scholarly journals Hydrometeor Distribution and Linear Depolarization Ratio in Thunderstorms

2020 ◽  
Vol 12 (13) ◽  
pp. 2144 ◽  
Author(s):  
Zbyněk Sokol ◽  
Jana Minářová ◽  
Ondřej Fišer
Keyword(s):  
Central Europe ◽  
Radar Data ◽  
Ice Crystals ◽  
Vertical Profiles ◽  
Depolarization Ratio ◽  
Air Velocity ◽  
Cloud Radar ◽  
Lightning Discharges ◽  
Linear Depolarization Ratio

The distribution of hydrometeors in thunderstorms is still under investigation as well as the process of electrification in thunderclouds leading to lightning discharges. One indicator of cloud electrification might be high values of the Linear Depolarization Ratio (LDR) at higher vertical levels. This study focuses on LDR values derived from vertically pointing cloud radars and the distribution of five hydrometeor species during 38 days with thunderstorms which occurred in 2018 and 2019 in Central Europe, close to our radar site. The study shows improved algorithms for de-aliasing, the derivation of vertical air velocity and the classification of hydrometeors in clouds using radar data. The comparison of vertical profiles with observed lightning discharges in the vicinity of the radar site (≤1 km) suggested that cloud radar data can indirectly identify “lightning” areas by high LDR values observed at higher gates due to the alignment of ice crystals, likely because of an intensified electric field in thunderclouds. Simultaneously, the results indicated that at higher gates, there is a mixture of several hydrometeor species, which suggests a well-known electrification process by collisions of hydrometeors.

Hydrometeor classification in convective clouds using cloud profiler data

2020 ◽  
Author(s):  
Jana Minářová ◽  
Zbyněk Sokol
Keyword(s):  
Central Europe ◽  
Terminal Velocity ◽  
Weather Station ◽  
Depolarization Ratio ◽  
Air Velocity ◽  
Convective Clouds ◽  
Linear Depolarization Ratio ◽  
Using Data ◽  
Profiler Data

<p>In this contribution, we investigate hydrometeors and their distribution in thunderclouds. We classify 5 kinds of hydrometeors using data of a Ka-band cloud profiler (35 GHz) situated at the weather station Milešovka in Central Europe. The classification of hydrometeors is based on calculated vertical air velocity, terminal velocity of a target, minimum and maximum terminal velocity of hydrometeor classes, and Linear Depolarization Ratio within three temperature intervals. We performed the classification for convective events that were observed at the station in 2018 and 2019 and were related to lightning in the vicinity of the station.</p><p>Results suggest that there is a link between lightning flashes observed close to the weather station (based on EUCLID data) and the presence of graupel, ice, snow, and hail. These are the hydrometeors (graupel and ice in particular) that are considered to play major role in thundercloud electrification by the collision of hydrometeors.</p>

scholarly journals Analysis of the Vertical Air Motions and Raindrop Size Distribution Retrievals of a Squall Line Based on Cloud Radar Doppler Spectral Density Data

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 348
Author(s):  
Ningkun Ma ◽  
Liping Liu ◽  
Yichen Chen ◽  
Yang Zhang
Keyword(s):  
Spectral Density ◽  
Size Distribution ◽  
Squall Line ◽  
Vertical Profiles ◽  
Air Velocity ◽  
Density Data ◽  
Cloud Radar ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Reflectivity Factor

