Funds are provided to analyze submarine and moored upward-looking sonar (ULS) data from 1975-2005, focusing on the North Polar Region (NPR, north of 87o N) where the submarine data are densest and moored data resolve multiple annual cycles. Recent declassifications by the U.S. Navy have doubled the available submarine data, and 4 or 5 annual series will be available from moored ULS in NPR. Coverage by the submarines is dense along the profile, but sporadic in time. Coverage by the moored ULS is dense in time, but sparse in space. Several ancillary datasets will be analyzed: sea-ice kinematics, thermodynamic and atmospheric circulation data from the International Arctic Buoy Program, estimated monthly fields of sea-ice age, and forcing and output variables from a coupled ocean/ice model. The mean ice draft will be described statistically. Binning the ULS data in space/time windows of varying size, estimating sample statistics and confidence limits, and performing multiple regression analysis will show how accurate this description is at different resolutions. Relationships between the ULS data and the ancillary data will be studied, using correlation techniques and diagnostic analysis of the budget equation for mean thickness, in order to identify causes of variability and discrepancies between the model and data.
Sea ice thickness is an important diagnostic for climate variability. It is required for estimation of the sea ice mass balance and, consequently, has implications for the world ocean's fresh water budget and thermohaline circulation (the global conveyer belt). Results of this project will permit improved estimation of ice draft variability in the NPR during the past and, potentially, at times when there are few or no submarine data, as is likely to be the case during the next decade. The study will increase knowledge and understanding of the spatial and temporal variability of ice draft, including its causes, and provide more robust estimates of sample statistics and trends in NPR.
