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

401 to 410 of 5,248 Results
Network Common Data Form - 5.5 MB - MD5: 645ad3acc93ccbe7c49c69ea04c0c81e
Uploaded with pyDataverse 2026-07-06 16:40
Comma Separated Values - 15.1 KB - MD5: 5e3a7b91c86518d1d8d5b53548560b58
Uploaded with pyDataverse 2026-07-06 16:41
Network Common Data Form - 338.8 KB - MD5: ebf51908999c8101b0d2a244dd7f7997
Uploaded with pyDataverse 2026-07-06 16:39
Comma Separated Values - 1.8 MB - MD5: 6128b419582d179917ad3daf60e6f2cb
Uploaded with pyDataverse 2026-07-06 18:06
Network Common Data Form - 1.6 MB - MD5: ae52ae3c1214243e1e83b952882cd82b
Uploaded with pyDataverse 2026-07-06 18:05
Comma Separated Values - 45.3 MB - MD5: 2b630cf14195bd3e2f566d983a141e0a
Uploaded with pyDataverse 2026-07-06 18:04
Network Common Data Form - 28.6 MB - MD5: 1cc11451e7a08ab816760747c553c88b
Uploaded with pyDataverse 2026-07-06 18:05
Comma Separated Values - 63.7 KB - MD5: 3a8c2c802d08204790c609f0a93687ee
Uploaded with pyDataverse 2026-07-06 18:06
Network Common Data Form - 383.5 KB - MD5: e819c83e947654ec0c2eba2bdbb8cd7c
Uploaded with pyDataverse 2026-07-06 18:05
Comma Separated Values - 2.0 MB - MD5: 99b7467486f89f61efcacbe8660e848b
Uploaded with pyDataverse 2026-07-06 17:45
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.