A new tide model for the Antarctic ice shelves and seas

TLDR

The authors present a new tide model for Antarctic seas and aim to improve its predictive skill through refined physics, better grounding line definitions, accurate water‑column data, and extended tide measurements. The model incorporates data assimilation to fit existing observations and relies on enhanced physics, precise grounding line delineation, and long‑duration pressure or GPS measurements to improve accuracy. Typical peak‑to‑peak tide ranges on ice shelves are 1–2 m, exceeding 3 m for the Filchner–Ronne and Larsen shelves, with spring ranges roughly double; however, the model currently falls short of the 5–10 cm accuracy required for GLAS height data, achieving such precision only near assimilated records.

Abstract

Abstract We describe a new tide model for the seas surrounding Antarctica, including the ocean cavities under the floating ice shelves. The model uses data assimilation to improve its fit to available data. Typical peak-to-peak tide ranges on ice shelves are 1–2 m but can exceed 3 m for the Filchner–Ronne and Larsen Ice Shelves in the Weddell Sea. Spring tidal ranges are about twice these values. Model performance is judged relative to the ~5–10 cm accuracy that is needed to fully utilize ice-shelf height data that will be collected with the Geoscience Laser Altimeter System, scheduled to be launched on the Ice, Cloud and land Elevation Satellite in late 2002. The model does not yet achieve this level of accuracy except very near the few high-quality tidal records that have been assimilated into the model. Some improvement in predictive skill is expected from increased sophistication of model physics, but we also require better definition of ice-shelf grounding lines and more accurate water-column thickness data in shelf seas and under the ice shelves. Long-duration tide measurements (bottom pressure gauge or global positioning system) in critical data-sparse areas, particularly near and on the Filchner–Ronne and Ross Ice Shelves and Pine Island Bay, are required to improve the performance of the data-assimilation model.