Toward Exploring the Synergy Between Cloud Radar Polarimetry and Doppler Spectral Analysis in Deep Cold Precipitating Systems in the Arctic

Abstract

The study of Arctic ice and mixed‐phase clouds, which are characterized by a variety of ice particle types in the same cloudy volume, is challenging research. This study illustrates a new approach to qualitative and quantitative analysis of the complexity of ice and mixed‐phase microphysical processes in Arctic deep precipitating systems using the combination of Ka‐band zenith‐pointing radar Doppler spectra and quasi‐vertical profiles of polarimetric radar variables measured by a Ka/W‐band scanning radar. The results illustrate the frequent occurrence of multimodal Doppler spectra in the dendritic/planar growth layer, where locally generated, slower‐falling particle populations are well separated from faster‐falling populations in terms of Doppler velocity. The slower‐falling particle populations contribute to an increase of differential reflectivity (ZDR), while an enhanced specific differential phase (KDP) in this dendritic growth temperature range is caused by both the slower and faster‐falling particle populations. Another area with frequent occurrence of multimodal Doppler spectra is in mixed‐phase layers, where both populations produce ZDR and KDP values close to 0, suggesting the occurrence of a riming process. Joint analysis of the Doppler spectra and the polarimetric radar variables provides important insight into the microphysics of snow formation and allows the separation of the contributions of ice of different habits to the values of reflectivity and ZDR.

Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration?

“…Instead, we will use the LWP-max(Z e ) relationship of one site as a reference and determine the calibration offset of a second site from this. In other words, the LWP-max(Z e ) relationship is used in a relative way unless we can trust the calibration of one of the radars, which would make it an absolute calibration similar to Protat et al (2011). Similar to the γ -and W -based methods, this assumes that the LWP-max(Z e ) relationship is sufficiently stable with respect to changes in microphysical and dynamical conditions.…”

“…Therefore, we have to not only determine the initial calibration constant of a system but also monitor the calibration constant for changes. For example, waveguide corrosion of the MilliMeter wavelength Cloud Radar (MMCR) of the US Department Of Energy (DOE) Atmospheric Radiation Measurement (ARM) program at the North Slope of Alaska (NSA) site in Utqiaġvik (Barrow), Alaska, caused a 9.8 dB calibration offset in 2008 (Protat et al, 2011). Also, a liquid film on the radome or radar antenna caused by precipitation can temporarily lead to up to 4 dB of additional two-way attenuation (Frech, 2009).…”

“…But such comparisons can be biased by different radar sensitivities and it is important to degrade both radars to the same sensitivity. Protat et al (2011) compared observations statistically from the CloudSat satellite W-band radar with groundbased observations for relative calibration. Because Cloud-Sat's calibration is well established (Tanelli et al, 2008), Protat et al (2011) and Louf et al (2019) proposed using Cloud-Sat as a reference for absolute calibration of ground-based radars.…”

“…Protat et al (2011) compared observations statistically from the CloudSat satellite W-band radar with groundbased observations for relative calibration. Because Cloud-Sat's calibration is well established (Tanelli et al, 2008), Protat et al (2011) and Louf et al (2019) proposed using Cloud-Sat as a reference for absolute calibration of ground-based radars. However, long time series of at least several months are required (Kollias et al, 2019) and the method cannot be used to monitor radar calibration at higher temporal resolutions.…”

“…Besides the three new methods based on liquid cloud microphysical processes, we use a reference method to calibrate the two cloud radars relative to one another. For this, we modify the relative calibration method that Protat et al (2011) proposed for calibrating ground-based cloud radars with CloudSat. In Sect.…”