Preprints
https://doi.org/10.5194/amt-2020-402
https://doi.org/10.5194/amt-2020-402

  28 Oct 2020

28 Oct 2020

Review status: a revised version of this preprint is currently under review for the journal AMT.

A method for random uncertainties validation and probing the natural variability with application to TROPOMI/Sentinel5P total ozone measurements

Viktoria F. Sofieva1, Hei Shing Lee1,2, Johanna Tamminen1, Christophe Lerot3, Fabian Romahn4, and Diego G. Loyola4 Viktoria F. Sofieva et al.
  • 1Finnish Meteorological Institute, Helsinki, Finland
  • 2University of Helsinki, Atmospheric Sciences Department, Finland
  • 3BIRA, Brussels, Belgium
  • 4German Aerospace Centre (DLR), Remote Sensing Technology Institute, Oberpfaffenhofen, Germany

Abstract. In this paper, we discuss the method for validation of random uncertainties in the remote sensing measurements based on evaluation of the structure function, i.e., root-mean-square differences as a function of increasing spatio-temporal separation of the measurements. The limit at the zero mismatch provides the experimental estimate of random noise in the data. At the same time, this method allows probing the natural variability of the measured parameter. As an illustration, we applied this method to the clear-sky total ozone measurements by TROPOMI/Sentinel-5P.

We found that the random uncertainties reported by the TROPOMI inversion algorithm, which are in the range 1–2 DU, agree well with the experimental uncertainty estimated by the structure function.

Our analysis of the structure function has shown the expected results on total ozone variability: it is significantly smaller in the tropics compared to mid-latitudes. At mid-latitudes, ozone variability is much larger in winter than in summer. The ozone structure function is anisotropic (being larger in latitudinal direction) at horizontal scales larger than 10–20 km. The structure function rapidly grows with the separation distance. At mid-latitudes in winter, the ozone values can differ by 5 % at separations 300–500 km.

The discussed method is a powerful tool in experimental estimates of the random noise in data and studies of natural variability and it can be used in various applications.

Viktoria F. Sofieva et al.

 
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

Viktoria F. Sofieva et al.

Viktoria F. Sofieva et al.

Viewed

Total article views: 179 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
146 30 3 179 10 11
  • HTML: 146
  • PDF: 30
  • XML: 3
  • Total: 179
  • BibTeX: 10
  • EndNote: 11
Views and downloads (calculated since 28 Oct 2020)
Cumulative views and downloads (calculated since 28 Oct 2020)

Viewed (geographical distribution)

Total article views: 292 (including HTML, PDF, and XML) Thereof 287 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 03 Mar 2021
Download
Short summary
Our paper discusses the structure function method, which allows validation of random uncertainties in the data and, at the same time, probing the small-scale natural variability. We applied this method to the clear-sky total ozone measurements by TROPOMI/Sentinel-5P satellite instrument and found that the TROPOMI random error estimation is adequate. The discussed method is a powerful tool, which can be used in various applications.