Abstract's details

Towards 30 years of Arctic sea ice freeboard retrieval using Altimetry

Marion Bocquet (LEGOS, France)


Sara Fleury (LEGOS, France); Thomas Moreau (CLS, France); Florent Garnier (LEGOS, France); Frédérique Rémy (LEGOS, France)

Event: 2022 Ocean Surface Topography Science Team Meeting

Session: Application development for Operations

Presentation type: Type Forum only

Sea ice thickness is an important variable for sea ice monitoring and climate projections. Although observations of ice extent and concentration have been available since late 1978, the same is not true for ice thickness. Because of the high interannual variability of the ice pack, climate trends in thickness and volume can only be observed over long time series. The earliest measurements of sea ice thickness (as multi-year averages for ERS-1 and ERS-2) were published in 2003 (Laxon al 2003) (but these results have never been replicated). Today, the longest series go back to the winter of 2002/2003 (the beginning of the Envisat mission). The main difficulty in going back in time is linked to the difference in altimeter generation and processing. The launch of the first SAR altimeter aboard CryoSat-2 made it possible to obtain the first consistent measurements of freeboards measurements, thanks to its small footprint (about 5km2). Prior to CryoSat-2, space altimeters were in low-resolution mode (LRM), with a footprint of the order of 150km2 overlapping heterogeneous surface types. To improve Envisat measurements, different calibration methodologies relative to CryoSat-2 have been proposed taking advantage of the common flight period (2010-2012) (Guerreiro al 2017, Paul al 2018, Tilling al 2019, etc.).We propose in this study a more general and robust method based on a neural network taking into account the state of the ice, from its surface roughness to its type. In order to extend the coverage to the beginning of the polar altimeter era (1993), we extended this method to ERS measurements by taking advantage of the common period with Envisat. Therefore, the measurements are successively corrected with reference to the most accurate CryoSat-2measurements, offering a homogeneous series over nearly 30 years. If ERS thickness measurements have not been reproduced, it is also because of the pulse-blurring effect due to instabilities of the tracker board, which must be corrected. The methodology used in the study to overcome this, is the interpretation of the N.Peacock (2004) approach. We are finally able to provide a radar freeboard product for the Arctic between 50°N and82.5°N over almost 30 winters (up to 88°N for Cryosat-2). The freeboard product is given with corresponding uncertainties using a Monte Carlo methodology to propagate all emission uncertainties through the neural network. The time series is finally compared to numerous in situ datasets, airborne measurements, or other products from other types of altimeters such as the ICE-Sat missions. Unless it is complicated to give precise conclusions due to the lack of long and homogeneous time series of snow depth, the comparisons show good consistency between field data and altimetry data.
Marion Bocquet