PINE - RT
Version: 1.0This plasmasphere model is a machine-learning model that produces a nowcast of the plasma density in the whole equatorial plane every hour. It uses the time history of the solar wind features and of the Kp index as inputs and it makes the nowcast of the plasma density in a few seconds, making it especially suitable for real-time operations.
This model has been developed as part of the PAGER (Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation) project (https://www.spacepager.eu/).
Caveats:
When there are too many missing values of solar wind and Kp index, the machine learning model misses input features and cannot produce an output. Therefore the plot produced by the post-processing plotting tool will be blank.
Inputs
solar wind, Kp
Outputs
plasmaspheric density
Model is time-dependent.
Domains
- Magnetosphere / Inner Magnetosphere / Plasmasphere
Space Weather Impacts
- Near-earth radiation and plasma environment (aerospace assets functionality)
Publications
- Zhelavskaya I., N. Aseev, Y. Y. Shprits (2021), A combined neural network- and physics-based approach for modeling plasmasphere dynamics.
- Zhelavskaya, I., Shprits, Y. Y., & Spasojević, M. (2017), Empirical modeling of the plasmasphere dynamics using neural networks.
- S. Bianco, B. Haas and Y. Y. Shprits (2023), PINE-RT: An operational real-time plasmasphere model
Relevant Links
Contacts
- Stefano Bianco, GFZ (Model Developer)
- Yihua Zheng, NASA GSFC CCMC (CCMC Model Host)
Publication Policy
In addition to any model-specific policy, please refer to the General Publication Policy.