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

151 to 160 of 4,238 Results
Network Common Data Form - 523.9 KB - MD5: 0fdb56bc35b5a717c189a071e63d0279
Uploaded with pyDataverse 2025-04-03 15:07
Comma Separated Values - 1.5 MB - MD5: 2d84060b98b2b03d73a04898dacbae67
Uploaded with pyDataverse 2025-04-03 15:52
Network Common Data Form - 1.2 MB - MD5: 7cf61b13824d5e3bc81901eae107fa3e
Uploaded with pyDataverse 2025-04-03 15:53
Comma Separated Values - 35.5 MB - MD5: bb42316a63b88cdd5d41ba31ca56502f
Uploaded with pyDataverse 2025-04-03 15:52
Network Common Data Form - 13.7 MB - MD5: 09095b241f944acf6d61e09aefcc431a
Uploaded with pyDataverse 2025-04-03 15:52
Comma Separated Values - 55.4 KB - MD5: 1f66efd201386c2d653b49a404391d74
Uploaded with pyDataverse 2025-04-03 15:51
Network Common Data Form - 474.1 KB - MD5: a07f890d96f7e49e44ddc1769d0b020f
Uploaded with pyDataverse 2025-04-03 15:52
Comma Separated Values - 3.0 MB - MD5: f194e59803d63d26b85ac4435829b372
Uploaded with pyDataverse 2025-04-03 15:34
Network Common Data Form - 2.4 MB - MD5: 662ce2e8deb3a83ee586241f337f669e
Uploaded with pyDataverse 2025-04-03 15:34
Comma Separated Values - 63.6 MB - MD5: 1ea62051a54f84aff36d50118cdd53bd
Uploaded with pyDataverse 2025-04-03 15:35
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.