A squall line is a type of strongly organized mesoscale convective system that can cause severe weather disasters. Thus, it is crucial to explore the dynamic structure and hydrometeor distributions in squall lines. This study analyzed a squall line over Guangdong Province on 6 May 2016 that was observed using a Ka-band millimeter-wave cloud radar (CR) and an S-band dual-polarization radar (PR). Doppler spectral density data obtained by the CR were used to retrieve the vertical air motions and raindrop size distribution (DSD). The results showed the following: First, the CR detected detailed vertical profiles and their evolution before and during the squall line passage. In the convection time segment (segment B), heavy rain existed with a reflectivity factor exceeding 35 dBZ and a velocity spectrum width exceeding 1.3 m s−1. In the PR detection, the differential reflectivity factor (Zdr) was 1–2 dB, and the large specific differential phase (Kdp) also represented large liquid water content. In the transition and stratiform cloud time segments (segments B and C), the rain stabilized gradually, with decreasing cloud tops, stable precipitation, and a 0 °C layer bright band. Smaller Kdp values (less than 0.9) were distributed around the 0 °C layer, which may have been caused by the melting of ice crystal particles. Second, from the CR-retrieved vertical air velocity, before squall line passage, downdrafts dominated in local convection and weak updrafts existed in higher-altitude altostratus clouds. In segment B, the updraft air velocity reached more than 8 m s−1 below the 0 °C layer. From segments C to D, the updrafts changed gradually into weak and wide-ranging downdrafts. Third, in the comparison of DSD values retrieved at 1.5 km and DSD values on the ground, the retrieved DSD line was lower than the disdrometer, the overall magnitude of the DSD retrieved was smaller, and the difference decreased from segments C to D. The standardized intercept parameter (Nw) and shape parameter (μ) of the DSD retrieved at 1.8 km showed good agreement with the disdrometer results, and the mass-weighted mean diameter (Dm) was smaller than that on the ground, but very close to the PR-retrieved Dm result at 2 km. Therefore, comparing with the DSD retrieved at around 2 km, the overall number concentration remained unchanged and Dm got larger on the ground, possibly reflecting the process of raindrop coalescence. Lastly, the average vertical profiles of several quantities in all segments showed that, first of all, the decrease of Nw and Dm with height in segments C and D was similar, reflecting the collision effect of falling raindrops. The trends were opposite in segment B, indicating that raindrops underwent intense mixing and rapid collision and growth in this segment. Then, PR-retrieved Dm profiles can verify the rationality of the CR-retrieved Dm. Finally, a vertical velocity profile peak generated a larger Dm especially in segments C and D.

scholarly journals Classification of Hydrometeors Using Measurements of the Ka-Band Cloud Radar Installed at the Milešovka Mountain (Central Europe)

2018 ◽  
Vol 10 (11) ◽  
pp. 1674 ◽  
Author(s):  
Zbyněk Sokol ◽  
Jana Minářová ◽  
Petr Novák
Keyword(s):  
Central Europe ◽  
Terminal Velocity ◽  
Small Particles ◽  
Cloud Droplets ◽  
Vertical Temperature Profile ◽  
Ka Band ◽  
Cloud Radar ◽  
Weather Radars ◽  
Cloud Particles ◽  
Linear Depolarization Ratio

In radar meteorology, greater interest is dedicated to weather radars and precipitation analyses. However, cloud radars provide us with detailed information on cloud particles from which the precipitation consists of. Motivated by research on the cloud particles, a vertical Ka-band cloud radar (35 GHz) was installed at the Milešovka observatory in Central Europe and was operationally measuring since June 2018. This study presents algorithms that we use to retrieve vertical air velocity (Vair) and hydrometeors. The algorithm calculating Vair is based on small-particle tracers, which considers the terminal velocity of small particles negligible and, thereby, Vair corresponds to the velocity of the small particles. The algorithm classifying hydrometeors consists of calculating the terminal velocity of hydrometeors and the vertical temperature profile. It identifies six hydrometeor types (cloud droplets, ice, and four precipitating particles: rain, graupel, snow, and hail) based on the calculated terminal velocity of hydrometeors, temperature, Vair, and Linear Depolarization Ratio. The results of both the Vair and the distribution of hydrometeors were found to be realistic for a thunderstorm associated with significant lightning activity on 1 June 2018.

