In 2007, Denmark launched the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) to assess changes in the mass balance of the ice sheet. The two major contributors to the ice sheet mass loss are surface melt and a larger production of icebergs through faster ice flow. PROMICE is focused on both processes. Ice movement and discharge is tracked by satellites and GPSs. The surface mass balance is monitored by a network of weather stations in the melt zone of the ice sheet, providing ground truth data to calibrate mass budget models.

The Greenland Climate Network (GC-Net) was established in 1995 by Prof. Konrad Steffen at CIRES, to obtain knowledge of the mass gain and climatology of the ice sheet. The programme was funded by the USA until 2020, at which point Denmark assumed responsibility for the operation and maintenance of the weather station network. The snowfall and climatology are monitored by a network of weather stations in the accumulation zone of the ice sheet, supplemented by satellite-derived data products.

Together, the two monitoring programmes deliver data about the mass balance of the Greenland ice sheet in near real-time. Explore our project dataverses and datasets below.
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Mar 4, 2026 - pypromice v1.10.0
Python Source Code - 1.7 KB - MD5: 7bd8bda04e9284075dfb2044e20cc87d
Uploaded with GitHub Action from GEUS-Glaciology-and-Climate/pypromice.
Mar 4, 2026 - pypromice v1.10.0
Python Source Code - 15.5 KB - MD5: 80c2228d4c4cd86d2b638bd2090cba1c
Uploaded with GitHub Action from GEUS-Glaciology-and-Climate/pypromice.
Adobe PDF - 101.6 KB - MD5: 71015ed8dce6541fb94cb31df280943d
Uploaded with pyDataverse 2026-03-03 16:10
Comma Separated Values - 2.9 KB - MD5: 13ce4e5612dac26df6c4f4e7a8a499a4
Uploaded with pyDataverse 2026-03-03 16:09
Comma Separated Values - 6.0 KB - MD5: 073328bdd206ac49b81b17c30585a628
Uploaded with pyDataverse 2026-03-03 16:10
Comma Separated Values - 13.9 KB - MD5: 7fb0a9cb4ec3469add48484503dab76d
Uploaded with pyDataverse 2026-03-03 16:09
Comma Separated Values - 2.8 MB - MD5: d386e727860cf98b28adb0e44daf4736
Uploaded with pyDataverse 2026-03-03 15:37
Network Common Data Form - 2.0 MB - MD5: 3769cd1274272f3a376b28a01cd774f5
Uploaded with pyDataverse 2026-03-03 15:37
Comma Separated Values - 67.7 MB - MD5: a689d4eb2807c84b178cc24514c1a37a
Uploaded with pyDataverse 2026-03-03 15:36
Network Common Data Form - 25.8 MB - MD5: 5f5d7d186b3178f66a6a503cadd65726
Uploaded with pyDataverse 2026-03-03 15:36
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