Improved Retrieval of Sea Ice Thickness and Density from Laser Altimeter

Abstract

The sensitivity of weather and climate system to sea ice thickness (SIT) in the Arctic is recognised from various studies. Decrease of SIT will affect atmospheric circulation, temperature, precipitation and wind speed in the Arctic and remotely. Ice thermodynamics and dynamic properties depend strongly on ice and snow thickness. The heat transfer through ice critically depends on ice thickness. Long term accurate SIT records with corresponding uncertainties are required for improved seasonal weather forecast and estimate of the sea ice mass balance. Satellite radar and Laser Altimeter (LA) provide long term records of sea ice freeboard. Assuming isostatic equilibrium, SIT is retrieved from the freeboard, extracted from radar altimeter (RA) or LA, where the snow depth, density, ice and water density are input variables in the equation for hydrostatic equilibrium to derive SIT from LA or RA. Different input variables (snow depth, density, ice and water density) with unknown accuracy have been applied from various authors to retrieve SIT and Sea Ice Draft (SID) from RA or LA, leading to not comparative results. Sea ice density dependence on ice type, thermodynamic properties and freeboard is confirmed with different studies. Sensitivity analyses confirm the great impact of sea ice density, snow depth and density on accuracy of the retrieved SIT and the importance of inserting variable ice density (VID) in the equation for hydrostatic equilibrium for more accurate SIT retrieval, weather and climate forecast. The impact of sea ice density and snow depth and density on retrieved SIT from the freeboard derived from LA and RA have been analyzed in this study using the equation for hydrostatic equilibrium, statistical and sensitivity analyses. An algorithm is developed to convert the freeboard, derived from LA in SIT, inserting VID in the equation for hydrostatic equilibrium. The algorithm is validated with field, laboratory studies and collocated SIT retrieved from RA on board Envisat. The accuracy of the developed algorithm is analyzed, using statistical and uncertainty analyses. It is found that the uncertainty of the retrieved SIT from LA is decreased 7.6 times (from r hi = 59 cm for fixed ice density) if variable ice density is inserted in the equation for hydrostatic equilibrium. The SIT, which has been retrieved from the freeboard derived from LA is validated with collocated SIT derived from RA2 on Envisat, using variable ice density. The bias of the mean SIT derived from LA and RA has been reduced from -1.1 m to about one millimeter when VID is applied to retrieve SIT from LA and RA. The results and algorithms, discussed in this paper are essential contribution to SIT and SID retrieval, satellite remote sensing, cryosphere, meteorology and improved weather and climate forecast.