Evaluation of the reflectivity calibration of W-band radars based on observations in rain

Abstract

Abstract. This study presents two methods for evaluating the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first approach is based on a self-consistency method of polarimetric radar variables, which is widely used in the precipitation radar community. As previous studies pointed out, the method cannot be directly applied to higher frequencies where non-Rayleigh scattering effects and attenuation have a nonnegligible influence on radar variables. The method presented here solves this problem by using polarimetric Doppler spectra to separate backscattering and propagational effects. New fits between the separated radar variables allow one to estimate the absolute radar calibration using a minimization technique. The main advantage of the self-consistency method is its lower dependence on the spatial variability in radar drop size distribution (DSD). The estimated uncertainty of the method is ±0.7 dB. The method was applied to three intense precipitation events, and the retrieved reflectivity offsets were within the estimated uncertainty range. The second method is an improvement on the conventional disdrometer-based approach, where reflectivity from the lowest range gate is compared to simulated reflectivity using surface disdrometer observations. The improved method corrects, first, for the time lag between surface DSD observations and the radar measurements at a certain range. In addition, the effect of evaporation of raindrops on their way towards the surface is mitigated. The disdrometer-based method was applied to 12 rain events observed by vertically pointed W-band radar and showed repeatable estimates of the reflectivity offsets at rain rates below 4 mm h−1 within ±0.9 dB. The proposed approaches can analogously be extended to Ka-band radars. Although very different in terms of complexity, both methods extend existing radar calibration evaluation approaches, which are inevitably needed for the growing cloud radar networks in order to provide high-quality radar observation to the atmospheric community.

Melting Behavior of Rimed and Unrimed Snowflakes Investigated With Statistics of Triple‐Frequency Doppler Radar Observations

“…As demonstrated with the TRIPEx‐pol data set in Myagkov et al. (2020), using rain as a calibration target provides similar accuracy (±0.7 dB) as compared to more comprehensive calibration methods. Differential attenuation has been mitigated in several steps.…”

“…The absolute calibration of Ze for all three radars has been evaluated using raindrop size distributions from several rain events measured by a Parsivel disdrometer (Löffler-Mang & Joss, 2000) installed directly next to the radars. As demonstrated with the TRIPEx-pol data set in Myagkov et al (2020), using rain as a calibration target provides similar accuracy (±0.7 dB) as compared to more comprehensive calibration methods. Differential attenuation has been mitigated in several steps.…”

Radar and ground-level measurements of precipitation collected by the École Polytechnique Fédérale de Lausanne during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games

“…Horizontal wind induces a horizontal displacement of the particles such that the superposition of the one-dimensional sections can lead to distorted particles. This issue is thoroughly investigated with numerical simulations in Nešpor et al (2000). The two orthogonal two-dimensional projections yield three-dimensional shape information, which can be used to compute the equivalent drop diameter and the aspect ratio.…”

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

“…The radar is a part of a dual-frequency system owned and operated by the Technical University of Delft in Cabauw, the Netherlands. Technical specifications of the radar can be found in Myagkov et al (2020). The radar uses frequency modulated continuous signals.…”