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.
Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

211 to 220 of 4,674 Results
Network Common Data Form - 45.8 MB - MD5: 5913f122912d9613f8d921b52e8e59e4
Uploaded with pyDataverse 2026-01-01 14:48
Comma Separated Values - 92.0 KB - MD5: 0e51b8f6ccccef41a327b983a1949f55
Uploaded with pyDataverse 2026-01-01 14:47
Network Common Data Form - 440.8 KB - MD5: 65a7169f9e87d33072d769c30e05f5dc
Uploaded with pyDataverse 2026-01-01 14:47
Comma Separated Values - 2.5 MB - MD5: dc3cc6523e67547c6a0fa0e11dd989e7
Uploaded with pyDataverse 2026-01-01 14:36
Network Common Data Form - 2.2 MB - MD5: 6a80a354a50923661294f74ace7edaae
Uploaded with pyDataverse 2026-01-01 14:34
Comma Separated Values - 62.5 MB - MD5: cb132046d115e092e5f0b24cbfd7cc93
Uploaded with pyDataverse 2026-01-01 14:35
Network Common Data Form - 41.6 MB - MD5: 278f5580e08704f84ffea5c09df86bcc
Uploaded with pyDataverse 2026-01-01 14:35
Comma Separated Values - 85.1 KB - MD5: 0876a0ac4823dcbfef2db2ac50029ba9
Uploaded with pyDataverse 2026-01-01 14:35
Network Common Data Form - 413.0 KB - MD5: 30241266a5e51b26e2525942fd35f667
Uploaded with pyDataverse 2026-01-01 14:36
Comma Separated Values - 213.5 KB - MD5: a2f002ff0f90072a58e9442796fac581
Uploaded with pyDataverse 2026-01-01 15:30
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.