CoAuthors

Pierre Thibaut (CLS, France); Duc Hoang (CLS, France); Laiba Amarouche (CLS, France); Amandine Guillot (CNES, France); Sophie Le Gac (CNES, France); Nicolas Picot (CNES, France); Graham Quartly (PML, UK); Andrey Kurekin (Plymouth Marine Laboratory, UK); Jérôme Benveniste (ESA, Italy)

The Arctic Ocean is an important component of the climate system whose exact influence on ocean circulation is still poorly understood today. Due to the presence of sea ice and its temporal variability, sea level data coverage is seasonal and this hampers the use of altimetry for climate studies. It is thus crucial to increase the coverage of altimetry measurements in these areas. Considering that the sea ice is not homogeneous but fractured by small openings or water channels called leads or polynyas, it is essential to distinguish ice-free regions from regions covered by sea ice, to identify lead returns and to improve the estimation process for those particular measurements.
Thanks to the CNES PEACHI project and the ESA Sea Level CCI project, Ka-band AltiKa waveforms and Ku-Band RA-2 waveforms have been respectively processed in order to retrieve sea level height estimates in the Arctic Ocean regardless of the sea ice presence. Peaky waveforms coming from leads or polynyas have been identified and a new retracking algorithm developed based on an ocean model including the mean square slope of the surface in its formulation. This new analytical adaptive 4-parameter solution allows us to fit very well both ocean waveforms as well as peaky waveforms from leads, accounting for the major instrumental characteristics (point target response, antenna gain pattern …) and ensuring the continuity between open ocean and ice covered sea level estimations. Finally, the use of such a physical model allows to mitigate the poor sampling of the returned waveform that is particularly limiting in such highly contrasted and reflective areas.