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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Comma Separated Values - 63.9 KB - MD5: 77e85ed20efeddf8c2b271e51ede708b
Uploaded with pyDataverse 2026-06-01 16:29
Network Common Data Form - 396.9 KB - MD5: 559681c0c42277aac7b20c48c9e72ed6
Uploaded with pyDataverse 2026-06-01 16:27
Comma Separated Values - 2.1 MB - MD5: 7b04e19c867aed3a5785fb66ec969386
Uploaded with pyDataverse 2026-06-01 16:07
Network Common Data Form - 1.9 MB - MD5: 7ccd8f07a967793f1604bedde812190f
Uploaded with pyDataverse 2026-06-01 16:07
Comma Separated Values - 54.1 MB - MD5: a87389c47352e4bb6344cbd7ad116dc8
Uploaded with pyDataverse 2026-06-01 16:05
Network Common Data Form - 35.7 MB - MD5: cb4fcaea3610c3eea21db79ea08d5630
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Comma Separated Values - 71.7 KB - MD5: 580904679bd90ebaf91cec26de8e1ae6
Uploaded with pyDataverse 2026-06-01 16:06
Network Common Data Form - 433.8 KB - MD5: de6beb06f441a4eba522bdec946ceb4e
Uploaded with pyDataverse 2026-06-01 16:05
Comma Separated Values - 3.3 MB - MD5: 6d905009f04cf43f1ed29f6f8d36ecb9
Uploaded with pyDataverse 2026-06-01 15:07
Network Common Data Form - 2.5 MB - MD5: a52a896235f26eb4c98656282383d994
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