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

851 to 860 of 4,176 Results
DYE-2_daily.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 2.9 MB - MD5: f45eaf4a7f1d696c6de3c963ba03af07
EastGRIP.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 15.1 MB - MD5: e5465df6ac6586dc785e419597f79584
EastGRIP_daily.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 643.4 KB - MD5: 1ede1e44fbd03b0c99057cb41762d344
GC-Net_location.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 3.0 KB - MD5: 3b4b4f9b77c8a6e1f1bdd6fa20dfe5ae
GITS.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 49.9 MB - MD5: fe64c6388acfd591da34f00569790fc9
GITS_daily.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 2.1 MB - MD5: eecbc7abcb252a698c22d37ac53e2486
Humboldt.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 62.9 MB - MD5: 6a677c083db01e616e73653feea38693
Humboldt_daily.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 2.6 MB - MD5: a2f7d6601704ff6f1a77355623562755
JAR1.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 52.9 MB - MD5: a71fca69d1bdaae02f6812de242ffe85
JAR1_daily.csv
Jul 17, 2024 - GC-Net Level 1 historical automated weather station data
Comma Separated Values - 2.2 MB - MD5: 9adf799642ae06fb42214b9b03a6b1e3
Add Data

Log in to create a dataverse or add a dataset.

Log In
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.