18 Aug 2021

18 Aug 2021

Review status: this preprint is currently under review for the journal AMT.

Analytic characterization of random errors in spectral dual-polarized cloud radar observations

Alexander Myagkov1 and Davide Ori2 Alexander Myagkov and Davide Ori
  • 1Radiometer Physics GmbH, Meckenheim, Germany
  • 2Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany

Abstract. This study presents the first-ever complete characterization of random errors in dual-polarimetric spectral observations of meteorological targets by cloud radars. The characterization is given by means of mathematical equations for joint probability density functions (PDF) and error covariance matrices. The derived equations are checked for consistency using real radar measurements. One of the main conclusions of the study is that the convenient representation of spectral polarimetric measurements including differential reflectivity ZDR, correlation coefficient pHV, and differential phase ΦDP is not suited for the proper characterization of the error covariance matrix. This is because the aforementioned quantities are complex, non-linear functions of the radar raw data and thus their error covariance matrix is commonly derived using simplified linear relations and by neglecting the correlation of errors. This study formulates the spectral polarimetric measurements in terms of a different set of quantities that allows for a proper analytic treatment of their error covariance matrix. The results given in this study allow for utilization of spectral polarimetric measurements for advanced meteorological applications, among which are variational retrieval techniques, data assimilation, and sensitivity analysis.

Alexander Myagkov and Davide Ori

Status: open (until 19 Oct 2021)

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Alexander Myagkov and Davide Ori

Data sets

W-band dataset with I/Q measurement for an AMT manuscript Alexander Myagkov and Christine Unal

Alexander Myagkov and Davide Ori


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Short summary
This study provides equations to characterize random errors of spectral polarimetric observations from cloud radars. The results can be used for a broad spectrum of applications. For instance, the accurate error characterization is essential for advanced retrievals of microphysical properties of clouds and precipitation. More over, the error characterization allows for using measurements from polarimetric cloud radars to potentially improve weather forecasts.