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.
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Sep 16, 2024 - Automatic weather stations
How, P..; Lund, M. C.; Bahbah, R.; Ahlstrøm, A.P.; Fausto, R.S.; Larsen, S.H.; Mankoff, K.D.; Vandecrux, B.; Wright, P.J., 2023, "pypromice v1.4.2", https://doi.org/10.22008/FK2/3TSBF0, GEUS Dataverse, V15
The pypromice toolbox is for retrieving, processing and handling PROMICE (Programme for Monitoring of the Greenland Ice Sheet) and GC-Net (Greenland Climate Network) automated weather station (AWS) data. The content here reflects pypromice releases for processing and handling the...
Sep 16, 2024 - pypromice v1.4.2
Python Source Code - 8.8 KB - MD5: 6bf2fdf7dca89815dba5b6244efd4085
Sep 16, 2024 - pypromice v1.4.2
Python Source Code - 507 B - MD5: ec4ca0a4e60b8cf447d9d5ca54999cd3
Sep 16, 2024 - pypromice v1.4.2
Python Source Code - 20.7 KB - MD5: be0c3710030c11f7ff6c1aae7b62b265
Sep 16, 2024 - pypromice v1.4.2
Unknown - 1.9 KB - MD5: 3a53e6211e034cdce468c1b17c615bc1
Sep 16, 2024 - pypromice v1.4.2
Python Source Code - 5.9 KB - MD5: 80a5d9f9284771fe70045af178bddc32
Sep 16, 2024 - pypromice v1.4.2
Python Source Code - 2.4 KB - MD5: 7a3d5f0d7196788851cf42aa003e5c11
Sep 16, 2024 - pypromice v1.4.2
Python Source Code - 5.5 KB - MD5: 332054439748d593ee222353340311f8
Sep 16, 2024 - pypromice v1.4.2
Unknown - 517 B - MD5: 9862a0c99884d7e1d5bf707940ba24ad
Sep 16, 2024 - pypromice v1.4.2
Unknown - 219 B - MD5: 390ea8d5787b7c0ae05dc53904ed111a
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