Microphysical Insights into Ice Pellet Formation Revealed by Fully Polarimetric Ka-Band Doppler Radar

2020 ◽  
Vol 59 (10) ◽  
pp. 1557-1580
Author(s):  
Matthew R. Kumjian ◽  
Dana M. Tobin ◽  
Mariko Oue ◽  
Pavlos Kollias
Keyword(s):  
New York ◽  
Correlation Coefficient ◽  
Doppler Radar ◽  
Radar Data ◽  
Ice Crystals ◽  
Horizontal Polarization ◽  
Ka Band ◽  
Pellet Formation ◽  
Linear Depolarization Ratio ◽  
Differential Reflectivity

AbstractFully polarimetric scanning and vertically pointing Doppler spectral data from the state-of-the-art Stony Brook University Ka-band Scanning Polarimetric Radar (KASPR) are analyzed for a long-duration case of ice pellets over central Long Island in New York from 12 February 2019. Throughout the period of ice pellets, a classic refreezing signature was present, consisting of a secondary enhancement of differential reflectivity ZDR beneath the melting layer within a region of decreasing reflectivity factor at horizontal polarization ZH and reduced copolar correlation coefficient ρhv. The KASPR radar data allow for evaluation of previously proposed hypotheses to explain the refreezing signature. It is found that, upon entering a layer of locally generated columnar ice crystals and undergoing contact nucleation, smaller raindrops preferentially refreeze into ice pellets prior to the complete freezing of larger drops. Refreezing particles exhibit deformations in shape during freezing, leading to reduced ρhv, reduced co-to-cross-polar correlation coefficient ρxh, and enhanced linear depolarization ratio, but these shape changes do not explain the ZDR signature. The presence of columnar ice crystals, though apparently crucial for instigating the refreezing process, does not contribute enough backscattered power to affect the ZDR signature, either.

X-Band Polarimetric Observations of Cross Coupling in the Ice Phase of Convective Storms in Taiwan

2014 ◽  
Vol 53 (6) ◽  
pp. 1678-1695 ◽  
Author(s):  
J. C. Hubbert ◽  
S. M. Ellis ◽  
W.-Y. Chang ◽  
Y.-C. Liou
Keyword(s):  
Electric Fields ◽  
Cross Coupling ◽  
Radar Data ◽  
Ice Crystals ◽  
Polarimetric Radar ◽  
Differential Phase ◽  
X Band ◽  
Linear Depolarization Ratio ◽  
Differential Reflectivity ◽  
Ice Phase

AbstractIn this paper, experimental X-band polarimetric radar data from simultaneous transmission of horizontal (H) and vertical (V) polarizations (SHV) are shown, modeled, and microphysically interpreted. Both range–height indicator data and vertical-pointing X-band data from the Taiwan Experimental Atmospheric Mobile-Radar (TEAM-R) are presented. Some of the given X-band data are biased, which is very likely caused by cross coupling of the H and V transmitted waves as a result of aligned, canted ice crystals. Modeled SHV data are used to explain the observed polarimetric signatures. Coincident data from the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) are presented to augment and support the X-band polarimetric observations and interpretations. The polarimetric S-Pol data are obtained via fast-alternating transmission of horizontal and vertical polarizations (FHV), and thus the S-band data are not contaminated by the cross coupling (except the linear depolarization ratio LDR) observed in the X-band data. The radar data reveal that there are regions in the ice phase where electric fields are apparently aligning ice crystals near vertically and thus causing negative specific differential phase Kdp. The vertical-pointing data also indicate the presence of preferentially aligned ice crystals that cause differential reflectivity Zdr and differential phase ϕdp to be strong functions of azimuth angle.

scholarly journals Differences in Cloud Radar Phase and Power in Co- and Cross-Channel—Indicator of Lightning

2021 ◽  
Vol 13 (3) ◽  
pp. 503
Author(s):  
Zbyněk Sokol ◽  
Jana Popová
Keyword(s):  
Power Spectra ◽  
Regression Tree ◽  
Radar Data ◽  
Tree Model ◽  
Cloud Radar ◽  
Critical Success ◽  
Lightning Discharges ◽  
First Time ◽  
Critical Success Index ◽  
Regression Tree Model

