Ensemble Solar Global Magnetic Field Modeling

Astronomy and Astrophysics – Astrophysics

Scientific paper

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[7524] Solar Physics, Astrophysics, And Astronomy / Magnetic Fields, [7924] Space Weather / Forecasting, [7959] Space Weather / Models

Scientific paper

The ability to forecast geoeffective space weather events is critically dependent on the estimation of the global solar photospheric magnetic field distribution as input to coronal and heliospheric models. Currently, the solar magnetic field can only be recorded for approximately half of the solar surface at any given time. Since the rotation period of the Sun as observed from Earth is approximately 27 days, any global map of the solar magnetic field includes data more than 13 days old. In this poster, we describe our efforts and progress toward developing the Air Force Data Assimilative Photospheric flux Transport (ADAPT) model. ADAPT incorporates data assimilation with a modified version of the Worden and Harvey (WH) photospheric magnetic flux transport model. The flux transport model evolves the solar magnetic flux by incorporating rotational, meridional, and super-granular diffusive transport processes when measurements are not available. The modified WH model version now utilizes an ensemble of model realizations using different model parameters constrained by the estimated errors of each parameter. In addition, the modified version allows for the hemispheres to be decoupled with regards to differential rotation and meridional flow. When new observations are available, the modeled flux is updated using an Ensemble Least Squares (EnLS) estimation method. The EnLS data assimilation utilizes model and observational uncertainties, where the model error is estimated from the ensemble variance. Besides providing an estimate of the model uncertainty, the different flux transport model realizations provide model parameter feedback. For model parameter feedback, we compare polar fluxes obtained by different ensemble realizations, using different meridional flow profiles at high latitude, with data recorded during periods when the poles are well observed. In addition, the challenges and benefits of ensemble modeling with regards to selecting metric parameters for model feedback and validation on different timescales are discussed.

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