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

251 to 260 of 5,248 Results
Network Common Data Form - 29.3 MB - MD5: af1d4ef15623b8de82dd8e2f0e2f5d2c
Uploaded with pyDataverse 2026-07-06 18:07
Comma Separated Values - 116.2 KB - MD5: 228f1c6de507fa248f44804f11aa0d69
Uploaded with pyDataverse 2026-07-06 18:08
Network Common Data Form - 509.4 KB - MD5: 76518badbc2628152857f709191b97a3
Uploaded with pyDataverse 2026-07-06 18:09
Comma Separated Values - 3.2 MB - MD5: 609a9d49c21e196cd5c42b3db9b6b973
Uploaded with pyDataverse 2026-07-06 16:25
Network Common Data Form - 2.4 MB - MD5: 16b9a2df90f3b0410c592b93e76e1645
Uploaded with pyDataverse 2026-07-06 16:26
Comma Separated Values - 72.8 MB - MD5: eb3df335e2fe8c2b858bd0df01feab2d
Uploaded with pyDataverse 2026-07-06 16:25
Network Common Data Form - 29.1 MB - MD5: ade53957bcea399921d8a4b2cb25cc76
Uploaded with pyDataverse 2026-07-06 16:26
Comma Separated Values - 112.2 KB - MD5: 0145f95b15398cd77e05fc0eb1b26518
Uploaded with pyDataverse 2026-07-06 16:25
Network Common Data Form - 507.8 KB - MD5: b7940b0e4ec2d0055b5950e4ff9d7c08
Uploaded with pyDataverse 2026-07-06 16:26
Comma Separated Values - 1.6 MB - MD5: 7249ed5002651438319098e30cacfb4d
Uploaded with pyDataverse 2026-07-06 17:51
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.