This 5-day course provides a comprehensive overview of the usage of meteorological satellite observations in operational numerical weather prediction (NWP).
It includes a series of lectures and practical sessions covering fundamental theoretical concepts through to practical applications in modern state-of-the-art data assimilation systems.
Programme
In our lectures and practicals we'll be covering:
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Data assimilation methods, including the role of background/observation errors, bias correction, coupled approaches
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Radiative transfer and other observation operators
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Key satellite observations from passive and active sensors (e.g., microwave, infrared, visible, radio occultation, scatterometers, Atmospheric Motion Vectors, etc)
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Machine learning with satellite data for NWP
More information on the contents of this course will be published on this website in due time.
Requirements
This course is sponsored by EUMETSAT and is open to anybody with a suitable background.
Prior knowledge in the quantitative use of satellites data or optimal estimation concepts is desirable.
We target primarily early career scientists starting in the field of satellite data assimilation or related subjects, including PhD students with relevant experience.
This training is in-person, and all lectures will be given in English.