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

51 to 60 of 4,225 Results
Network Common Data Form - 2.5 MB - MD5: d6be182da096b68a8272116e400c6c55
Uploaded with pyDataverse 2025-04-03 15:08
Comma Separated Values - 71.2 MB - MD5: a10b01106c501b91dbf21d80cb71c4a3
Uploaded with pyDataverse 2025-04-03 15:08
Network Common Data Form - 29.1 MB - MD5: 3e341cc99082d6f73cd2130c03d905a7
Uploaded with pyDataverse 2025-04-03 15:08
Comma Separated Values - 118.0 KB - MD5: 41c719580d058600aa5880a57a37cca8
Uploaded with pyDataverse 2025-04-03 15:09
Network Common Data Form - 523.9 KB - MD5: 4225a2bc7990b929682eeda06ffd8d8d
Uploaded with pyDataverse 2025-04-03 15:07
Comma Separated Values - 1.5 MB - MD5: 2db2ceac98cb5ad64840773cce02e332
Uploaded with pyDataverse 2025-04-03 15:39
Network Common Data Form - 1.5 MB - MD5: fd7416774bbcc0eed4d9a5ca1823d15f
Uploaded with pyDataverse 2025-04-03 15:38
Comma Separated Values - 38.0 MB - MD5: a2d2e48468680e5c6d1e61eda68b8255
Uploaded with pyDataverse 2025-04-03 15:39
Network Common Data Form - 24.0 MB - MD5: 19bd83251b2e9ac27be47fc89b670e45
Uploaded with pyDataverse 2025-04-03 15:39
Comma Separated Values - 53.9 KB - MD5: 65255c7fca2ff0604bb9daca32a9b923
Uploaded with pyDataverse 2025-04-03 15:40
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.