EGU24-10791, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-10791
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

A Novel Empirical EUV Model with Uncertainty Quantification

Daniel Brandt1 and Aaron Ridley2
Daniel Brandt and Aaron Ridley
  • 1Michigan Technology University, Michigan Tech Research Institute, United States of America (daabrand@mtu.edu)
  • 2Department of Climate and Space Sciences and Engineering, University of Michigan, United States of America (ridley@umich.edu)

The ubiquitous usage of solar proxies in the nowcasting and forecasting of ionospheric and thermospheric conditions has seen the application of a multitude of techniques to ensure high fidelity representation of the effects of solar EUV forcing on the atmospheric state. The inherent limitations of reliance on a single solar proxy have encouraged the development of numerous EUV irradiance models in which the EUV irradiance in multiple bands is reconstructed from F10.7 solar flux. These models have progressed from lower to higher resolution, as well as higher-fidelity parameterization of time-varying components of the EUV irradiance. We contribute to this development in presenting NEUVAC, a simple, but novel empirical solar EUV model trained on FISM2 data. NEUVAC models the solar EUV irradiance from F10.7 and 81-day averaged F10.7 in 59 wavelength bands between 1 and 1750 Angstroms using a nonlinear parameterization, and performs uncertainty quantification in each band with the assistance of exclusively data-driven methods that exploit the dynamical properties of EUV, and intercorrelations between irradiance in each band. The irradiances provided by NEUVAC highlight the success of the FISM2 program, are suitable for direct ingestion into global ionosphere-thermosphere models, and are structured so that ensembles of irradiance estimates can be generated for principled forecasting and statistical assessment of downstream parameters generated by ionosphere-thermosphere models.

How to cite: Brandt, D. and Ridley, A.: A Novel Empirical EUV Model with Uncertainty Quantification, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10791, https://doi.org/10.5194/egusphere-egu24-10791, 2024.