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 - 64.3 MB - MD5: d6432d028c7296626f92177a9ca38738
Uploaded with pyDataverse 2026-09-01 15:36
Network Common Data Form - 43.5 MB - MD5: 65f0f80490b7385d8516cb4c50e4c941
Uploaded with pyDataverse 2026-09-01 15:34
Comma Separated Values - 86.7 KB - MD5: 809d356e1a59e7954d3d5688619e6785
Uploaded with pyDataverse 2026-09-01 15:36
Network Common Data Form - 428.6 KB - MD5: 8a267f18665d0d27118ee64f04e31087
Uploaded with pyDataverse 2026-09-01 15:35
Comma Separated Values - 1.3 MB - MD5: f39b861dd8a075c3584a7665cf33de2c
Uploaded with pyDataverse 2026-09-01 15:30
Network Common Data Form - 1.3 MB - MD5: 82ed94083ffe4536c82b320b0ab64747
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Comma Separated Values - 33.9 MB - MD5: 8db4220d054f1344e61508eed3ed3847
Uploaded with pyDataverse 2026-09-01 15:28
Network Common Data Form - 22.0 MB - MD5: b3bb998d8e9ba4462344d3a116f669d2
Uploaded with pyDataverse 2026-09-01 15:30
Comma Separated Values - 47.0 KB - MD5: 477e13607176a18692ad876ae3b37302
Uploaded with pyDataverse 2026-09-01 15:29
Network Common Data Form - 393.9 KB - MD5: 958c4ecc8e4637ffb81ae0a3c2489b53
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