A snow covered ice sheet will be created to study the effects of brine wicking and scattering from snow grains on electromagnetic signatures. Data from these measurements will be used to evaluate the performance of existing forward models. The data will also be used to begin the development of inverse models.