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

761 to 770 of 4,128 Results
Nov 27, 2024 - pypromice v1.5.0
Unknown - 640 B - MD5: 05035afa9e416c20e3f2a3a6f9358a23
Nov 27, 2024 - pypromice v1.5.0
Python Source Code - 9.3 KB - MD5: 66abc150a69126b099825ea3ce26d3bd
Nov 27, 2024 - pypromice v1.5.0
Plain Text - 180 B - MD5: 43af9ae5e5b71426e50ce24a2b669ac0
Nov 27, 2024 - pypromice v1.5.0
Python Source Code - 7.1 KB - MD5: 658b41d1a05ef5b3cb09f42fe1c889d1
Nov 27, 2024 - pypromice v1.5.0
Python Source Code - 2.5 KB - MD5: 29f563576c3b71966fde32ee7857aa8a
Nov 27, 2024 - pypromice v1.5.0
Python Source Code - 3.9 KB - MD5: 36e73d84cfe2be3e83d6164f64aa88ca
Nov 27, 2024 - pypromice v1.5.0
Unknown - 1.1 KB - MD5: 1dab4b922f9d277b47869c1e09a56ee0
Nov 27, 2024 - pypromice v1.5.0
Unknown - 4.2 KB - MD5: 34c706283035bf6bb90fe9a8ed607962
Nov 27, 2024 - pypromice v1.5.0
Unknown - 111 B - MD5: dcd30e48c0cdbf2e680eb7d822d2b855
Nov 27, 2024 - pypromice v1.5.0
Python Source Code - 7.6 KB - MD5: c41ac16071f8ed89bb0c06119eb2a7d2
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.