EGU23-9724
https://doi.org/10.5194/egusphere-egu23-9724
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

A new algorithm to separate meteor trail echoes from ionospheric radar scatter

Magnus Ivarsen1,2, Glenn Hussey1, Jean-Pierre St-Maurice1,3, Adam Lozinsky1, Draven Galeschuk1, Brian Pitzel1, and Kathryn McWilliams1
Magnus Ivarsen et al.
  • 1Department of Physics and Engineering Physics, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
  • 2University of Oslo, Institute of Physics, Department of Mathematics and Natural Sciences, Oslo, Norway
  • 3Department of Physics and Astronomy, University of Western Ontario, London, Ontario, Canada

Coherent scatter echoes from meteors entering Earth’s atmosphere and those from the ionospheric E-region overlap: echoes of both types are seen at altitudes between 95 km -105 km. The physical origin of plasma irregularities produced by disintegrating meteors naturally differ from that of ionospheric turbulence, and there is a need to distinguish between the two types of echoes. We present a novel algorithm to automatically sort through arbitrarily large datasets of radar echoes with accurate location data, classifying each echo as either meteoric or ionospheric in origin. The algorithm establishes a definition of clustering, in both time and space. We use data from ICEBEAR 3D, an experimental coherent scatter radar in Saskatchewan, Canada. We discuss the two classes of scatter echoes, and present statistical results from 2020, 2021. In future experiments, our proposed algorithm can be applied to both coherent and incoherent radar scatter, provided they come with 3D location information.

How to cite: Ivarsen, M., Hussey, G., St-Maurice, J.-P., Lozinsky, A., Galeschuk, D., Pitzel, B., and McWilliams, K.: A new algorithm to separate meteor trail echoes from ionospheric radar scatter, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9724, https://doi.org/10.5194/egusphere-egu23-9724, 2023.