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

231 to 240 of 5,219 Results
Network Common Data Form - 524.0 KB - MD5: 99602f5929eecc2ad0b86b3062e4fd60
Uploaded with pyDataverse 2026-04-01 14:58
Comma Separated Values - 2.2 MB - MD5: 5829622888f1bbf8cc5eb5e2e719527d
Uploaded with pyDataverse 2026-04-01 15:45
Network Common Data Form - 1.9 MB - MD5: 329a010778583a5bfa5321386cbfc8d8
Uploaded with pyDataverse 2026-04-01 15:44
Comma Separated Values - 55.1 MB - MD5: 812bb40454d1082416769f457ba1e5c4
Uploaded with pyDataverse 2026-04-01 15:46
Network Common Data Form - 33.1 MB - MD5: 4e3b8c2f9b74ee2cf19840bdba528162
Uploaded with pyDataverse 2026-04-01 15:45
Comma Separated Values - 75.5 KB - MD5: d30da710aa85074071b83a512e76be59
Uploaded with pyDataverse 2026-04-01 15:46
Network Common Data Form - 402.2 KB - MD5: 715fcd93f240ceb9c360b5a6ccd8b4ae
Uploaded with pyDataverse 2026-04-01 15:44
Comma Separated Values - 2.5 MB - MD5: c5c8db68fd28ee696b0789b9c013b3e3
Uploaded with pyDataverse 2026-04-01 14:40
Network Common Data Form - 2.1 MB - MD5: 87beed29aa01a62f16836404f8cea7f5
Uploaded with pyDataverse 2026-04-01 14:38
Comma Separated Values - 60.9 MB - MD5: c07bdfc2509d91a5360e4e614af39b23
Uploaded with pyDataverse 2026-04-01 14:39
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.