Assimilative Upper Atmosphere Model TIE-GCM PDAF

Earth’s upper atmosphere begins at roughly 90 km altitude and is an ionized gas mixture whose state is strongly influenced by solar radiation and solar wind. It is also coupled to Earth’s magnetosphere, plasmasphere, and the lower atmosphere. The state of this gas, including its composition, temperatures, wind velocities, ionization, and conductivities, varies in time and space and affects the orbit, lifetime, and instrumentation of Low Earth orbiting Satellites.
Upper-atmosphere models have limited predictive skill because of assumptions and simplifications of physical processes, discretization in time and space, and idealized external forcings. Data assimilation is a frequently used tool that improves model predictions by combining them with observations, weighted by the uncertainties of both.
The NCAR TIEGCM (Thermosphere-Ionosphere-Electrodynamics General Circulation Model) is a numerical model of Earth’s upper atmosphere. TIE-GCM PDAF is a fork augmented with data assimilation capabilities using the Parallel Data Assimilation Framework (PDAF), developed at the Alfred Wegener Institute in Bremerhaven. The model uncertainty is represented by an ensemble of TIE-GCM instances with perturbed inputs, which run in parallel on an HPC system. At each analysis step, a (localized) ensemble Kalman filter (ESTKF) updates the state prediction, leading to a more realistic description of Earth’s upper atmosphere.
TIE-GCM PDAF has been used to enhance TIE-GCM prediction of the upper atmosphere by assimilating accelerometer-derived mass densities from geodetic satellite missions such as CHAMP, Swarm-C, GRACE, and GRACE-FO. It also allows the assimilation of semi-empirical models that aggregate multiple observations and supports assimilation of integrated observations such as VTEC.
TIE-GCM PDAF is intended for research, academic, and non-profit use only; the TIE-GCM license applies.

References:

• Corbin, A., & Kusche, J. (2026a). PDAF Binding for TIE-GCM [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.23103187.
• Corbin, A., & Kusche, J. (2026b). TIE-GCM PDAF [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.23102803.
• Corbin, A., & Kusche, J. (2026c). TIE-GCM PDAF 3 Simulation of the 2024 Gannon Geomagnetic Storm Assimilating Mass Densities from the TOLEOS Project. bonndata.  https://doi.org/10.60507/FK2/QMNFKG.
• Corbin, A. (2025). Enhancing Numerical Simulation of Mass Density in Earth’s Upper Atmosphere using Data Assimilation [Thesis, Universitäts- und Landesbibliothek Bonn]. https://doi.org/10.48565/bonndoc-596.
• Corbin, A., & Kusche, J. (2022). Improving the estimation of thermospheric neutral density via two-step assimilation of in situ neutral density into a numerical model. Earth, Planets and Space, 74(1), 183. https://doi.org/10.1186/s40623-022-01733-z.

Contact:

If you have any questions regarding this data set, please contact Dr.-Ing. Armin Corbin