Work Description

Title: Dataset for the "Response of the Geospace System to the Solar Wind Dynamic Pressure Decrease on 11 June 2017: Numerical Models and Observations" Open Access Deposited

http://creativecommons.org/licenses/by-nc/4.0/
Attribute Value
Methodology
  • The simulation data were generated through the use of the following models: the Block Adaptive Tree Solarwind Roe Upwind Scheme (BATS-R-US), Comprehensive Ring Current Model (CRCM), Ridley Ionosphere Model (RIM) and the Global Ionosphere Thermosphere Model (GITM). The simulations were performed on the Yellowstone and Cheyenne Supercomputer Clusters provided by National Center for Atmospheric Research (NCAR) Computational and Information Systems Laboratory, sponsored by the National Science Foundation.
Description
  • 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.
Creator
Depositor
  • dcsoztrk@umich.edu
Contact information
Discipline
Funding agency
  • National Science Foundation (NSF)
ORSP grant number
  • AGS1400998
Keyword
Citations to related material
Resource type
Last modified
  • 08/14/2019
Published
  • 11/16/2018
DOI
License
To Cite this Work:
Ozturk, D. (2018). Dataset for the "Response of the Geospace System to the Solar Wind Dynamic Pressure Decrease on 11 June 2017: Numerical Models and Observations" [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/Z26T0JW6

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