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

41 to 50 of 4,589 Results
Network Common Data Form - 1.6 MB - MD5: 76cb05ece98a3ddc38e9278607a73e91
Uploaded with pyDataverse 2025-12-03 16:53
Comma Separated Values - 41.1 MB - MD5: 65db244d8d7e386be857adae59cf8df7
Uploaded with pyDataverse 2025-12-03 16:54
Network Common Data Form - 25.8 MB - MD5: 2c453ac62ef1fe1fd5d13c1942e1e3bc
Uploaded with pyDataverse 2025-12-03 16:54
Comma Separated Values - 56.2 KB - MD5: 449113b369798657ebfbb0a71d2c26b8
Uploaded with pyDataverse 2025-12-03 16:55
Network Common Data Form - 475.5 KB - MD5: 96b226e7a34b0d977ee329b8b8ae8fb3
Uploaded with pyDataverse 2025-12-03 16:54
Comma Separated Values - 1.3 MB - MD5: 2035b1d6a917c231437f64a37161c5c4
Uploaded with pyDataverse 2025-12-03 17:07
Network Common Data Form - 1.3 MB - MD5: 87097c5e16357dc5a62806def4464397
Uploaded with pyDataverse 2025-12-03 17:06
Comma Separated Values - 33.5 MB - MD5: 4ce6e70e39185273d2d38653906a722b
Uploaded with pyDataverse 2025-12-03 17:07
Network Common Data Form - 22.6 MB - MD5: 2e09b5d837cb68ea516a1fc6f76159a6
Uploaded with pyDataverse 2025-12-03 17:05
Comma Separated Values - 45.9 KB - MD5: 9453887b9b30cc71b98d54c161106923
Uploaded with pyDataverse 2025-12-03 17:06
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.