How Different Analysis and Interpolation Methods Affect the Accuracy of Ice Surface Elevation Changes Inferred from Satellite Altimetry

• Published in: Mathematical Geosciences
• Main Authors: Strößenreuther, Undine, Horwath, Martin, Schröder, Ludwig
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2020
• Subjects: Ice sheet; Satellite altimetry; Article; Interpolation; Kriging; Repeat altimetry; Greenland; Raa; Ice Sheet
• Online Access: https://repository.publisso.de/resource/frl:6468526; https://doi.org/10.1007/s11004-019-09851-3

<jats:title>Abstract</jats:title><jats:p>Satellite altimetry has been widely used to determine surface elevation changes in polar ice sheets. The original height measurements are irregularly distributed in space and time. Gridded surface elevation changes are commonly derived by repeat altimetry analysis (RAA) and subsequent spatial interpolation of height change estimates. This article assesses how methodological choices related to those two steps affect the accuracy of surface elevation changes, and how well this accuracy is represented by formal uncertainties. In a simulation environment resembling CryoSat-2 measurements acquired over a region in northeast Greenland between December 2010 and January 2014, different local topography modeling approaches and different cell sizes for RAA, and four interpolation approaches are tested. Among the simulated cases, the choice of either favorable or unfavorable RAA affects the accuracy of results by about a factor of 6, and the different accuracy levels are propagated into the results of interpolation. For RAA, correcting local topography by an external digital elevation model (DEM) is best, if a very precise DEM is available, which is not always the case. Yet the best DEM-independent local topography correction (nine-parameter model within a 3,000 m diameter cell) is comparable to the use of a perfect DEM, which exactly represents the ice sheet topography, on the same cell size. Interpolation by heterogeneous measurement-error-filtered kriging is significantly more accurate (on the order of 50% error reduction) than interpolation methods, which do not account for heterogeneous errors.</jats:p>