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

321 to 330 of 5,287 Results
Network Common Data Form - 16.2 MB - MD5: 8281e8fbd0a920a0b5ca563c50622532
Uploaded with pyDataverse 2026-05-01 14:15
Comma Separated Values - 41.1 KB - MD5: a1f5d24e3fcce12a8f0e41570b13b3cd
Uploaded with pyDataverse 2026-05-01 14:13
Network Common Data Form - 472.8 KB - MD5: c173af42becbfb397d9272788cd85453
Uploaded with pyDataverse 2026-05-01 14:14
Comma Separated Values - 1.8 MB - MD5: a1ac1f1f14c93efaf8bfcdeeda0ad659
Uploaded with pyDataverse 2026-05-01 14:26
Network Common Data Form - 1.5 MB - MD5: 1e907fa8ebcfd483093ee93d33b3fa09
Uploaded with pyDataverse 2026-05-01 14:27
Comma Separated Values - 43.9 MB - MD5: 3c955b169a88aa429e387f9773d558a6
Uploaded with pyDataverse 2026-05-01 14:27
Network Common Data Form - 24.8 MB - MD5: bc83b94d27d7473e8a1476b7db0ee803
Uploaded with pyDataverse 2026-05-01 14:25
Comma Separated Values - 61.1 KB - MD5: 5ab84c92875d9d287a8b5763a8effd40
Uploaded with pyDataverse 2026-05-01 14:26
Network Common Data Form - 402.5 KB - MD5: abc827e69f3e94c649ba1f450f723c86
Uploaded with pyDataverse 2026-05-01 14:25
Comma Separated Values - 1.2 MB - MD5: f2f6cc365bd5a9b4a6e768645907cc19
Uploaded with pyDataverse 2026-05-01 15:54
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.