摘要：Knowledge of the surface velocity and strain of ice shelves is important in determining their present kinematic state and detecting any change in that state. Data collected using the Global Positioning System (GPS) often plays an important role in determing these parameters, either directly, or as ground-truthing to other techniques such as InSAR. The processing of GPS data on floating ice shelves is complicated by the presence of a distinct vertical tidal signal and large horizontal motions in the data. Over a one hour period, vertical and horizontal movements can be as much as 0.3 metres and 0.1 metres respectively. For such GPS data to be processed using conventional static methods would require the observation period to be split into small (∼1 hour) segments, and the segments processed separately. Other processing options may include kinematic processing or sequential processing, although these techniques have their own drawbacks. Instead, we have developed software to remove signals based on a priori knowledge of the ice shelf motion. The tidal signal is removed using a local tide model and the horizontal velocity effect is corrected to a specific time epoch. This allows us to process our GPS data in a tide-free, velocity-free environment for a given day using conventional GPS processing software. The corrected GPS data, now largely free from the effects of ice shelf motion, may then be combined to produce high precision velocity and strain rate models of the ice shelf.
