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

171 to 180 of 4,238 Results
Network Common Data Form - 1.4 MB - MD5: 0828f7df2af66c9385e96531cc1afc45
Uploaded with pyDataverse 2025-04-03 15:10
Comma Separated Values - 32.5 MB - MD5: 7805430984d943d1d2a438f43e0b09b4
Uploaded with pyDataverse 2025-04-03 15:10
Network Common Data Form - 20.8 MB - MD5: a04cdbae6ef31511e78a859fae24a5b4
Uploaded with pyDataverse 2025-04-03 15:10
Comma Separated Values - 52.0 KB - MD5: c5628915ee6f47a8db28008d194171fe
Uploaded with pyDataverse 2025-04-03 15:11
Network Common Data Form - 393.5 KB - MD5: 139948acc6c6c357a3273c4b7f3bb46d
Uploaded with pyDataverse 2025-04-03 15:11
Comma Separated Values - 2.4 MB - MD5: 2110f047ad0bcef4bb94f308fb81e8fb
Uploaded with pyDataverse 2025-04-03 15:36
Network Common Data Form - 2.1 MB - MD5: 9be499b94040f67bf563638de89afbfd
Uploaded with pyDataverse 2025-04-03 15:37
Comma Separated Values - 54.1 MB - MD5: 640d20bf632702ca6ce1526c87b35164
Uploaded with pyDataverse 2025-04-03 15:35
Network Common Data Form - 36.0 MB - MD5: 43516f894606c7756608dd78d07e2605
Uploaded with pyDataverse 2025-04-03 15:36
Comma Separated Values - 84.2 KB - MD5: 1dc51f47a45c97ccf83943104d2fcea3
Uploaded with pyDataverse 2025-04-03 15:36
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.