Thunderstorms and especially induced lightning discharges have still not been fully understood, although they are known to cause many casualties yearly worldwide. This study aims at filling the gap of knowledge by investigating the potential of phase and power of the co- and cross-channels of a vertical cloud radar to indicate lightning close to the radar site. We performed statistical and correlation analyses of vertical profiles of phase and power spectra in the co- and the cross-channel for 38 days of thunderstorms producing lightning up to 20 km from the radar in 2018–2019. Specifically, we divided the dataset into “near” and “far” data according to the observed distance of lightning to the radar and analyzed it separately. Although the results are quite initial given the limited number of “near” data, they clearly showed different structures of “near” and “far” data, thus confirming the potential of radar data to indicate lightning. Moreover, for the first time in this study the predictability of lightning using cloud radar quantities was evaluated. We applied a Regression Tree Model to diagnose lightning and verified it using Receiver Operating Characteristic (ROC) and Critical Success Index (CSI). ROC provided surprisingly good results, while CSI was not that good but considering the very rare nature of lightning its values are high as well.

scholarly journals Characterization of Arctic mixed-phase cloud properties at small scale and coupling with satellite remote sensing

2017 ◽  
Author(s):  
Guillaume Mioche ◽  
Olivier Jourdan ◽  
Julien Delanoë ◽  
Christophe Gourbeyre ◽  
Guy Febvre ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Crystal Size ◽  
Mixed Phase ◽  
Ice Crystals ◽  
Small Scale ◽  
Vertical Profiles ◽  
Liquid Droplets ◽  
Ice Crystal ◽  
High Concentration ◽  
Ice Crystal Size

Abstract. This study aims to characterize the microphysical and optical properties of ice crystals and supercooled liquid droplets within low-level Arctic mixed-phase clouds (MPC). We compiled and analyzed cloud in situ measurements from 4 airborne campaigns (18 flights, 71 vertical profiles in MPC) over the Greenland Sea and the Svalbard region. Cloud phase discrimination and representative vertical profiles of number, size, mass and shapes of ice crystals and liquid droplets are assessed. The results show that the liquid phase dominates the upper part of the MPC with high concentration of small droplets (120 cm−3, 15&tinsp;μm), and averaged LWC around 0.2 g m−3. The ice phase is found everywhere within the MPC layers, but dominates the properties in the lower part of the cloud and below where ice crystals precipitate down to the surface. The analysis of the ice crystal morphology highlights that irregulars and rimed are the main particle habit followed by stellars and plates. We hypothesize that riming and condensational growth processes (including the Wegener-Bergeron-Findeisein mechanism) are the main growth mechanisms involved in MPC. The differences observed in the vertical profiles of MPC properties from one campaign to another highlight that large values of LWC and high concentration of smaller droplets are possibly linked to polluted situations which lead to very low values of ice crystal size and IWC. On the contrary, clean situations with low temperatures exhibit larger values of ice crystal size and IWC. Several parameterizations relevant for remote sensing or modeling are also determined, such as IWC (and LWC) – extinction relationship, ice and liquid integrated water paths, ice concentration and liquid water fraction according to temperature. Finally, 4 flights collocated with active remote sensing observations from CALIPSO and CloudSat satellites are specifically analyzed to evaluate the cloud detection and cloud thermodynamical phase DARDAR retrievals. This comparison is valuable to assess the sub-pixel variability of the satellite measurements as well as their shortcomings/performance near the ground.

scholarly journals Benefit of depolarization ratio at λ = 1064 nm for the retrieval of the aerosol microphysics from lidar measurements

2014 ◽  
Vol 7 (11) ◽  
pp. 3773-3781 ◽  
Author(s):  
J. Gasteiger ◽  
V. Freudenthaler
Keyword(s):  
Optical Properties ◽  
Mass Concentration ◽  
Volcanic Ash ◽  
Single Scattering ◽  
Depolarization Ratio ◽  
Complex Relation ◽  
Microphysical Properties ◽  
Lidar Measurements ◽  
Increased Sensitivity ◽  
Linear Depolarization Ratio

