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OSPREI: A Coupled Approach to Modeling CME-Driven Space Weather With Automatically Generated, User-Friendly Outputs

Presentation #301.03 in the session Predicting solar wind properties across the heliosphere with integrated modeling efforts (empirical or first-principles).

Published onOct 20, 2022
OSPREI: A Coupled Approach to Modeling CME-Driven Space Weather With Automatically Generated, User-Friendly Outputs

Coronal mass ejections (CMEs) drive space weather activity at Earth and throughout the solar system. Current CME-related space weather predictions rely on information reconstructed from coronagraphs, sometimes from only a single viewpoint, to drive a simple interplanetary propagation model, which only gives the arrival time or limited additional information. We present the coupling of three established models into OSPREI (Open Solar Physics Rapid Ensemble Information), a new tool that describes Sun-to-Earth CME behavior, including the location, orientation, size, shape, speed, arrival time, and internal thermal and magnetic properties, on the timescale needed for forecasts. First, Forecasting a CME’s Altered Trajectory (ForeCAT) describes the trajectory that a CME takes through the solar corona. Second, ANother Type of Ensemble Arrival Time Results simulates the propagation, including expansion and deformation, of a CME in interplanetary space and determines the evolution of internal properties via conservation laws. Finally, ForeCAT In situ Data Observer produces in situ profiles for a CME’s interaction with a synthetic spacecraft. OSPREI includes ensemble modeling by varying each input parameter to probe any uncertainty in their values, yielding probabilities for all outputs. Standardized visualizations are automatically generated, providing easily accessible, essential information for space weather forecasting. We show OSPREI results for a CMEs observed in the corona on 22 April and 09 May 2021. We approach these CME as a forecasting proof-of-concept, using information analogous to what would be available in real time rather than fine-tuning input parameters to achieve a best fit for a detailed scientific study. The OSPREI “prediction” shows good agreement with the arrival time and in situ properties.

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