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 - 72.8 MB - MD5: fd6458209368e69e6e0b912ee02c6998
Uploaded with pyDataverse 2026-06-01 14:36
Network Common Data Form - 28.9 MB - MD5: cf7895ff3a4f360ed933858569a5d7d7
Uploaded with pyDataverse 2026-06-01 14:38
Comma Separated Values - 114.0 KB - MD5: 2e304994a6087dd32d2190127fd75aa9
Uploaded with pyDataverse 2026-06-01 14:37
Network Common Data Form - 524.6 KB - MD5: 18d29d54a2622c7535c0f29a0b6c083e
Uploaded with pyDataverse 2026-06-01 14:37
Comma Separated Values - 1.7 MB - MD5: e15a3bbec1ed76ce64f5b4835196add7
Uploaded with pyDataverse 2026-06-01 16:12
Network Common Data Form - 1.3 MB - MD5: d52a1caf2606233d2ac16c8efd2974a2
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Comma Separated Values - 40.4 MB - MD5: 72b82b4de64971025288c7085c97f5b1
Uploaded with pyDataverse 2026-06-01 16:11
Network Common Data Form - 16.6 MB - MD5: 7b6998bdb8b0926ad6d63b86c13e2442
Uploaded with pyDataverse 2026-06-01 16:11
Comma Separated Values - 58.7 KB - MD5: 865418d6abf9b403f249a30a09e7b257
Uploaded with pyDataverse 2026-06-01 16:10
Network Common Data Form - 478.8 KB - MD5: d4bcc3a202c785e5dd24bf93e473095f
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