Examining the Mean Dynamic Topography and Circulation of the Arctic Ocean using CryoSat & GOCE
Thomas, Sam1; Giles, Katharine1; Bingham, Rory2; Ridout, Andy1
1Centre for Polar Observation & Modelling, UNITED KINGDOM; 2Newcastle University, UNITED KINGDOM

The Arctic is a region of great significance to the global climate, and is currently undergoing major changes on a short timescale. It is crucial to improve monitoring of this region and our understanding of its climate. However, the polar environment makes gathering spatially & temporally comprehensive data via in-situ measurements highly impractical. Furthermore, our ability to use satellite-based techniques in the region has been limited by the inclination at which past missions have been flown.

CryoSat is unprecedented in providing continuous, high-resolution altimetry at latitudes of up to 88°, giving almost complete polar coverage. In addition to CryoSat's primary mission of surveying ice, this allows us to derive the mean dynamic topography (MDT) and hence geostrophic circulation of almost the entire Arctic Ocean by combination with new gravity data from the GOCE mission. Given GOCE's high resolution, we may achieve excellent accuracy using this technique.

In this paper we describe how the latest GOCE potential model is expanded into gridded form at a degree & order chosen to minimise omission & commission error, before being combined with a recent mean sea surface (MSS) derived from CryoSat altimetry. We detail how both traditional low-pass methods and the emergent technique of anisotropic diffusion are used to filter this data an optimal level in order to produce a solution for the Arctic Ocean MDT. From these solutions geostrophic currents are calculated, and the results are compared to previous work. We also present a preliminary comparison with data gathered in-situ, as well as a brief examination of the suitability of different gravity models for oceanographic work in the Arctic region. Finally we outline ongoing work on a superior MDT solution by combining the MSS & geoid in spectral form and some potential applications of this new data.