MULLARD SPACE SCIENCE LABORATORY – UNIVERSITY COLLEGE LONDON (GB)
Why has Antarctic sea ice experienced a small increase in extent over the past decades in stark contrast to the rapid decline observed in the Arctic? What role are the Southern Ocean and sea ice playing in controlling the Deep Water formation and thermohaline circulation and the melting of the Antarctic ice shelves and sea level rise? Only satellite remote sensing can provide the pan-Antarctic view required to fully understand these changes to the Southern Hemisphere’s sea ice and ocean fields in response to anthropogenic warming.
Over the last 8 years CryoSat-2 (CS2) has allowed a radically new view of the ice covered Arctic Ocean, providing us with the first pan-Arctic sea ice thickness maps, dynamic topography and geostrophic currents, and indirectly a wealth of geophysical products ranging from Eddy kinetic energy (EKE), Ekman upwelling / downwelling, to snow on sea ice, and improved tidal models, or better resolved bathymetry at the bottom ocean.
In Antarctica similar products have emerged but remain at a lower level of maturity. Specific challenges in the processing of the radar signal result from the complex surface characteristics of the ice covered Southern Ocean such as the sea ice flooding from snow loading or the highly fragmented and divergent marginal ice zone like nature of the sea ice cover. In addition, validation of sea ice and ocean products is hindered by the observational gap of in-situ and airborne data in the Southern Hemisphere.
The overarching objective of this project is to address these issues by developing new approaches and algorithms that could be implemented in ESA’s CryoSat-2 ground segment processor to produce state of the art sea ice and ocean products that will be validated against a comprehensive dataset of airborne and in-situ measurements and result in scientific progress for our understanding of the Antarctic Climate system and ocean circulation.
The main objectives of this project are:
The main outputs of the project will be:
The biggest challenges the project faces are the difficulties in validating data products against sparse or preferentially sampled, in-situ data, and in proving that a new method is measurably better than an existing method when applied to inherently noisy data.
IEEE Transactions on Geoscience and Remote Sensing
Geophysical Research Letters