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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/amt-2020-159
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-159
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 05 May 2020

Submitted as: research article | 05 May 2020

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This preprint is currently under review for the journal AMT.

How to estimate total differential attenuation due to hydrometeors with ground-based multi-frequency radars?

Frédéric Tridon1, Alessandro Battaglia2,3, and Stefan Kneifel1 Frédéric Tridon et al.
  • 1Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
  • 2Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Torino, Italy
  • 3Department of Physics and Astronomy, University of Leicester, Leicester, UK

Abstract. At millimeter wavelengths, attenuation by hydrometeors, such as liquid droplets or large snowflakes, is generally not negligible. When using multi-frequency ground-based radar measurements, it is common practice to use the Rayleigh targets at cloud top as a reference in order to derive attenuation-corrected reflectivities and meaningful dual-frequency ratios (DFR). By capitalizing on this idea, this study describes a new quality-controlled approach aiming at identifying regions of the cloud where particle growth is negligible. The core of the method is the identification of a Rayleigh plateau, i.e. a large enough region near cloud top where the vertical gradient of DFR remains small.

By analyzing collocated Ka-W band radar and microwave radiometer (MWR) observations taken at two European sites under various meteorological conditions, it is shown how the resulting estimates of differential path-integrated attenuation (DeltaPIA) can be used to characterize hydrometeor properties. When the DeltaPIA is predominantly produced by cloud liquid droplets, this technique alone can provide accurate estimates of the liquid water path. When combined with MWR observations, this methodology paves the way towards profiling the cloud liquid water and/or quality flagging the MWR retrieval for rain/drizzle contamination and/or estimating the snow differential attenuation.

Frédéric Tridon et al.

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