Inferring Near-Surface Density and Surface Roughness from Satellite-Based Radar Altimetry over Greenland
Authors: Scanlan Kirk Michael , Simonsen Sebastian B. 
Published: March 2022

&lt;p&gt;Estimates of mass balance across the Greenland Ice Sheet (GrIS) are commonly based on the joint interpretation of satellite radar altimetry measurements and the outputs of climate models. Conventional radar altimetry measurements, such as those produced by ESA&amp;#8217;s CryoSat-2 platform, provide an observational constraint on the physical dimensions of the ice sheet (i.e., surface height), while climate models attempt to constrain relevant mass fluxes (i.e., precipitation, run-off, and evaporation/sublimation). However, this approach provides no direct observational insight into the large-scale state and temporal evolution of near-surface density across the ice sheet; a critical quantity through which surface deformation and mass flux estimates are linked to overall mass balance.&lt;/p&gt;&lt;p&gt;To date, the analysis of space-based radar altimetry measurements over the GrIS has been predominantly concerned with determining the range between the satellite and the surface as a means of quantifying changes in ice column thickness. While some studies have investigated the relative shape of the measured return echo, little attention has been paid to its actual recorded strength. Radar Statistical Reconnaissance (RSR), originally developed for use with radar reflections from the surface of Mars, provides a framework for the interpretation of backscattered surface echo powers and the quantitative estimation of near-surface properties. The RSR method relies on using the distribution of a set of observed echo strengths in order to determine their coherent and incoherent components. These decomposed reflection components are then assumed to be related to near-surface density (coherent) and wavelength-scale surface roughness (incoherent) respectively.&lt;/p&gt;&lt;p&gt;In this study, we present the first attempt to apply the RSR methodology to Ku-band (SIRAL; on-board ESA CryoSat-2) and Ka-band (ALtiKa; on-board ISRO/CNES SARAL) radar altimetry measurements acquired over the GrIS. In continual operation since July 2010 and March 2013 respectively, the longevity of these spacecraft along with their dense spatial coverage of the GrIS provides a tantalizing opportunity to produce long-term trends in near-surface density. Surface echo powers are extracted from recorded waveforms contained in CryoSat-2 SARin FBR data products as well as SARAL SGDR data products and organized by month. We focus on waveforms in the CryoSat-2 SARin FBR data products in lieu of those from LRM Level 1B data products in order to increase the spatial density of surface echo power measurements and therefore, the spatial resolution of the RSR results. Estimates of coherent and incoherent power are then produced on a month-by-month basis for a constant set of grid points (5 km by 5 km spacing) across the GrIS. We calibrate the coherent component of the CryoSat-2 and SARAL surface echoes to near-surface density using &lt;em&gt;in situ&lt;/em&gt; measurements from the SUMup dataset.&lt;/p&gt;&lt;p&gt;This research into leveraging the radiometric information previously ignored in radar altimetry measurements to determine near-surface densities across the GrIS is a new frontier in Earth Observation. The capability to observationally determine near-surface density across the GrIS represents a fundamental contribution to refining surface mass balance estimates and understanding the evolution of the ice sheet in face of a changing climate.&lt;/p&gt;