scholarly journals Quasi-Vertical Profiles—A New Way to Look at Polarimetric Radar Data

2016 ◽  
Vol 33 (3) ◽  
pp. 551-562 ◽  
Author(s):  
Alexander Ryzhkov ◽  
Pengfei Zhang ◽  
Heather Reeves ◽  
Matthew Kumjian ◽  
Timo Tschallener ◽  
...  
Keyword(s):  
Continuous Monitoring ◽  
Radar Data ◽  
Vertical Profiles ◽  
Remote Sensors ◽  
Weather Radars ◽  
X Band ◽  
Potential Benefits ◽  
High Vertical Resolution ◽  
Microphysical Processes ◽  
Differential Reflectivity

AbstractA novel methodology is introduced for processing and presenting polarimetric data collected by weather surveillance radars. It involves azimuthal averaging of radar reflectivity Z, differential reflectivity ZDR, cross-correlation coefficient ρhv, and differential phase ΦDP at high antenna elevation, and presenting resulting quasi-vertical profiles (QVPs) in a height-versus-time format. Multiple examples of QVPs retrieved from the data collected by S-, C-, and X-band dual-polarization radars at elevations ranging from 6.4° to 28° illustrate advantages of the QVP technique. The benefits include an ability to examine the temporal evolution of microphysical processes governing precipitation production and to compare polarimetric data obtained from the scanning surveillance weather radars with observations made by vertically looking remote sensors, such as wind profilers, lidars, radiometers, cloud radars, and radars operating on spaceborne and airborne platforms. Continuous monitoring of the melting layer and the layer of dendritic growth with high vertical resolution, and the possible opportunity to discriminate between the processes of snow aggregation and riming, constitute other potential benefits of the suggested methodology.

scholarly journals Characteristics of the Bright Band Based on Quasi-Vertical Profiles of Polarimetric Observations from an S-Band Weather Radar Network

2020 ◽  
Vol 12 (24) ◽  
pp. 4061
Author(s):  
Jeong-Eun Lee ◽  
Sung-Hwa Jung ◽  
Soohyun Kwon
Keyword(s):  
Signal To Noise Ratio ◽  
Vertical Profiles ◽  
Bright Band ◽  
Weather Radars ◽  
Radar Network ◽  
Temperature Zero ◽  
The Mean ◽  
Microphysical Processes ◽  
Differential Reflectivity ◽  
Self Consistency

Bright band (BB) characteristics obtained via dual-polarization weather radars elucidate thermodynamic and microphysical processes within precipitation systems. This study identified BB using morphological features from quasi-vertical profiles (QVPs) of polarimetric observations, and their geometric, thermodynamic, and polarimetric characteristics were statistically examined using nine operational S-band weather radars in South Korea. For comparable analysis among weather radars in the network, the calibration biases in reflectivity (ZH) and differential reflectivity (ZDR) were corrected based on self-consistency. The cross-correlation coefficient (ρHV) bias in the weak echo regions was corrected using the signal-to-noise ratio (SNR). First, we analyzed the heights of BBPEAK derived from the ZH as a function of season and compared the heights of BBPEAK derived from the ZH, ZDR, and ρHV. The heights of BBPEAK were highest in the summer season when the surface temperature was high. However, they showed distinct differences depending on the location (e.g., latitude) within the radar network, even in the same season. The height where the size of melting particles was at a maximum (BBPEAK from the ZH) was above that where the oblateness of these particles maximized (BBPEAK from ZDR). The height at which the inhomogeneity of hydometeors was at maximum (BBPEAK from the ρHV) was also below that of BBPEAK from the ZH. Second, BB thickness and relative position of BBPEAK were investigated to characterize the geometric structure of the BBs. The BB thickness increased as the ZH at BBBOTTOM increased, which indicated that large snowflakes melt more slowly than small snowflakes. The geometrical structure of the BBs was asymmetric, since the melting particles spent more time forming the thin shell of meltwater around them, and they rapidly collapsed to form a raindrop at the final stage of melting. Third, the heights of BBTOP, BBPEAK, and BBBOTTOM were compared with the zero-isotherm heights. The dry-temperature zero-isotherm heights were between BBTOP and BBBOTTOM, while the wet-bulb temperature zero-isotherm heights were close to the height of BBPEAK. Finally, we examined the polarimetric observations to understand the involved microphysical processes. The correlation among ZH at BBTOP, BBPEAK, and BBBOTTOM was high (>0.94), and the ZDR at BBBOTTOM was high when the BB’s intensity was strong. This proved that the size and concentration of snowflakes above the BB influence the size and concentration of raindrops below the BB. There was no depression in the ρHV for a weak BB. Finally, the mean profile of the ZH and ZDR depended on the ZH at BBBOTTOM. In conclusion, the growth process of snowflakes above the BB controls polarimetric observations of BB.

