Detecting seasonal ice dynamics in satellite images

• Main Authors: Greene, Chad A., Gardner, Alex S., Andrews, Lauren C.
• Format: Text
• Language: English
• Published: 2020
• Subjects: Antarctic; Greenland; Antarc*; glacier
• Online Access: https://doi.org/10.5194/tc-2020-122; https://tc.copernicus.org/preprints/tc-2020-122/

Fully understanding how glaciers respond to environmental change will require new methods to help us identify the onset of ice acceleration events and observe how dynamic signals propagate within glaciers. In particular, observations of ice dynamics on seasonal timescales may offer insights into how a glacier interacts with various forcing mechanisms throughout the year. The task of generating continuous ice velocity time series that resolve seasonal variability is made difficult by the finite integration time over which ice velocities are measured from optical and repeat SAR imagery, and by a spotty satellite record that contains no optical observations throughout dark, polar winters. In this paper, we describe a method of analyzing feature-tracked velocities to characterize the magnitude and timing of seasonal ice dynamic variability. Our method is agnostic to data gaps and is able to recover climatological average winter velocities regardless of the availability of direct observations during winter. Using characteristic image acquisition times and error distributions from Antarctic image pairs in the ITS_LIVE dataset, we generate synthetic ice velocity time series, then apply our method to recover imposed magnitudes of seasonal variability within ±1.4 m yr −1 . We then validate the techniques by comparing our results to GPS data collected on Russell Glacier in Greenland. The methods presented here may be applied to better understand how ice dynamic signals propagate on seasonal timescales, and what mechanisms control the flow of the world’s ice.