CEDAR email: AGU Session: SA016 - Models, Observations, and Data Assimilation for Orbital Space Weather Forecasting

[Aaron Bukowski]

Dear Colleagues,

We would like to extend an invitation for you to submit an abstract to our
AGU session titled:
(SA016) Models, Observations, and Data Assimilation for Orbital Space
Weather Forecasting

Geospace is defined as the region of space delineated by the interaction of
the magnetosphere and upper atmosphere with the solar wind, encompassing
both orbital and cis-lunar space. The rapidly increasing number of
operational satellites and space debris in geospace, particularly in Low
Earth Orbit, requires improved forecasting models to ensure the safety and
sustainability of human exploration and satellite operations. This session
focuses on improving nowcasts and forecasts of the geospace environment
through developments in theory, numerical simulation and empirical models,
observations, data assimilation, machine learning and other techniques that
merge models and data. We invite presentations on physics-based and
data-driven modeling of the geospace system, theoretical aspects of this
system and its interaction with solar outputs; existing, new, or planned
space weather observations, both space- and ground-based; as well as
methods to improve nowcasting and forecasting of geospace variability
through data assimilation and development of machine learning models.

The abstract submission deadline is Wednesday, 30 July, 2025, 23:59 EDT.

We hope you consider contributing to this session,

Aaron L Bukowski, on behalf of session conveners:
Jeffrey P Thayer
Thomas E Berger
Pauline M Dredger
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