scholarly journals Calibration of radar differential reflectivity using quasi-vertical profiles

2021 ◽  
Author(s):  
Daniel Sanchez-Rivas ◽  
Miguel A. Rico-Ramirez
Keyword(s):  
Weather Radar ◽  
Radar Data ◽  
Vertical Profiles ◽  
Weather Radars ◽  
Precipitation Estimates ◽  
Novel Method ◽  
One Year ◽  
The Uk ◽  
Quantitative Precipitation Estimates ◽  
Differential Reflectivity

Abstract. The differential reflectivity (ZDR) is a crucial weather radar measurement that helps to improve quantitative precipitation estimates using polarimetric weather radars. However, a system bias between the horizontal and vertical channels generated by the radar produces an offset in ZDR. Existing methods to calibrate ZDR measurements rely on vertical observations of ZDR taken in rain, in which ZDR values close to 0 dB are expected. However, not all weather radar systems are capable of producing vertical pointing measurements. In this work, we present and analyse a novel method for correcting and monitoring the ZDR offset using quasi-vertical profiles of polarimetric variables. The method is applied to radar data collected through one year of precipitation events by two operational C-band weather radars in the UK. The proposed method proves effective in achieving the required accuracy of 0.1 dB for the calibration of ZDR as the calibration results are consistent with the traditional method based on vertical profiles. Additionally, the method is independently evaluated using disdrometers located near the radar sites. The results showed a good agreement between disdrometer-derived and radar-calibrated ZDR measurements.

A Polarimetric Radar Analysis of Ice Microphysical Processes in Melting Layers of Winter Storms Using S-Band Quasi-Vertical Profiles

2020 ◽  
Vol 59 (4) ◽  
pp. 751-767 ◽  
Author(s):  
Erica M. Griffin ◽  
Terry J. Schuur ◽  
Alexander V. Ryzhkov
Keyword(s):  
Cold Season ◽  
Vertical Profiles ◽  
Horizontal Polarization ◽  
Winter Storms ◽  
Differential Phase ◽  
High Vertical Resolution ◽  
Microphysical Processes ◽  
Statistical Relationships ◽  
Reflectivity Data ◽  
Differential Reflectivity

AbstractQuasi-vertical profiles (QVPs) obtained from a database of U.S. WSR-88D data are used to document polarimetric characteristics of the melting layer (ML) in cold-season storms with high vertical resolution and accuracy. A polarimetric technique to define the top and bottom of the ML is first introduced. Using the QVPs, statistical relationships are developed to gain insight into the evolution of microphysical processes above, within, and below the ML, leading to a statistical polarimetric model of the ML that reveals characteristics that reflectivity data alone are not able to provide, particularly in regions of weak reflectivity factor at horizontal polarization ZH. QVP ML statistics are examined for two regimes in the ML data: ZH ≥ 20 dBZ and ZH < 20 dBZ. Regions of ZH ≥ 20 dBZ indicate locations of MLs collocated with enhanced differential reflectivity ZDR and reduced copolar correlation coefficient ρhv, while for ZH < 20 dBZ a well-defined ML is difficult to discern using ZH alone. Evidence of large ZDR up to 4 dB, backscatter differential phase δ up to 8°, and low ρhv down to 0.80 associated with lower ZH (from −10 to 20 dBZ) in the ML is observed when pristine, nonaggregated ice falls through it. Positive correlation is documented between maximum specific differential phase KDP and maximum ZH in the ML; these are the first QVP observations of KDP in MLs documented at S band. Negative correlation occurs between minimum ρhv in the ML and ML depth and between minimum ρhv in the ML and the corresponding enhancement of ZH (ΔZH = ZHmax − ZHrain).

Quantitative Evaluation of Polarimetric Estimates from Scanning Weather Radars using a Vertically Pointing Micro Rain Radar

2020 ◽  
Author(s):  
Ricardo Reinoso-Rondinel ◽  
Marc Schleiss
Keyword(s):  
Drop Size ◽  
Limited Attention ◽  
Size Distributions ◽  
Weather Radars ◽  
X Band ◽  
Microphysical Processes ◽  
Drop Size Distributions ◽  
Differential Reflectivity ◽  
The Impact ◽  
Rain Radar

