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

261 to 270 of 5,219 Results
Network Common Data Form - 398.5 KB - MD5: 5af1ca8645ceb5b6a605c8f7444c60f1
Uploaded with pyDataverse 2026-04-01 15:54
Comma Separated Values - 3.4 MB - MD5: f2706968659f60f40269e4f74c951291
Uploaded with pyDataverse 2026-04-01 15:35
Network Common Data Form - 2.5 MB - MD5: 648a9bd7a6e804503d43987c5e662ed6
Uploaded with pyDataverse 2026-04-01 15:34
Comma Separated Values - 72.1 MB - MD5: 81312ba36b5aa784b163236c779ade8b
Uploaded with pyDataverse 2026-04-01 15:35
Network Common Data Form - 29.0 MB - MD5: 10fa0f2d6616682b091d7d24d3c54c9d
Uploaded with pyDataverse 2026-04-01 15:34
Comma Separated Values - 117.1 KB - MD5: a0f4eee61385afe78499b589752bca7f
Uploaded with pyDataverse 2026-04-01 15:36
Network Common Data Form - 524.3 KB - MD5: 745be9ed4a8497e14566a1ea419947c5
Uploaded with pyDataverse 2026-04-01 15:36
Comma Separated Values - 3.2 MB - MD5: 936af55d6be276de79ca037227a7017d
Uploaded with pyDataverse 2026-04-01 14:04
Network Common Data Form - 2.4 MB - MD5: 38c55f44a5522ef6a9691e48a3ebd98d
Uploaded with pyDataverse 2026-04-01 14:05
Comma Separated Values - 72.1 MB - MD5: 10e610f4338fb3fe1aae39684d910b57
Uploaded with pyDataverse 2026-04-01 14:04
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.