Earth System Science Data (Dec 2024)

The PAZ polarimetric radio occultation research dataset for scientific applications

  • R. Padullés,
  • R. Padullés,
  • E. Cardellach,
  • E. Cardellach,
  • A. Paz,
  • A. Paz,
  • S. Oliveras,
  • S. Oliveras,
  • D. C. Hunt,
  • S. Sokolovskiy,
  • J.-P. Weiss,
  • K.-N. Wang,
  • F. J. Turk,
  • C. O. Ao,
  • M. de la Torre Juárez

DOI
https://doi.org/10.5194/essd-16-5643-2024
Journal volume & issue
Vol. 16
pp. 5643 – 5663

Abstract

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Polarimetric radio occultations (PROs) represent an augmentation of the standard radio occultation (RO) technique that provides precipitation and cloud vertical information along with the standard thermodynamic products. A combined dataset that contains both the PRO observable retrievals and the RO standard retrievals, the resPrf, has been developed with the aim of fostering the use of these unique observations and fully exploiting the scientific implication of having information about vertical cloud structures with an intrinsically collocated thermodynamic state of the atmosphere. This paper describes such a dataset and provides detailed information on the processing of the observations. The procedure followed at the University Corporation for Atmospheric Research (UCAR) to combine both horizontal (H) and vertical (V) observations to generate profiles equivalent to those in standard RO missions is described in detail, and the obtained refractivity is shown to be of equivalent quality compared to that from TerraSAR-X. The steps for the processing of the PRO observations are detailed, derived products such as the top of the signal are described, and validation is provided. Furthermore, the dataset contains the simulated ray trajectories for the PRO observation and collocated information with global satellite-based precipitation products, such as merged rain rate retrievals or passive microwave observations. These collocations are used for further validation of the PRO observations, and they are also provided within the resPrf profiles for additional use. It is also shown how accounting for external collocated information can significantly improve the effective PRO horizontal resolution, tackling one of the challenges of the technique. The resPrf dataset is publicly available at https://doi.org/10.20350/digitalCSIC/16137 (Padullés et al., 2024).