Comparison of Sea Ice Thickness Retrieval Algorithms from CryoSat-2 Satellite Altimeter Data

Sea ice thickness is an important parameter and indicator of climate change, sensitive to ecosystem in Polar Regions. For accurate forecasting of climate change, sea ice mass balance, ocean circulation and sea-atmosphere interactions, it is required to have long term records of sea ice thickness. Satellite altimetry provide useful technology for obtaining time series sea ice thickness information on hemispheric scale. So far, four mainstream algorithms based on satellite altimeter data have been used to estimate sea ice thickness effectively. Different algorithms and parameter values as selected by different researchers will lead to results unsuitable for comparison and large uncertainties. To solve this problem, this study compared sea ice thickness over the Arctic research area retrieved from these four mainstream algorithms based on CryoSat-2 satellite altimeter data. Our results demonstrate that: (1) when compared to each other, the retrieved mean sea ice thickness estimated from these four algorithms have similar spatial distribution, but with larger difference in the value, up to 0.476 m;(2) the sequence of estimated sea ice thickness for the Arctic spatial average based on four algorithms is Laxon03 algorithm, Yi11 algorithm, Laxon13 algorithm and Kurtz09 algorithm;(3) the difference of the mean sea ice thickness from these four algorithms was higher in Beaufort Sea than in Central Arctic or Greenland Sea;(4) The Laxon13 algorithm was the optimal algorithm, with the minimum bias and RMSE when compared to IceBridge sea ice thickness measurements. These results can provide useful reference and basis for further study to improve algorithms, so as to quantify dynamic changes of sea ice thickness more accurately.