Reconstruction of historical surface mass balance, 1984–2017 from GreenTrACS multi-offset ground-penetrating radar

Abstract We present continuous estimates of snow and firn density, layer depth and accumulation from a multi-channel, multi-offset, ground-penetrating radar traverse. Our method uses the electromagnetic velocity, estimated from waveform travel-times measured at common-midpoints between sources and r...

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Bibliographic Details
Published in:Journal of Glaciology
Main Authors: Meehan, Tate G., Marshall, H. P., Bradford, John H., Hawley, Robert L., Overly, Thomas B., Lewis, Gabriel, Graeter, Karina, Osterberg, Erich, McCarthy, Forrest
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2020
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Online Access:http://dx.doi.org/10.1017/jog.2020.91
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S002214302000091X
Description
Summary:Abstract We present continuous estimates of snow and firn density, layer depth and accumulation from a multi-channel, multi-offset, ground-penetrating radar traverse. Our method uses the electromagnetic velocity, estimated from waveform travel-times measured at common-midpoints between sources and receivers. Previously, common-midpoint radar experiments on ice sheets have been limited to point observations. We completed radar velocity analysis in the upper ~2 m to estimate the surface and average snow density of the Greenland Ice Sheet. We parameterized the Herron and Langway (1980) firn density and age model using the radar-derived snow density, radar-derived surface mass balance (2015–2017) and reanalysis-derived temperature data. We applied structure-oriented filtering to the radar image along constant age horizons and increased the depth at which horizons could be reliably interpreted. We reconstructed the historical instantaneous surface mass balance, which we averaged into annual and multidecadal products along a 78 km traverse for the period 1984–2017. We found good agreement between our physically constrained parameterization and a firn core collected from the dry snow accumulation zone, and gained insights into the spatial correlation of surface snow density.