Abstract
Global maps of the solar photospheric magnetic flux are fundamental drivers for simulations of the corona and solar wind and therefore are important predictors of geoeffective events. However, observations of the solar photosphere are only made intermittently over approximately half of the solar surface. The Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model uses localized ensemble Kalman filtering techniques to adjust a set of photospheric simulations to agree with the available observations. At the same time, this information is propagated to areas of the simulation that have not been observed. ADAPT implements a local ensemble transform Kalman filter (LETKF) to accomplish data assimilation, allowing the covariance structure of the flux-transport model to influence assimilation of photosphere observations while eliminating spurious correlations between ensemble members arising from a limited ensemble size. We give a detailed account of the implementation of the LETKF into ADAPT. Advantages of the LETKF scheme over previously implemented assimilation methods are highlighted.
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Acknowledgements
This research was primarily supported by NASA Living With a Star project #NNA13AB92I, “Data Assimilation for the Integrated Global-Sun Model”. Additional support was provided by the Air Force Office of Scientific Research project R-3562-14-0, “Incorporation of Solar Far-Side Active Region Data within the Air Force Data Assimilative Photospheric Flux Transport (ADAPT) Model”. The photospheric observations used in Figures 1, 3, and 4 were provided by SOLIS-VSM part of the NSO Integrated Synoptic Program (NISP), managed by the National Solar Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA), Inc. under a cooperative agreement with the National Science Foundation. Approved for public release: LA-UR-14-27938.
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Hickmann, K.S., Godinez, H.C., Henney, C.J. et al. Data Assimilation in the ADAPT Photospheric Flux Transport Model. Sol Phys 290, 1105–1118 (2015). https://doi.org/10.1007/s11207-015-0666-3
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DOI: https://doi.org/10.1007/s11207-015-0666-3