Preprints
https://doi.org/10.5194/egusphere-2026-507
https://doi.org/10.5194/egusphere-2026-507
29 Jan 2026
 | 29 Jan 2026
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Estimation of wet radome and rain induced attenuation in cloud radar observations

Bernd Mom and Dmitri Moisseev

Abstract. Estimation of the properties of ice clouds above rain from ground-based cloud radar observations is affected by the wet radome, rain path, and melting layer attenuation. In this study, we present a method for estimating wet radome and rain attenuation using collocated disdrometer observations. To ensure that cloud radar retrievals can be performed at a relatively high temporal resolution, on the order of a minute, attenuation estimates are computed at the same temporal resolution. However, the small sampling volumes of disdrometers introduce significant uncertainty in these estimates. To address this, we developed a statistical model to calculate the uncertainty range of the estimated drop size distribution (DSD) parameters and radar variables. The computed radar variables are compared to radar observations to identify radome attenuation. As an additional check of the validity of the estimated variables, the DSD observations are used to calculate rain intensity and accumulated precipitation, which are then compared to precipitation gauge measurements. In addition to radome attenuation, rain path attenuation is estimated using specific attenuation derived from the disdrometer observations. Limitations of this approach are presented and discussed. The proposed method is demonstrated using observations of two rain events collected in Hyytiälä, Finland. These events were selected to demonstrate the effect of radome attenuation, which was rather minor in one case and as large as 10dB in the other.

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Bernd Mom and Dmitri Moisseev

Status: open (until 06 Mar 2026)

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Bernd Mom and Dmitri Moisseev
Bernd Mom and Dmitri Moisseev
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Short summary
A method for estimating wet radome and rain attenuation in cloud radar observations using a disdrometer is developedBecause of the uncertainty in disdrometer measurements, we created a statistical model that provides an estimate for the drop size distribution parameters and radar variables. Analysis of selected case studies indicates that wet radome attenuation can be successfully estimated. The mitigation of rain attenuation, however, is affected by cloud layers embedded in rain.
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