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

201 to 210 of 5,287 Results
Comma Separated Values - 46.5 KB - MD5: dcb34a24faeeee528a4a6496d9752b4d
Uploaded with pyDataverse 2026-05-01 14:35
Network Common Data Form - 407.0 KB - MD5: c4affdc5e12f060fb7622cc858279982
Uploaded with pyDataverse 2026-05-01 14:35
Comma Separated Values - 2.4 MB - MD5: 5d84e35d29d2502742a86dc5479a6898
Uploaded with pyDataverse 2026-05-01 14:10
Network Common Data Form - 2.1 MB - MD5: 4dcda5bf6d52692267bbad4292bf8404
Uploaded with pyDataverse 2026-05-01 14:11
Comma Separated Values - 58.7 MB - MD5: 15dc280b4b374238319b35f15480953a
Uploaded with pyDataverse 2026-05-01 14:09
Network Common Data Form - 37.3 MB - MD5: 10722bf850c3c21ca0c5ef4c61027de8
Uploaded with pyDataverse 2026-05-01 14:09
Comma Separated Values - 81.1 KB - MD5: 752f423b8f00f2374c9147b900848840
Uploaded with pyDataverse 2026-05-01 14:10
Network Common Data Form - 439.4 KB - MD5: d4f3b213323c5db07d279d017690faf1
Uploaded with pyDataverse 2026-05-01 14:09
Comma Separated Values - 259.4 KB - MD5: 317079f769ea814d27019069e68662b6
Uploaded with pyDataverse 2026-05-01 14:46
Network Common Data Form - 543.7 KB - MD5: 663a999994627c96fbeaabf863cc9df0
Uploaded with pyDataverse 2026-05-01 14:46
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.