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

301 to 310 of 4,180 Results
Network Common Data Form - 36.9 MB - MD5: 35d1ef894de42c81be36f9cf92704ca0
Uploaded with pyDataverse 2025-04-03 15:13
Comma Separated Values - 79.7 KB - MD5: e4bd2f506e4d967e4d3c82f499d7e3d3
Uploaded with pyDataverse 2025-04-03 15:13
Network Common Data Form - 398.2 KB - MD5: 8cbdf311e5b9d347b5cd637a24895367
Uploaded with pyDataverse 2025-04-03 15:14
Comma Separated Values - 2.2 MB - MD5: 0df69c13931739f31c4840c8b7e13b1d
Uploaded with pyDataverse 2025-04-03 15:46
Network Common Data Form - 2.0 MB - MD5: 33662ba61470bd33eadd54ba928ce74c
Uploaded with pyDataverse 2025-04-03 15:46
Comma Separated Values - 50.7 MB - MD5: 16b375708e321ed77fee6fc0132946bf
Uploaded with pyDataverse 2025-04-03 15:46
Network Common Data Form - 33.5 MB - MD5: 9e5c13b9b77ebf0110830055898e003a
Uploaded with pyDataverse 2025-04-03 15:46
Comma Separated Values - 79.2 KB - MD5: be0763fa2b60997a039816a96cccb5c6
Uploaded with pyDataverse 2025-04-03 15:47
Network Common Data Form - 397.6 KB - MD5: 2923267725531e90cb9451f6c9226fef
Uploaded with pyDataverse 2025-04-03 15:47
Comma Separated Values - 13.0 KB - MD5: d742fa54d5da181bce42b5eb104a8235
Uploaded with pyDataverse 2025-04-03 16:18
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.