Summary
Despite its importance, snow water equivalent (SWE) monitoring remains an unresolved issue in modern hydrology. This is a consequence of the limitations of orbital sensors, the large spatial variability of the snowpack and the combined errors of meteorological forcings and numerical models. Snow data assimilation (SDA) of remotely sensed data into numerical models is one way to advance the estimation of SWE distribution in remote regions. However, implement SDA initiatives in forested areas is challenging, limiting the development of SDA initiatives in more than 20% of the Northern Hemisphere. The aim of this project is to train the candidate in sophisticated radiative transfer modelling and AI, to implement snow-forest interactions in data assimilation pipelines for a better understanding of snow freshwater resources. This main objective will be developed through the creation of an international network of experts, to train the researcher in different related topics. This includes Dr Jessica Lundquis (Outgoing phase host) from the University of Washington, an authority on forest-snow interactions, and Dr Simon Gascoin (returning phase host) from CESBIO (Toulouse, France), with long experience in multidisciplinary snow remote sensing. The results will be used to enhance the current capabilities of the MuSA tool, an open source and highly scalable data assimilation system developed by the researcher. The project will be the first effort to infer SWE in forest through SDA of spacial imagery, and therefore is of great interest for many stakeholders and scientists. The project is designed with an obvious focus on training the researcher in new techniques but also in soft skills thanks to the mentoring programs of both the University of Washington and CESBIO. The ultimate goal of the project is to improve the career prospects of the researcher, making him an authority in snow science and providing the scientific community with a new and sophisticated SDA tool.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101108674 |
Start date: | 01-10-2023 |
End date: | 30-09-2025 |
Total budget - Public funding: | - 203 159,00 Euro |
Cordis data
Original description
Despite its importance, snow water equivalent (SWE) monitoring remains an unresolved issue in modern hydrology. This is a consequence of the limitations of orbital sensors, the large spatial variability of the snowpack and the combined errors of meteorological forcings and numerical models. Snow data assimilation (SDA) of remotely sensed data into numerical models is one way to advance the estimation of SWE distribution in remote regions. However, implement SDA initiatives in forested areas is challenging, limiting the development of SDA initiatives in more than 20% of the Northern Hemisphere. The aim of this project is to train the candidate in sophisticated radiative transfer modelling and AI, to implement snow-forest interactions in data assimilation pipelines for a better understanding of snow freshwater resources. This main objective will be developed through the creation of an international network of experts, to train the researcher in different related topics. This includes Dr Jessica Lundquis (Outgoing phase host) from the University of Washington, an authority on forest-snow interactions, and Dr Simon Gascoin (returning phase host) from CESBIO (Toulouse, France), with long experience in multidisciplinary snow remote sensing. The results will be used to enhance the current capabilities of the MuSA tool, an open source and highly scalable data assimilation system developed by the researcher. The project will be the first effort to infer SWE in forest through SDA of spacial imagery, and therefore is of great interest for many stakeholders and scientists. The project is designed with an obvious focus on training the researcher in new techniques but also in soft skills thanks to the mentoring programs of both the University of Washington and CESBIO. The ultimate goal of the project is to improve the career prospects of the researcher, making him an authority in snow science and providing the scientific community with a new and sophisticated SDA tool.Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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