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Archive
by Altube, P., Bech, J., Argemí, O., Rigo, T., Pineda, N., Collis, S. and Helmus, J.
Abstract:
In Doppler weather radars, the presence of unfolding errors or outliers is a well-known quality issue for radial velocity fields estimated using the dual–pulse repetition frequency (PRF) technique. Postprocessing methods have been developed to correct dual-PRF outliers, but these need prior application of a dealiasing algorithm for an adequate correction. This paper presents an alternative procedure based on circular statistics that corrects dual-PRF errors in the presence of extended Nyquist aliasing. The correction potential of the proposed method is quantitatively tested by means of velocity field simulations and is exemplified in the application to real cases, including severe storm events. The comparison with two other existing correction methods indicates an improved performance in the correction of clustered outliers. The technique proposed is well suited for real-time applications requiring high-quality Doppler radar velocity fields, such as wind shear and mesocyclone detection algorithms, or assimilation in numerical weather prediction models.
Reference:
Altube, P., Bech, J., Argemí, O., Rigo, T., Pineda, N., Collis, S. and Helmus, J., 2017: Correction of Dual-PRF Doppler Velocity Outliers in the Presence of AliasingJournal of Atmospheric and Oceanic Technology, 34, 1529-1543.
Bibtex Entry:
@Article{Altube2017,
  author        = {Altube, P. and Bech, J. and Argemí, O. and Rigo, T. and Pineda, N. and Collis, S. and Helmus, J.},
  title         = {Correction of Dual-PRF Doppler Velocity Outliers in the Presence of Aliasing},
  journal       = {Journal of Atmospheric and Oceanic Technology},
  year          = {2017},
  volume        = {34},
  number        = {7},
  pages         = {1529-1543},
  abstract      = {In Doppler weather radars, the presence of unfolding errors or outliers is a well-known quality issue for radial velocity fields estimated using the dual–pulse repetition frequency (PRF) technique. Postprocessing methods have been developed to correct dual-PRF outliers, but these need prior application of a dealiasing algorithm for an adequate correction. This paper presents an alternative procedure based on circular statistics that corrects dual-PRF errors in the presence of extended Nyquist aliasing. The correction potential of the proposed method is quantitatively tested by means of velocity field simulations and is exemplified in the application to real cases, including severe storm events. The comparison with two other existing correction methods indicates an improved performance in the correction of clustered outliers. The technique proposed is well suited for real-time applications requiring high-quality Doppler radar velocity fields, such as wind shear and mesocyclone detection algorithms, or assimilation in numerical weather prediction models.},
  copublication = {7: 5 Es, 2 USA},
  doi           = {10.1175/JTECH-D-16-0065.1},
  eprint        = {https://doi.org/10.1175/JTECH-D-16-0065.1},
  keywords      = {Wind; Data quality control; Radars/Radar observations; Remote sensing; Filtering techniques; Statistical techniques;},
  owner         = {hymexw},
  timestamp     = {2019-01-25},
  url           = {https://doi.org/10.1175/JTECH-D-16-0065.1},
}