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摘要
A simple, blended mechanistic-statistical ice motion model is presented. The model requires regular synoptic-scale wind and ice velocity observations as input. It is intended as an ice forecast tool for offshore operators. We anticipate this model will be useful for short-term forecasts from a few hours up to roughly 5 days. Ice velocity is estimated and forecast as the sum of mechanistic components (fully dynamic free drift, slowly varying deep ocean currents, and tidal oscillations) and a statistical component that minimizes errors between the mechanistic components and recent observations. The free-drift model includes the inertial effects of the ocean mixed layer and describes the combined effects of wind forcing and inertial oscillations. Deep ocean currents are estimated as the average of recent mechanistic component model errors. Tidal velocity contributions can be input by filtering recent observations at tidal frequencies or by an independent model. The effects of ice stress divergence and other unmodeled physics are approximated using optimal linear interpolation. The statistical component is estimated from the difference between recent ice motion observations and the mechanistic components of the model. Its mean and variance are then held constant for the forecast period. Using 60 days of CEAREX drift data, we found the following accuracy statistics. Average ice velocity component forecasts were accurate to within 0.002-0.003 m/s for all forecast periods up to 5 days. Nowcasts had a vector standard deviation of about 0.06 m/s, and 5-day forecasts had a vector standard deviation of 0.14 m/s. Concurrent free-drift forecasts had similar average component errors, but nowcasts were accurate to about 0.08 m/s, although after 3 days they agreed with the blended model forecasts, since the optimal estimate approaches zero after this period.
- 出版日期2012-6
