Inferred basal friction and surface mass balance of North-East Greenland Ice Stream using data assimilation of ICESat-1 surface altimetry and ISSM

Abstract

Abstract. We present a new data assimilation method within the ISSM framework that is capable of assimilating surface altimetry data from missions such as ICESat-1 into reconstructions of transient ice flow. The new method relies on algorithmic differentiation to compute gradients of diagnostics with respect to model forcings. It is applied to the North East Greenland Ice Stream where surface mass balance and basal friction forcings are temporally inverted, resulting in significantly improved modeled surface heights that match existing altimetry. This new approach allows for a better quantification of basal and surface processes, and a better understanding of the physical processes currently missing in transient ice flow models to better capture the important intra and inter-annual variability in surface altimetry. It also demonstrates that large spatial and temporal variability is required in model forcings such as surface mass balance and basal friction, variability that can only be explained by including more complex processes such as snowpack compaction at the surface and basal hydrology at the bottom of the ice sheet. This approach is indeed a first step towards assimilating the wealth of high spatial resolution altimetry data available from EnviSat, ICESat-1, Operation IceBridge and CryoSat-2, and that will be available in the near future with the launch of ICESat-2.

Thermal Weakening, Convergent Flow, and Vertical Heat Transport in the Northeast Greenland Ice Stream Shear Margins

“…This mismatch likely arises from a combination of data limitations (e.g., spatially incomplete ice thickness measurements or poorly known accumulation rates) and missing physics in the model (e.g., ice fabric evolution), and is a common challenge in ice sheet modeling. Models typically address this mismatch using one of three approaches: (1) the ice surface is allowed to relax in accordance with ice velocities (as in Larour et al, ; Brondex et al, ), resulting in a model with matching surface velocities but erroneous ice thickness; (2) the horizontal velocities are calculated from the observed ice geometry and accumulation rate to bring the system into mass balance, resulting in a disagreement between observed and modeled horizontal flow speeds (Dansgaard & Johnsen, ); or (3) the ice thickness and horizontal velocities are imposed, and the vertical velocities are assumed to provide balance, allowing disagreement with accumulation rates at the surface (as in Pattyn, ).…”

Crevasses as Indicators of Surge Dynamics in the Bering Bagley Glacier System, Alaska: Numerical Experiments and Comparison to Image Data Analysis

“…In this study, we solve for global and uniform values for 𝛽 and 𝜎 threshold as the simplest method for determining basal sliding and ice yield strength during a surge phase. A spatially variable approach could use a more advanced cost function that minimizes observed and modeled crevasse differences to estimate 𝛽 and 𝜎 threshold at each nodal location given some regularization, such as those used in velocity-based approaches (e.g., Larour et al, 2014).…”

Satellite Remote Sensing of the Greenland Ice Sheet Ablation Zone: A Review

“…Examples include fusing radar and laser altimetry with optical stereophotogrammetry to discriminate and diagnose causes of surface elevation change [174], or fusing radar and laser backscatter with optical imagery to discriminate snow, ice, liquid water, and refrozen meltwater in sensitive areas near the equilibrium line altitude [362,363]. Other areas of opportunity recommended for future research include spaceborne detection of subsurface refrozen meltwater and its effects on radar backscatter, which requires additional in-situ validation [115,116], the partitioning of ablation zone thinning into ice-dynamic and surface mass balance components [97], cross-validation of ice surface elevation change from altimetry with modeled surface mass balance [89] and modeled ice dynamic motion [189], spaceborne diagnosis of changing bare ice albedo [269] and grain size [191], and monitoring the inland migration of snowlines, surface melt extent, and surface hydrologic features including lakes, streams, and moulins [26,56].…”

“…ICESat-2 research to date has focused on pre-mission proof of concept, airborne and ground validation, and sensor calibration [186][187][188]. In addition to its unique ability to map surface water bathymetry, other novel applications of laser altimetry to the ablation zone that will benefit from ICESat-2 continuity include assimilation of dH/dt observations into transient ice flow simulations [189], fusion of multi-sensor (e.g., stereophotogrammetry or radar altimetry) datasets to increase the spatial density of surface elevation measurements [174], and application of lidar-based snow grain size and surface roughness retrievals independent of or in combination with optical sensors [190,191]. Comparison between ice sheet surface elevation change estimates by the laser altimetry and regional climate model (RCM) SMB is another area that is underexplored [89].…”