| Summary: | The article of record as published may be found at http://inis.iaea.org/search/search.aspx?orig_q=RN:24050052 The US Navy has recently developed an underwater acoustic propagation loss model suitable for use in ice-covered seas. The under-ice scattering component of this model requires a spatially varying input data base of ice roughness characteristics to support both empirically- and theoretically derived scattering loss algorithms. The empirical algorithms characterize the under-ice roughness by the standard deviation of the mean ice draft. The theoretical algorithms are based upon keel characteristics, namely the mean deep draft keel and the number of deep draft keels per unit distance. The authors have attempted to construct a data base of these parameters for the Arctic Ocean based upon analysis of under-ice thickness distribution data acquired from inverted echo-sounder data from submarines transmitting under the ice. From the voyages of 13 submarines, which traversed virtually all regions of the Arctic Ocean during all seasons, a suite of ice thickness statistics have been calculated for 50-km segments along each submarine track. Contour maps of the roughness parameters were constructed. Not surprisingly they show that the roughest ice and the greatest number of deep draft ice keels are found off the north coasts of the Canadian Archipelago and Greenland due to ice convergence on these land barriers. A linear regression demonstrates that the ice roughness, characterized by the standard deviation, increases with increasing ice thickness at a rate of about 0.5. Similar maps based on further analysis of all submarine-collected under-ice thickness distribution data on a year by year basis could be invaluable in the determination and monitoring of geographically specific and basin-wide sea ice changes. Such maps could be of considerable significance in the determination of the role of the polar regions in global change.
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