Volume 2 Issue 2
Authors: Vera Djepa
Abstract: Long term Sea Ice Thickness (SIT) distribution in the Arctic with corresponding uncertainties is required for improved climate forecast. Different approaches have been applied to retrieve SIT, where only satellite altimeter (radar or laser) has been proven to provide hemispheric estimates of SIT distribution. SIT, retrieved from Radar Altimeter (RA), depends on the accuracy of the derived freeboard from RA, and the information for ice and snow densities and depths. Constant ice densities have been used for SIT retrieval from RA, which leads to different results for derived SIT and Sea Ice Draft (SID) in dependence on input information for sea ice densities and snow depth. The aim of this study is to develop algorithm to convert the freeboard derived from RA into SIT and SID, providing minimum long term bias with collocated SID derived from Upward Looking Sonar (ULS) and Laser Altimeter (LA), using variable ice density. For the first time, variable ice density (rather than constant ice densities used until now from different authors) is inserted in the equation for hydrostatic equilibrium. The sea ice density dependence on ice freeboard, confirmed with observations, has been applied to develop a new algorithm to convert the freeboard, measured from RA and LA in SIT, using variable sea ice density. The impact of snow depth, ice and snow densities on accuracy of the retrieved SIT has been examined by applying sensitivity analyses. The propagated uncertainties have been summarised and it is confirmed the high accuracy of the developed freeboard depended (FD) algorithm to retrieve SIT from RA, using variable ice density, snow depth and density from Warren Climatology (WC). Sensitivity analyses and comparison of collocated SID from RA and ULS, as well as SIT, retrieved from RA and LA confirm the high accuracy of the developed FD algorithms. The validation study and sensitivity analyses demonstrate that the assumption of half snow depth over First Year Ice (FYI) will always lead to underestimation of SIT and SID derived from RA. ESA (ERS1, 2, ENVISAT, CryoSat-2 and Sentinel), the National Aeronautics and Space Administration (NASA), satellite, airborne missions, climate and numerical forecast programs will benefit from the results of this paper.
Keywords: Remote Sensing; Sea Ice Thickness; Algorithms; Sensitivity Analyses; Radar and Laser Altimeter
Authors: Guido Staub
Abstract: Within this article a novel approach is described, in which spaceborne Long Wavelength Infrared, Synthetic Aperture Radar and geophysical observations are combined in one single and comprehensive 3D representation in order to provide a tool for monitoring and analysis purposes. Digital Terrain Model information is considered in order to generate a three dimensional topographic model of an ice shelf. In case of sea ice, instead of height information, data derived from the raw spaceborne observations are assigned to the z-axis. However, in order to complement the 3D representation ASTER GDEM data is considered. Furthermore, sub-surface and –ocean data from geophysical surveys and MODIS observations are incorporated. By such a multi-sensor model, it is possible to make a statement about the past and present situations in the study area and the nearby environmental conditions. In consequence, it can be considered as the basic (sub-)surface representation that incorporates environmental information.
Keywords: Remote Sensing; Visualization; Antarctica