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

161 to 170 of 4,238 Results
Network Common Data Form - 27.6 MB - MD5: bca06cfb81fb321f1e0d91cc3b8e86e5
Uploaded with pyDataverse 2025-04-03 15:35
Comma Separated Values - 108.7 KB - MD5: 83d07ab585b311d2e4d61eb3f1248853
Uploaded with pyDataverse 2025-04-03 15:34
Network Common Data Form - 523.0 KB - MD5: 76667df0d5d6e4e8f0f667cd79e937b2
Uploaded with pyDataverse 2025-04-03 15:35
Comma Separated Values - 153.0 KB - MD5: ff40cc14f279033f0a7df904c4d8e8a9
Uploaded with pyDataverse 2025-04-03 15:05
Network Common Data Form - 344.0 KB - MD5: d31fe6a5bc18aae6236fe1646ab19e59
Uploaded with pyDataverse 2025-04-03 15:06
Comma Separated Values - 3.7 MB - MD5: 18a53c25a9cf9cd051a0f7bb2d82f0a7
Uploaded with pyDataverse 2025-04-03 15:05
Network Common Data Form - 2.3 MB - MD5: 31e90e35c0ef36427176047e3fdddd5b
Uploaded with pyDataverse 2025-04-03 15:06
Comma Separated Values - 5.6 KB - MD5: 9c7673efb1140339f4c4c43bd0056f42
Uploaded with pyDataverse 2025-04-03 15:05
Network Common Data Form - 247.9 KB - MD5: 1f648aa85cb2a2a8c38a0daf7a0900ec
Uploaded with pyDataverse 2025-04-03 15:05
Comma Separated Values - 1.4 MB - MD5: d4be0868574356547b46862efd712d36
Uploaded with pyDataverse 2025-04-03 15:11
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.