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

341 to 350 of 4,674 Results
Network Common Data Form - 516.6 KB - MD5: 8a41e865d0158e295db5a34752764fbc
Uploaded with pyDataverse 2026-01-01 14:30
Comma Separated Values - 5.1 MB - MD5: 4152932f626a6674f45297ad4cc08d0f
Uploaded with pyDataverse 2026-01-01 14:29
Network Common Data Form - 3.6 MB - MD5: 4f7801b2ffc5cc686d0a2831ab88e6f1
Uploaded with pyDataverse 2026-01-01 14:29
Comma Separated Values - 7.9 KB - MD5: 288d311d14365904cce91a04034b34bd
Uploaded with pyDataverse 2026-01-01 14:29
Network Common Data Form - 356.5 KB - MD5: db348bded006d9c28ae848ded4f46909
Uploaded with pyDataverse 2026-01-01 14:28
Comma Separated Values - 2.4 MB - MD5: 13060be5dbe30e2523b76b23dd3f8ef9
Uploaded with pyDataverse 2026-01-01 15:37
Network Common Data Form - 2.2 MB - MD5: 28a36342d2e73942a9954f410f8aecd0
Uploaded with pyDataverse 2026-01-01 15:38
Comma Separated Values - 59.7 MB - MD5: 1b494c6849daf7b1c3f9acb37de7a07a
Uploaded with pyDataverse 2026-01-01 15:37
Network Common Data Form - 39.1 MB - MD5: 23f1771d7717355e99a6ac1463b59aa9
Uploaded with pyDataverse 2026-01-01 15:36
Comma Separated Values - 82.8 KB - MD5: 6b6c6cd7f608974f25e67ce620767da7
Uploaded with pyDataverse 2026-01-01 15:37
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.