Abstract
Abstract. The recent influx of remote sensing data provides new opportunities for quantifying spatiotemporal variations in glacier surface velocity and elevation fields. Here, we introduce a flexible time series reconstruction and decomposition technique for forming continuous, time-dependent surface velocity and elevation fields from discontinuous data and partitioning these time series into short- and long-term variations. The time series reconstruction consists of a sparsity-regularized least-squares regression for modeling time series as a linear combination of generic basis functions of multiple temporal scales, allowing us to capture complex variations in the data using simple functions. We apply this method to the multitemporal evolution of Sermeq Kujalleq (Jakobshavn Isbræ), Greenland. Using 555 ice velocity maps generated by the Greenland Ice Mapping Project and covering the period 2009–2019, we show that the amplification in seasonal velocity variations in 2012–2016 was coincident with a longer-term speedup initiating in 2012. Similarly, the reduction in post-2017 seasonal velocity variations was coincident with a longer-term slowdown initiating around 2017. To understand how these perturbations propagate through the glacier, we introduce an approach for quantifying the spatially varying and frequency-dependent phase velocities and attenuation length scales of the resulting traveling waves. We hypothesize that these traveling waves are predominantly kinematic waves based on their long periods, coincident changes in surface velocity and elevation, and connection with variations in the terminus position. This ability to quantify wave propagation enables an entirely new framework for studying glacier dynamics using remote sensing data.
Highlights
Until recently, observations of glacier and ice stream motion were limited to velocity snapshots measuring motion over distinct time periods, most commonly averaged over multiple years or annually repeating (Rignot et al, 2011; Gardner et al, 2018; Moon et al, 2012)
We focus on applying the time series analysis methods presented in Sect. 2 to analyze and decompose the observed time-dependent velocity magnitude and surface elevation fields summarized in Sect. 3 into subannual and multi-annual transient variations
Our focus is on quantifying the rates and distances over which stress perturbations of various frequencies propagate through Jakobshavn Isbræ
Summary
Observations of glacier and ice stream motion were limited to velocity snapshots measuring motion over distinct time periods, most commonly averaged over multiple years or annually repeating (Rignot et al, 2011; Gardner et al, 2018; Moon et al, 2012). While the increase in spatial coverage of velocity measurements facilitated by the increasing availability of satellite-based remote sensing observations has allowed for ice-sheet-wide analysis, the complexity of glacier dynamics requires observations at multiple temporal scales. Velocity observations averaged over multiple years may not resolve rapid dynamical changes, whereas isolated snapshots acquired over a short time window may bias estimates of longer-term or periodic trends (Minchew et al, 2017). Since the relevant timescales for resolving glacier dynamics vary significantly from glacier to glacier, any attempt to reconstruct the velocity history must be able to resolve these multiple temporal scales with minimal prior information.
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