Dein Suchergebnis zum Thema: have

Extreme Droughts in Mountain Regions: EMERGE

https://www.wsl.ch/de/projekte/emerge-extreme-droughts-in-mountain-regions/

As the climate continues to change, Switzerland edges closer to a future in which extreme drought in the Alps is increasingly likely – and could push water and ecological systems to their limits. The EMERGE project studies past extreme droughts in mountain regions to help us better understand, and prepare for, potential impacts in the future.
simplified characterisation techniques, failing to accurately capture how droughts have

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Understanding self-sustained crack propagation in snow – the key to predicting avalanche size

https://www.wsl.ch/de/projekte/understanding-self-sustained-crack-propagation-in-snow/

If an avalanche is triggered, how large will it be? To answer this question, we will analyze unique data from field experiments to provide new insights into the process controlling avalanche release and avalanche size.
While in recent years computer models have been used to study this process, there

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StillbergDAT

https://www.wsl.ch/de/projekte/stillbergdat/

This ETH-Domain ORD Program Contribute Project aims at curating and uploading the existing data of the European Long-term treeline Ecosystem Research (eLTER) site Stillberg, Switzerland, was established in to national and international ORD platforms (EnviDat, DEIMS-SDR).
In almost 50 years, we have collected a wealth of ecological and environmental data

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Remote Sensing Lecture Series

https://www.wsl.ch/de/ueber-die-wsl/veranstaltungen-und-kurse/remote-sensing-lecture-series/

The WSL remote sensing group established a lecture series on current topics in the field of remote sensing. Besides latest developments in remote sensing techniques and sensors, special focus is laid on their usability and relevance for practice.
In this webinar we will have five in-house and five external presentations from renowned

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Real-time cleansing of snow and weather data for operational avalanche forecasting

https://www.wsl.ch/de/projekte/real-time-cleansing-of-snow-and-weather-data-for-operational-avalanche-forecasting/

The data for avalanche forecasting need to be accessible in high quality as soon as these become available. Any measurement errors, anomalies and data gaps diminish forecast accuracy. We aim to develop algorithms for real-time data cleansing by applying state-of-the-art machine learning approaches.
Hence, the completion of the proposed research will have a major impact, in particular

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