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

231 to 240 of 5,248 Results
Network Common Data Form - 814.3 KB - MD5: 66706431f74f303e69c22c72af3e200b
Uploaded with pyDataverse 2026-07-06 16:53
Comma Separated Values - 20.6 MB - MD5: 034638ab7c5f8070b1ff607f7eb8664b
Uploaded with pyDataverse 2026-07-06 16:51
Network Common Data Form - 13.7 MB - MD5: a5656a59b46d8f940bf234f303e58559
Uploaded with pyDataverse 2026-07-06 16:52
Comma Separated Values - 26.6 KB - MD5: 1e3ce93cc3c0ed93d41f6d08792cd2f3
Uploaded with pyDataverse 2026-07-06 16:54
Network Common Data Form - 270.3 KB - MD5: 23ccc8f0f0eb3660455d786ebc8090a3
Uploaded with pyDataverse 2026-07-06 16:53
Comma Separated Values - 318.0 KB - MD5: 6948c340fe0b5486c55aa4567e7869a1
Uploaded with pyDataverse 2026-07-06 17:52
Network Common Data Form - 532.0 KB - MD5: 3471856ef8655531b6a8fce2faa4f5fe
Uploaded with pyDataverse 2026-07-06 17:53
Comma Separated Values - 6.1 MB - MD5: d1fa0da40b7646742ab393429d85d98b
Uploaded with pyDataverse 2026-07-06 17:53
Network Common Data Form - 2.7 MB - MD5: 1c3fbcd75b047c0b46bd1b663994ebd8
Uploaded with pyDataverse 2026-07-06 17:52
Comma Separated Values - 11.2 KB - MD5: b2751b51ac17253f9911af6ed0dbf834
Uploaded with pyDataverse 2026-07-06 17:52
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.