This research was completed to introduce a state-of-the-art Venus GCM to the modeling community. Validation studies were performed to give credence to the model's results. and This data set is made available under a Creative Commons Public Domain
license (CC0 1.0). The python scripts contained were ran on macOS
Monterey version 12.7 with Python 3.9.
Numpy version: 1.19.4
Pandas version: 1.2.0
Ponder, Brandon & Ridley, Aaron J. & Bougher, Stephen W. & Pawlowski, D. & Brecht, A. (2023). The Venus Global Ionosphere-Thermosphere Model (V-GITM): A Coupled Thermosphere and Ionosphere Formulation. JGR Planets. In Press.
This research was completed to statistically validate that a data-model refinement technique could integrate real measurements to remove bias from physics-based models via changing the forcing parameters such as the thermal conductivity coefficients.
Ponder, B. M., Ridley, A. J., Goel, A., & Bernstein, D. S. (2023). Improving forecasting ability of GITM using data-driven model refinement. Space Weather, 21, e2022SW003290. https://doi.org/10.1029/2022SW003290
