AbstractAn Ocean Tidal Inverse Model for the Antarctic Ice Shelves and SeasLaurie Padman, Helen Fricker, and Richard Coleman. We describe an inverse model for ocean tides around Antarctica, including the ocean water cavities beneath the large ice shelves. This high resolution (<10 km grid spacing) model uses objective assimilation of surface height data (TOPEX/Poseidon satellite altimetry over open water; coastal and benthic tide gauges; and 3-D GPS on the ice shelves) to improve the tidal solution relative to existing global models. Non-assimilated data, including short GPS records and differential SAR interferometry on ice shelves, is used to assess model performance. We examine the tides of the Amery Ice Shelf to illustrate the effect of data assimilation on the local tidal solutions. Around the Antarctic, peak-to-peak tide-induced elevation changes for ice shelves are typically 1-2 m, but can exceed 5 m during spring tides on the Filchner-Ronne and Larsen ice shelves in the Weddell Sea. The new model provides a tool for removal of tides from satellite-based estimates of three-dimensional shelf ice motion using SAR interferometry. Studies of long-term trends in ice shelf surface elevation using data from the Geoscience Laser Altimeter System (GLAS), planned for launch in October 2001 on board the Ice Cloud and Land Elevation satellite (ICESat), will also require accurate removal of tides from the GLAS surface elevation profiles. While the data assimilation method helps overcome some of the difficulties that make tides close to Antarctica difficult to predict, we emphasize that two significant obstacles remain to a reliable circum-Antarctic tidal model poor-quality model grids of bathymetry and water column thickness under ice shelves; and lack of sufficient GPS data from ice shelves. We see the continued improvement of the BEDMAP water column thickness grid as an essential tool for tidal modeling. We also propose to develop and maintain a database of GPS records from all Antarctic ice shelves, that can be used in data assimilation and model validation studies. We solicit feedback from investigators willing to contribute data to this database. |