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
The research that produced this data focused on conducting a statistical comparison between horizontal winds modeled with GITM and those derived from the accelerometer aboard the GOCE satellite. The winds from GITM and GOCE were compared by constructing their respective probability densities under different levels of geomagnetic activity, and by distributing them as a function of geomagnetic activity, magnetic latitude, magnetic local time, day-of-the-year, and solar radio flux.
The modeling research conducted to produce this dataset focuses on the solar wind dynamic pressure drop events and how they affect the Earth's intrinsically coupled Magnetosphere, Ionosphere and Thermosphere systems. This study specifically focuses on the 11 June 2017 event, where the solar wind dynamic pressure dropped significantly following a period of higher pressure. We model the response to this pressure drop using University of Michigan Space Weather Modeling Framework ( http://csem.engin.umich.edu/tools/swmf/). The simulation results were created using BATS-R-US and GITM models. The observational data required for model comparisons were taken from OMNI ( https://omniweb.gsfc.nasa.gov) and CDAWeb ( https://cdaweb.gsfc.nasa.gov/sp_phys/) Databases.
Ozturk, D. S., Zou, S., Slavin, J. A., & Ridley, A. J. ( 2019). Response of the geospace system to the solar wind dynamic pressure decrease on 11 June 2017: Numerical models and observations. Journal of Geophysical Research: Space Physics, 124, 2613– 2627. https://doi.org/10.1029/2018JA026315
The global magnetosphere-ionosphere-thermosphere (M-I-T) system is intrinsically coupled and susceptible to external drivers such as solar wind dynamic pressure enhancements. In order to understand the large-scale dynamic processes in the M-I-T system due to the compression from the solar wind, the 17 March 2015 sudden commencement was studied in detail using global numerical models. This data set is comprised of the simulation data
generated from these models. and NOTE: The following changes were made to this dataset on March 28, 2018. First, two mp4 files were added. Second, the symbol representing "degree" was not rendering properly in the README file. The symbols were removed and replaced with the word "degree". Third, the metadata in the "methodology" and "description" fields were revised for content and clarity. On April 16, 2018 a citation to the corresponding article was added to the metadata record.
