Greenland Ice Mapping Project: Ice Flow Velocity Variation at sub-monthly to decadal time scales

We describe several new ice velocity maps produced by the Greenland Ice Mapping Project (GIMP) using Landsat 8 and Copernicus Sentinel 1A/B data. We then focus on several sites where we analyse these data in conjunction with earlier data from this project, which extend back to the year 2000. At Jako...

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Bibliographic Details
Published in:The Cryosphere
Main Authors: Joughin, Ian, Smith, Ben E., Howat, Ian
Format: Text
Language:English
Published: 2018
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469699/
https://doi.org/10.5194/tc-12-2211-2018
Description
Summary:We describe several new ice velocity maps produced by the Greenland Ice Mapping Project (GIMP) using Landsat 8 and Copernicus Sentinel 1A/B data. We then focus on several sites where we analyse these data in conjunction with earlier data from this project, which extend back to the year 2000. At Jakobshavn Isbrae and Koge Bugt, we find good agreement when comparing results from different sensors. In a change from recent behaviour, Jakobshavn Isbrae began slowing substantially in 2017, with a mid-summer peak that was even slower than some previous winter minimums. Over the last decade, we identify two major slowdown events at Koge Bugt that coincide with short-term advances of the terminus. We also examined populations of glaciers in northwest and southwest Greenland to produce a record of speedup since 2000. Collectively these glaciers continue to speed up, but there are regional differences in the timing of periods of peak speedup. In addition, we computed trends in winter flow speed for much of the southwest margin of the ice sheet and find little in the way of statistically significant change over the period covered by our data. Finally, although consistency of the data generally is good through time and across sensors, our analysis indicates substantial differences can arise in regions with high strain rates (e.g., shear margins) where sensor resolution can become a factor. For applications such as constraining model inversions, users should factor in the impact that the data’s resolution has on their results.