AbstractConventionally, micro rain radars (MRRs) have been used as a tool to calibrate reflectivity from weather radars, estimate the relation between rainfall rate and reflectivity, and study microphysical processes in precipitation. However, limited attention has been given to the reliability of the retrieved drop size distributions DSDs from MRRs. This study sheds more light on this aspect by examining the sensitivity of retrieved DSDs to the assumptions made to map Doppler spectra into size distributions, and investigates the capability of an MRR to assess polarimetric observations from operational weather radars. For that, an MRR was installed near the Cabauw observatory in the Netherlands, between the IDRA X-band radar and the Herwijnen operational C-band radar. The measurements of the MRR from November 2018 to February 2019 were used to retrieve DSDs and simulate horizontal reflectivity Ze, differential reflectivity ZDR, and specific differential phase KDP in rain. Attention is given to the impact of aliased spectra and right-hand side truncation on the simulation of polarimetric variables. From a quantitative assessment, the correlations of Ze and ZDR between the MRR and Herwijnen radar were 0.93 and 0.70, respectively, while those between the MRR and IDRA were 0.91 and 0.69. However, Ze and ZDR from the Herwijnen radar showed slight biases of 1.07 and 0.25 dB. For IDRA, the corresponding biases were 2.67 and -0.93 dB. Our results show that MRR measurements are advantageous to inspect the calibration of scanning radars and validate polarimetric estimates in rain, provided that the DSDs are correctly retrieved and controlled for quality assurance.

Polarimetric Observations and Simulations of Sublimating Snow: Implications for Nowcasting

2021 ◽  
Author(s):  
Jacob T. Carlin ◽  
Heather D. Reeves ◽  
Alexander V. Ryzhkov
Keyword(s):  
Radar Data ◽  
Lead Times ◽  
Start Time ◽  
Good Correspondence ◽  
Wide Range ◽  
Potential Benefits ◽  
Microphysical Processes ◽  
Ice Production ◽  
Differential Reflectivity

AbstractSnow sublimating in dry air is a forecasting challenge and can delay the onset of surface snowfall and affect storm-total accumulations. Despite this, it remains comparatively less studied than other microphysical processes. Herein, the characteristics of sublimating snow and the potential for nowcasting snowfall reaching the surface are explored through the use of dual-polarization radar. Twelve cases featuring prolific sublimation were analyzed using range-defined quasi-vertical profiles (RDQVPs) and compared with environmental model analyses. Overall, reflectivity Z significantly decreases, differential reflectivity ZDR slightly decreases, and copolar-correlation coefficient ρhv remains nearly constant through the sublimation layer. Regions of enhanced specific differential phase Kdp were frequently observed in the sublimation layer and are believed to be polarimetric evidence of secondary ice production via sublimation. A 1D bin model was initialized using particle size distributions retrieved from the RDQVPs using numerous novel polarimetric snowretrieval relations for a wide range of forecast lead times, with the model environment evolving in response to sublimation. It was found that the model was largely able to predict the snowfall start time up to six hours in advance, with a 6-h median bias of just -18.5 minutes. A more detailed case study of the 08 December 2013 snowstorm in the Philadelphia region was also performed, demonstrating good correspondence with observations and examples of model fields (e.g., cooling rate) hypothetically available from such a tool. The proof-of-concept results herein demonstrate the potential benefits of incorporating spatially averaged radar data in conjunction with simple 1D models into the nowcasting process.

A Comparative Study of Rainfall Retrievals Based on Specific Differential Phase Shifts at X- and S-Band Radar Frequencies

2006 ◽  
Vol 23 (7) ◽  
pp. 952-963 ◽  
Author(s):  
Sergey Y. Matrosov ◽  
Robert Cifelli ◽  
Patrick C. Kennedy ◽  
Steven W. Nesbitt ◽  
Steven A. Rutledge ◽  
...  
Keyword(s):  
Comparative Study ◽  
Radar Data ◽  
Drop Diameter ◽  
Horizontal Polarization ◽  
Differential Phase Shift ◽  
Phase Measurements ◽  
Differential Phase ◽  
X Band ◽  
Raindrop Size ◽  
Differential Reflectivity

Abstract A comparative study of the use of X- and S-band polarimetric radars for rainfall parameter retrievals is presented. The main advantage of X-band polarimetric measurements is the availability of reliable specific differential phase shift estimates, KDP, for lighter rainfalls when phase measurements at the S band are too noisy to produce usable KDP. Theoretical modeling with experimental raindrop size distributions indicates that due to some non-Rayleigh resonant effects, KDP values at a 3.2-cm wavelength (X band) are on average a factor of 3.7 greater than at 11 cm (S band), which is a somewhat larger difference than simple frequency scaling predicts. The non-Rayleigh effects also cause X-band horizontal polarization reflectivity, Zeh, and differential reflectivity, ZDR, to be larger than those at the S band. The differences between X- and S-band reflectivities can exceed measurement uncertainties for Zeh starting approximately at Zeh &gt; 40 dBZ, and for ZDR when the mass-weighted drop diameter, Dm, exceeds about 2 mm. Simultaneous X- and S-band radar measurements of rainfall showed that consistent KDP estimates exceeding about 0.1° km−1 began to be possible at reflectivities greater than ∼26–30 dBZ while at the S band such estimates can generally be made if Zeh &gt; ∼35–39 dBZ. Experimental radar data taken in light-to-moderate stratiform rainfalls with rain rates R in an interval from 2.5 to 15 mm h−1 showed availability of the KDP-based estimates of R for most of the data points at the X band while at the S band such estimates were available only for R greater than about 8–10 mm h−1. After correcting X-band differential reflectivity measurements for differential attenuation, ZDR measurements at both radar frequency bands were in good agreement with each other for Dm &lt; 2 mm, which approximately corresponds to ZDR ≈ 1.6 dB. The ZDR-based retrievals of characteristic raindrop sizes also agreed well with in situ disdrometer measurements.

