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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Comma Separated Values - 400.0 KB - MD5: 51592427f416fa1110df511f2db9868f
Regional discharge. Git hash: 93f8ed6
Comma Separated Values - 400.5 KB - MD5: ca86c8b4e1f26d29c868650e3f0db989
Regional error. Git hash: 93f8ed6
Plain Text - 376.0 KB - MD5: c12ecf9fca3d7004a5dc43f9fde205de
Regional discharge, coverage, and error. Git hash: 93f8ed6
Comma Separated Values - 3.3 MB - MD5: 3744336d594242b18b41da25554f75da
Sector coverage. Git hash: 93f8ed6
Comma Separated Values - 9.1 MB - MD5: 0a0685ed0dc0692bf82bc74a89c78261
Sector discharge. Git hash: 93f8ed6
Comma Separated Values - 9.5 MB - MD5: 4e572da8d5c3c541d9f48e70fe6b75e3
Sector error. Git hash: 93f8ed6
Plain Text - 6.8 MB - MD5: 4068aa9a03e9210b2751acf72cec333b
Sector discharge, coverage, and error. Git hash: 93f8ed6
Network Common Data Form - 1.2 GB - MD5: 0598747535b86f632dd6b6f45e27ee9d
Data
PNG Image - 3.4 MB - MD5: 654d9d5f54a84020b7c0e8afa6ae300b
Image
Oct 9, 2025 - pypromice v1.7.0
Python Source Code - 2.0 KB - MD5: 539b4397b1585188ff9199593e1913a0
Uploaded with GitHub Action from GEUS-Glaciology-and-Climate/pypromice.
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