Comparison of Elevation Change Detection Methods From ICESat Altimetry Over the Greenland Ice Sheet

Abstract

Estimation of the surface elevation change of the Greenland Ice Sheet (GrIS) is essential for understanding its response to recent and future climate change. Laser measurements from the NASA’s Ice, Cloud, and land Elevation Satellite (ICESat) created altimetric surveys of GrIS surface elevations over the 2003–2009 operational period of the mission. This paper compares four change detection methods using Release 634 ICESat laser altimetry data: repeat tracks (RTs), crossovers (XOs), overlapping footprints (OFPs), and triangulated irregular networks (TINs). All four methods begin with a consistently edited data set and yield estimates of volumetric loss of ice from the GrIS ranging from −193 to −269 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /yr. Using a uniform approach for quantifying uncertainties, we find that volume change rates at the drainage system scale from the four methods can be reconciled within 1- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula> uncertainties in just 5 of 19 drainage systems. Ice-sheet-wide volume change estimates from the four methods cannot be reconciled within 1- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula> uncertainties. Our volume change estimates lie within the range of previously published estimates, highlighting that the choice of method plays a dominant role in the scatter of volume change estimates. We find that for much of the GrIS, the OFP and TIN methods yield the lowest volume change uncertainties because of their superior spatial distribution of elevation change rate estimates. However, the RT and XO methods offer inherent advantages, and the future work to combine the elevation change detection methods to produce better estimates is warranted.