3a.5 A new data set for Arctic sea ice motion, deformation, and thickness from the Radarsat Geophysical Processor System

Thursday, 17 May 2001: 10:30 AM
Harry L. Stern, University of Washington, Seattle, WA; and R. W. Lindsay

The Radarsat Geophysical Processor System (RGPS) produces Lagrangian fields of arctic sea ice motion, deformation, and thickness by tracking tens of thousands of points in successive synthetic aperture radar (SAR) images of the Arctic ice cover. A systematic program of data acquisition (the "Arctic Snapshot") results in a temporal sampling rate of about once every three days, with grid points spaced (initially) 10 kilometers apart. The RGPS computes deformation directly as the spatial gradient of the ice motion, and infers the thickness of young ice indirectly from its age. In this paper we only examine the ice motion and deformation (not thickness) from RGPS for November 1996 through May 1997.

Comparison of buoy data from the International Arctic Buoy Program (IABP) with RGPS ice motion shows good agreement -- the position accuracy of both sources is about 200-300 meters. There are occasional outliers in the RGPS data due to tracking errors. The accurate RGPS ice motion leads to accurate estimates of the ice deformation (over the intervals between successive SAR images) on the scale of the grid spacing (~10 km). Spatial averaging leads to even better estimates of the deformation at the expense of spatial resolution. This trade-off is appropriate when comparing RGPS-derived deformation with that of ice dynamics models, whose grid spacing is typically many tens of kilometers.

We have made such a comparison with a state-of-the-art coupled ice-ocean dynamic-thermodynamic model for November 1996 through May 1997. Model output is averaged in time to match the RGPS sampling intervals, and RGPS data are averaged in space to match the model grid size of 40 km. Since the model is not designed to simulate actual deformation events like those captured in real data, we present a statistical comparison between the model and RGPS.

Finally, we note that several new projects are starting to use RGPS data products, and the RGPS will continue to acquire Arctic Snapshots from Radarsat and future SAR sensors, enhancing the value of these data sets by building up long time series of important variables with high spatial resolution and accuracy, and broad coverage.

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