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Author

Uri Feldman

Date of Award

8-1978

Degree Type

Thesis

Degree Name

Doctor of Philosophy (PhD)

Department

Geography

Supervisor

Professor P.J. Howarth

Abstract

Methods for predicting motions of drifting open pack ice and determining wind fields and ice parameters, associated with these motions, are needed for studying sea ice dynamics in the Polar Oceans. The new ice motion prediction method, developed and tested in this study, is a response to these needs. To ensure its applicability only readily available data, such as surface weather charts and LANDSAT-1 MSS images, were used. The method is able

a. to predict the motions of groups of wind driven detached ice floes over periods of 12, 36 and 60 hours.

b. to determine the surface wind fields, sea ice thickness and the surface and subsurface drag coefficients associated with these motions. This did not require any ice based measurements.

The method was developed by assuming wind stress, water drag and Coriolis force to be at equilibrium for a drifting group. Parameters associated with these motions were obtained from three day data sequences. Surface wind speed was estimated from the geostrophic wind fields, obtained from surface weather charts. Ice motion velocity was calculated from LANDSAT-1 MSS images. The angle of sea ice deflection, the cross isobar angles, sea ice thickness and the surface and subsurface drag coefficients were determined by solving the equilibrium equation of motion for detached ice floes, using values of the minima, maxima, means and ratios of these parameters. Weather data from a fourth day were used to predict the motions for this day. Where available, LANDSAT-1 MSS images for this day were used to test these predictions.

The method has practical usefulness if used in conjunction with data from microwave sensing systems. The predictions and parameters could be applied to support marine traffic and exploration of natural resources in the Polar Oceans. Wind fields and sea ice parameters, which were formerly practically unavailable can now be derived by the method. The knowledge gained in this study can lead to a better understanding of the physical environment in the Polar Oceans.

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