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. Sea ice drift plays a central role in the Arctic climate and ecology throughits effects on the ice cover, thermodynamics, and energetics of northernmarine ecosystems. Due to the challenges of accessing the Arctic, remotesensing has been used to obtain large-scale longitudinal data. These dataare often associated with errors and biases that must be considered whenincorporated into research. However, obtaining reference data for validationis often prohibitively expensive or practically unfeasible. We used themotion of 20 passively drifting high-accuracy GPS telemetry collarsoriginally deployed on polar bears, Ursus maritimus, in western Hudson Bay, Canada, tovalidate a widely used sea ice drift dataset produced by the National Snowand Ice Data Center (NSIDC). Our results showed that the NSIDC model tendedto underestimate the horizontal and vertical (i.e., u and v)components of drift. Consequently, the NSIDC model underestimated magnitudeof drift, particularly at high ice speeds. Modelled drift direction wasunbiased; however, it was less precise at lower drift speeds. Research usingthese drift data should consider integrating these biases into theiranalyses, particularly where absolute ground speed or direction isnecessary. Further investigation is required into the sources of error,particularly in under-examined areas without in situ data.

Opportunistic evaluation of modelled sea ice drift using passively drifting telemetry collars in Hudson Bay, Canada