CRAMPON – Cryospheric Monitoring and Prediction Online
How much are Swiss glaciers melting right now? In the CRAMPON project we develop an operational modeling tool to nowcast and predict mass balance and runoff of all Swiss glaciers. We assimilate both field data and near real-time remote sensing observations into the tool’s workflow, and use ensemble approaches for uncertainty assessment.
In Alpine regions, glacier runoff plays a significant role in the hydrological budget. Knowledge about glacier mass changes can therefore be critical, especially for hydropower operations and issues of water supply. In situ mass balance measurements, however, are demanding in terms of both time and manpower, and are thus not always available. The “CRAMPON” project (Cryospheric Monitoring and Prediction Online) addresses this difficulty and aims at developing a model-based, near real-time glacier monitoring and prediction platform for Switzerland. The operational modeling workflow relies on meteorological analyses, whilst field-based data from the Glacier Monitoring Switzerland (GLAMOS, www.glamos.ch) program and elevation changes from repeated Digital Elevation Models (DEMs) are used for calibration and validation. Additionally, optical and radar satellite data are assimilated as in situ constraints into the workflow. Data assimilation is a scarcely explored field in glaciology and mass balance studies. <o:p></o:p>
The basis for parts of the preprocessing is the Open Global Glacier Model (OGGM, www.oggm.org). In the first project phase, OGGM is extended with a workflow to digest operational high-resolution, spatially distributed daily meteorological products. The model includes regionally and locally relevant processes, such as variations in snow cover distribution and albedo aging. We implement an ensemble of mass balance models and test the suitability of repeated Digital Elevation Models (DEMs) for calibration. Calibration of each of the more than 1500 Swiss glaciers is challenging but inevitable to correctly model processes on subannual time scales. Model ensemble validation is done with field measurements from the GLAMOS program.<o:p></o:p>
In a second phase, the added value of data assimilation for operational glaciological modeling will be investigated. Among the assimilated data, we will use extents of melt areas derived from satellite radar data and the glacier snow covered fraction derived from optical imagery. Different assimilation techniques will be compared, including Ensemble Kalman Filtering, Ensemble Smoothing and Ensemble Smoothing with Multiple Data Assimilation.<o:p></o:p>
In a third phase, the calculations will be extended to deliver runoff from glacierized catchments. Results will be made publicly available on a web portal. The portal will include (a) a “status map” displaying the current state of every glacier with respect to the long-term average, and (b) plots showing the temporal evolution of the current mass balance year with respect to long-term conditions (see preview figure). Forecasts of glacier mass balance and runoff will complement the platform. Model forecasts skills from several days up to the seasonal scale will be examined in a hindcasting framework.<o:p></o:p>
The operational workflow resulting from this work will be one of the first near-real time information platforms on glacier mass balance and runoff. This is anticipated to enable better management of both water resources and hydropower operations. In the context of climate services, the platform will support decision making related to electricity production and water allocation.
2017 - 2020
Johannes Marian Landmann