2024 Workshop: Data sciences for whole atmosphere models
Fabrizio Sassi,
Chih-Ting Hsu (early career),
Jeff Klenzing,
Nick Dietrich (student)
This session invites presentations with focus on numerical simulations and integrations of atmospheric and ionospheric observations from the ground into geospace. The use of emerging data science techniques to better leverage existing observational and modeled data will be discussed. This workshop calls on synergy between state-of-the-art models and data sciences to advance the prediction capability and the physical understanding of the whole atmosphere and ionosphere system. Presentations including theoretical work, data analysis, and instrument development are also encouraged.
This workshop is merged to "Advances in Data Science and Data Assimilation for an integrated system from the ground into geospace"
The Space Atmosphere Interaction Region (SAIR) is a crucial environment where space weather effects impact our technology and society, and where influences from solar wind and magnetosphere interact strongly with the lower atmosphere forcing. Yet observational measurements of various atmospheric and ionospheric properties throughout SAIR do not exist. The complex interactions and underlying processes for driving the dramatic SAIR variability are still poorly understood. To gain new insights, this session calls for community discussions on applications of data sciences in whole atmosphere and ionosphere models. Leveraging available observations with state-of-the-art models is a vital step towards the prediction and the physical understanding of the SAIR system.