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 4,234 Results
Network Common Data Form - 431.8 KB - MD5: b452ad5c9eb5f6ce950e40913d775d9b
Uploaded with pyDataverse 2025-06-01 14:19
Comma Separated Values - 568.4 KB - MD5: fe8625c7914cbe57a31a9f8966faac8a
Uploaded with pyDataverse 2025-06-01 14:31
Network Common Data Form - 759.8 KB - MD5: ee0ab27dc68030da4989081899008f11
Uploaded with pyDataverse 2025-06-01 14:31
Comma Separated Values - 12.2 MB - MD5: 9391c14eb21a964804b9c639790618ff
Uploaded with pyDataverse 2025-06-01 14:31
Network Common Data Form - 8.6 MB - MD5: 275309f8d50951b0c056085fc661cff4
Uploaded with pyDataverse 2025-06-01 14:30
Comma Separated Values - 20.3 KB - MD5: 60e0ac76159858c34c0f43be2ff3299a
Uploaded with pyDataverse 2025-06-01 14:30
Network Common Data Form - 347.8 KB - MD5: abb97ed89cc2dc7cbca98bb83f04a491
Uploaded with pyDataverse 2025-06-01 14:31
Comma Separated Values - 2.9 MB - MD5: c8d69f4a4f1b1f50ff09f3ed26e1b693
Uploaded with pyDataverse 2025-06-01 14:51
Network Common Data Form - 2.1 MB - MD5: 5ed11232727bcbe512c8d5f68292060f
Uploaded with pyDataverse 2025-06-01 14:51
Comma Separated Values - 64.5 MB - MD5: 8abb47e228a9252609f044eb424d8d7b
Uploaded with pyDataverse 2025-06-01 14:50
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.