Master & SIE Projects
CRYOS
First simulations with the new community snow model (“Helmut”)
Contact (supervisor)
Professor Michael Lehning : [email protected]
Description:
- Helmut will be the future French/Swiss flagship land surface model and is currently developed between CEN (MeteoFrance) and SLF Davos. The numerical core has been developed and the work will be to execute first model simulations and compare to the state of the art model SNOWPACK. Work will be at SLF Davos.
Introducing a new snow model into the weather and climate model ICON
Contact (supervisors)
Nander Wever : [email protected]
Professor Michael Lehning : [email protected]
Description:
- The work conducts validation studies with the new simplified snow model NIX as part of the TERRA land surface scheme in ICON. The task consists in simulating snow cover dynamics over the Alps and validating against observations.
Training machine learning models to predict energy production and demand during extreme weather events and testing their application for (future) scenarios
Contact (supervisors)
Professor Michael Lehning : [email protected]
Pauline Rivoire : [email protected]
Albin Cintas : [email protected]
Description:
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The thesis aims at forecasting the energy demand and the energy production from renewable energy sources in Switzerland, based on present conditions and future scenarios.
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As inputs, several meteorological variables such as temperature, radiation, wind and pressure on a large scale, will be provided, as well as installed capacities, energy consumption and production in the country for the past 20 years. The model will have to accurately predict the energy consumed and produced. Different machine learning models will be investigated, such as Random forests, LSTM, Gradient boosting methods, neural networks, with a focus on the parameter tuning and explainability.
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Once the model and its features are selected, a second step will consist in testing the model with synthetic time series with more extremes to simulate alternative scenarios. The variability of the future scenarios can be characterized with different extreme occurrences, installed capacities, and demand trends. The synthetic data will be the basis for a statistical analysis of problematic situations, in which demand cannot be satisfied. Such events may not only result from individual extreme weather but come during for example extended periods of not so extreme events such as droughts or foggy winter weeks.
WSL institute for Snow and Avalanche Research SLF, in Davos
Master’s internships at SLF
Spatial interpolation of Automatic Weather Station (AWS) data, (Despiking): Internship Despiking
Contact:
Dr. Mathias Bavay : [email protected]
081 41 70 265
Master’s thesis at SLF
Studying the atmospheric circulation and their related snow effects using observational methods at SLF Davos
Contact:
Dr. Sergi Gonzalez Herrero : [email protected]
Description:
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The tasks consist on deploying a LIDAR system in the Flüela valley during winter and use the data of the new Tschuggen station to study the effects of mesoscale circulations (katabatic winds, rotors, etc.) on the snow in an Alpine Valley.
Studying the capacity of CRYOWRF on simulating snow redistribution at SLF Davos
Contact:
Dr. Sergi Gonzalez Herrero : [email protected]
Description:
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The task consists on observing and mapping the snow redistribution using drones. After, the event will be simulated using the coupled snow-atmospheric model CRYOWRF to compare it with the observational dataset.
Studying the heat flux representation by different reanalysis and climate models.
Contact:
Dr. Sergi Gonzalez Herrero : [email protected]
Description:
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The tasks will be compiling heat fluxes by different datasets in Antarctica and analyze them to study the uncertainty of reanalysis and climate models in Antarctica. Also set simulations with CRYOWRF to understand the importance of grid resolution.