EGU22-10563
https://doi.org/10.5194/egusphere-egu22-10563
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

More data and increased automation leads to better quality for GLIMS and RGI glacier data sets

Bruce Raup1, Fabien Maussion2, Frank Paul3, Etienne Berthier4, Tobias Bolch5, Jeffrey Kargel6, and Adina Racoviteanu7
Bruce Raup et al.
  • 1University of Colorado, National Snow and Ice Data Center, Boulder, United States of America (braup@nsidc.org)
  • 2University of Innsbruck, Innsbruck, Austria
  • 3University of Zurich, Zurich, Switzerland
  • 4Laboratoire d'étude en géophysique et océanographie spatiale, Toulouse, France
  • 5University of St. Andrews, Scotland
  • 6Planetary Science Institute, Tucson, USA
  • 7University of Exeter, UK

GLIMS, Global Land Ice Measurements from Space, is an initiative that involves ~250 analysts from 34 countries and has the purpose of mapping all glaciers in the world (excluding the Greenland and Antarctic ice sheets) on a periodic basis.  The GLIMS Glacier Database, which became an official product of the NASA NSIDC DAAC (Distributed Active Archive Center) in 2019, contains time series of glacier outlines from different data sources.  Various parts or facies of glaciers are mapped, including the full glacier extent, debris-covered parts, internal rock outcrops, and glacial lakes.  The Randolph Glacier Inventory (RGI) is a snapshot map of glaciers, with one outline per glacier, as close as possible to a target date.

In the last year, GLIMS and the RGI working group have been working closely together to ingest new data into GLIMS and to improve GLIMS and RGI software tools. The goal is to improve data completeness and quality and to make the creation of the RGI smoother and more transparent (Maussion et al., EGU22-4484).  New data include approximately 60,000 outlines from 14 regions in all parts of the Earth, with times ranging from the Little Ice Age to 2018. Software improvements include more quality-control checks and constraints, such as separating multi-polygons into individual ones. 

The presentation will provide an overview on the latest data additions and software developments in GLIMS and the synergy with RGI production.

How to cite: Raup, B., Maussion, F., Paul, F., Berthier, E., Bolch, T., Kargel, J., and Racoviteanu, A.: More data and increased automation leads to better quality for GLIMS and RGI glacier data sets, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10563, https://doi.org/10.5194/egusphere-egu22-10563, 2022.