Abstract. A better quantification of aerosol properties is required for improving the modelling of aerosol effects on weather and climate. This task is methodologically demanding due to the diversity of the microphysical properties of aerosols and the complex relation between their microphysical and optical properties. Advanced lidar systems provide spatially and temporally resolved information on the aerosol optical properties that is sufficient for the retrieval of important aerosol microphysical properties. Recently, the mass concentration of transported volcanic ash, which is relevant for the flight safety of aeroplanes, was retrieved from measurements of such lidar systems in southern Germany. The relative uncertainty of the retrieved mass concentration was on the order of ±50%. The present study investigates improvements of the retrieval accuracy when the capability of measuring the linear depolarization ratio at 1064 nm is added to the lidar setup. The lidar setups under investigation are based on those of MULIS and POLIS of the Ludwig-Maximilians-Universität in Munich (Germany) which measure the linear depolarization ratio at 355 and 532 nm with high accuracy. The improvements are determined by comparing uncertainties from retrievals applied to simulated measurements of this lidar setup with uncertainties obtained when the depolarization at 1064 nm is added to this setup. The simulated measurements are based on real lidar measurements of transported Eyjafjallajökull volcano ash. It is found that additional 1064 nm depolarization measurements significantly reduce the uncertainty of the retrieved mass concentration and effective particle size. This significant improvement in accuracy is the result of the increased sensitivity of the lidar setup to larger particles. The size dependence of the depolarization does not vary strongly with refractive index, thus we expect similar benefits for the retrieval in case of measurements of other volcanic ash compositions and also for transported desert dust. For the retrieval of the single scattering albedo, which is relevant to the radiative transfer in aerosol layers, no significant improvements were found.

scholarly journals MU Radar and Lidar Observations of Clear-Air Turbulence underneath Cirrus

2010 ◽  
Vol 138 (2) ◽  
pp. 438-452 ◽  
Author(s):  
Hubert Luce ◽  
Takuji Nakamura ◽  
Masayuki K. Yamamoto ◽  
Mamoru Yamamoto ◽  
Shoichiro Fukao
Keyword(s):  
Convective Instability ◽  
Radar Data ◽  
Ice Crystals ◽  
Shear Instability ◽  
Cloud Base ◽  
Doppler Spectrum ◽  
Cirrus Cloud ◽  
Air Turbulence ◽  
Mu Radar ◽  
Generation Mechanisms

Abstract Turbulence generation mechanisms prevalent in the atmosphere are mainly shear instabilities, breaking of internal buoyancy waves, and convective instabilities such as thermal convection due to heating of the ground. In the present work, clear-air turbulence underneath a cirrus cloud base is described owing to coincident observations from the VHF (46.5 MHz) middle and upper atmosphere (MU) radar, a Rayleigh–Mie–Raman (RMR) lidar, and a balloon radiosonde on 7–8 June 2006 (at Shigaraki, Japan; 34.85°N, 136.10°E). Time–height cross section of lidar backscatter ratio obtained at 2206 LT 7 June 2006 showed the presence of a cirrus layer between 8.0 and 12.5 km MSL. Downward-penetrating structures of ice crystals with horizontal and vertical extents of 1.0–4.0 km and 200–800 m, respectively, have been detected at the cirrus cloud base for about 35 min. At the same time, the MU radar data revealed clear-air turbulence layers developing downward from the cloud base in the environment of the protuberances detected by the RMR lidar. Their maximum depth was about 2.0 km for about 1.5 h. They were associated with oscillatory vertical wind perturbations of up to ±1.5 m s−1 and variances of Doppler spectrum of 0.2–1.5 m−2 s−2. Analysis of the data suggests that the turbulence and the downward penetration of cloudy air were possibly the consequence of a convective instability (rather than a dynamical shear instability) that was likely due to sublimation of ice crystals in the subcloud region. Downward clear-air motions measured by the MU radar were associated with the descending protuberances, and updrafts were observed between them. These observations suggest that the cloudy air might have been pushed down by the downdrafts of the convective instability and pushed up by the updrafts to form the observed protuberances at the cloud base. These structures may be virga or perhaps more likely mamma as reported by recent observations of cirrus mamma with similar instruments and by numerical simulations.

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