Abstract
AbstractThe surface restitution method we present reconstructs the evolution of a glacier surface between two time-separated surface topographies using seasonal surface mass balance (SMB) data. A conservative and systematic error analysis is included, based on the availability of surface elevation measurements within the period. The method is applied from 2001 to 2013 at Hurd Glacier (a 4 km2 glacier), where we have sufficient SMB and elevation data. We estimate surface elevation changes in two steps: (1) elevation change due to SMB and (2) elevation change due to glacier dynamics. Four different models of the method are compared depending on whether or not accumulation is memorised at each time step and whether they employ balance profiles or SMB maps. Models are validated by comparing a set of surface measurements retrieved in 2007 with the corresponding restituted elevations. Although surface elevation change between 2001 and 2007 was larger than 10 m, more than 80% of the points restituted by the four models showed errors below ±1 m compared to only 33% when predicted by a linear interpolator. As error estimates between models differ by 0.10 m, we recommend the simplest model, which does not memorise accumulation and interpolates SMB by elevation profiles.
Highlights
The use of accurate digital surface models of glaciers, hereafter DSMs, is essential for various glaciological applications, including glacier dynamics modelling, mass-balance studies and climate-forcing analysis
They are provided by the combination of two models of conversion from surface mass balance (SMB) to elevation change (Section 4.3: nM and M), each using both types of SMB data (Section 4.4: balance profile (BP) and MAP)
First (Section 5.1), we show the surface evolution during the period in a set of eight points on Hurd Glacier as a result of the restitution method, revealing the different surface oscillations depending on whether the point is in accumulation or ablation zone
Summary
The use of accurate digital surface models of glaciers, hereafter DSMs, is essential for various glaciological applications, including glacier dynamics modelling, mass-balance studies and climate-forcing analysis. Darlington Mensah and others data are not available, a DSM of the glacier is essential for the inverse methods that infer the ice thickness distribution from surface topography, velocities, mass balance and glacier thickness changes. For this approach, the error in surface slope is most often the largest source of uncertainty, stressing the importance of an accurate glacier surface topography (Farinotti and others, 2017; Fürst and others, 2017). Together with the slant-range and azimuth displacements, DSMs can be used to obtain a 3-D displacement map by combining differential SAR interferometry in the slant-range direction, offset tracking in the azimuth direction and a DSM (Strozzi and others, 2002; Sánchez-Gámez and Navarro, 2017; Gardner and others, 2018)
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