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Annales Geophysicae An interactive open-access journal of the European Geosciences Union
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Volume 32, issue 3
Ann. Geophys., 32, 197–206, 2014
https://doi.org/10.5194/angeo-32-197-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Ann. Geophys., 32, 197–206, 2014
https://doi.org/10.5194/angeo-32-197-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Regular paper 11 Mar 2014

Regular paper | 11 Mar 2014

Automated identification and tracking of polar-cap plasma patches at solar minimum

R. Burston1, K. Hodges2, I. Astin1, and P. T. Jayachandran3 R. Burston et al.
  • 1University of Bath, Bath, UK
  • 2University of Reading, Reading, UK
  • 3University of New Brunswick, Fredericton, Canada

Abstract. A method of automatically identifying and tracking polar-cap plasma patches, utilising data inversion and feature-tracking methods, is presented. A well-established and widely used 4-D ionospheric imaging algorithm, the Multi-Instrument Data Assimilation System (MIDAS), inverts slant total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers to produce images of the free electron distribution in the polar-cap ionosphere. These are integrated to form vertical TEC maps. A flexible feature-tracking algorithm, TRACK, previously used extensively in meteorological storm-tracking studies is used to identify and track maxima in the resulting 2-D data fields. Various criteria are used to discriminate between genuine patches and "false-positive" maxima such as the continuously moving day-side maximum, which results from the Earth's rotation rather than plasma motion. Results for a 12-month period at solar minimum, when extensive validation data are available, are presented. The method identifies 71 separate structures consistent with patch motion during this time. The limitations of solar minimum and the consequent small number of patches make climatological inferences difficult, but the feasibility of the method for patches larger than approximately 500 km in scale is demonstrated and a larger study incorporating other parts of the solar cycle is warranted. Possible further optimisation of discrimination criteria, particularly regarding the definition of a patch in terms of its plasma concentration enhancement over the surrounding background, may improve results.

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