scholarly journals Radar Remote Sensing of Precipitation in High Mountains: Detection and Characterization of Melting Layer in the Grenoble Valley, French Alps

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 784 ◽  
Author(s):  
Anil Kumar Khanal ◽  
Guy Delrieu ◽  
Frédéric Cazenave ◽  
Brice Boudevillain
Keyword(s):  
Remote Sensing ◽  
Correlation Coefficient ◽  
Vertical Profiles ◽  
Radar Remote Sensing ◽  
French Alps ◽  
X Band ◽  
The Mean ◽  
Velocity Spectra ◽  
Differential Reflectivity ◽  
Polar Correlation

The RadAlp experiment aims at developing advanced methods for rain and snow estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed in the French Alps, Grenoble region. It is composed of a Météo-France operated X-band MOUC radar (volumetric, Doppler and polarimetric) on top of the Mt Moucherotte (1920 m ASL), the X-band XPORT research radar (volumetric, Doppler, polarimetric), a K-band micro rain radar (MRR, Doppler, vertically pointing) and in situ sensors (rain gauges, disdrometers), latter three operated on the Grenoble campus (220 m ASL). Based on the observation that the precipitation phase changes at/below the elevation of mountain-top MOUC radar for more than 60% of the significant events, an algorithm for ML identification has been developed using valley-based radar systems: it uses the quasi vertical profiles of XPORT polarimetric measurements (horizontal and vertical reflectivity, differential reflectivity, cross-polar correlation coefficient) and the MRR vertical profiles of apparent falling velocity spectra. The algorithm produces time series of the altitudes and values of peaks and inflection points of the different radar observables. A literature review allows us to link the micro-physical processes at play during the melting process with the available polarimetric and Doppler signatures, e.g., (i) regarding the altitude differences between the peaks of reflectivity, cross-polar correlation coefficient and differential reflectivity, as well as (ii) regarding the co-variation of the profiles of Doppler velocity spectra and cross-polar correlation coefficient. A statistical analysis of the ML based on 42 rain events (98 h of XPORT data) is then proposed. Among other results, this study indicates that (i) the mean value of the ML width in Grenoble is 610 m with a standard deviation of 160 m; (ii) the mean altitude difference between the horizontal reflectivity and the ρ H V peaks is 90 m and the mean altitude difference between the ρ H V and Zdr peaks is 30 m; (iii) even for the limited rainrate range in the dataset (0–8.5 mm h − 1 ), the “intensity effect” is clear on the reflectivity profile and the ML width, as well as on polarimetric variables such as ρ H V peak value and the Zdr enhancement in the upper part of the profile. On the contrary, the study of both the “density effect” and the influence of the 0   ° C isotherm altitude did not yield significant results with the considered dataset; (iv) a principal component analysis on one hand shows the richness of the dataset since the first 2 PCs explain only 50% of the total variance and on the other hand the added-value of the polarimetric variables since they rank high in a ranking of the total variance explained by individual variables.

scholarly journals Mobile Radar Observations of the Evolving Debris Field Compared with a Damage Survey of the Shawnee, Oklahoma, Tornado of 19 May 2013

2020 ◽  
Vol 148 (5) ◽  
pp. 1779-1803 ◽  
Author(s):  
Roger M. Wakimoto ◽  
Zachary Wienhoff ◽  
Howard B. Bluestein ◽  
David J. Bodine ◽  
James M. Kurdzo
Keyword(s):  
Cross Correlation ◽  
Vertical Structure ◽  
Leading Edge ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Vertical Profiles ◽  
Damage Survey ◽  
X Band ◽  
First Time ◽  
Rapid Scanning

Abstract A detailed damage survey is combined with high-resolution mobile, rapid-scanning X-band polarimetric radar data collected on the Shawnee, Oklahoma, tornado of 19 May 2013. The focus of this study is the radar data collected during a period when the tornado was producing damage rated EF3. Vertical profiles of mobile radar data, centered on the tornado, revealed that the radar reflectivity was approximately uniform with height and increased in magnitude as more debris was lofted. There was a large decrease in both the cross-correlation coefficient (ρhv) and differential radar reflectivity (ZDR) immediately after the tornado exited the damaged area rated EF3. Low ρhv and ZDR occurred near the surface where debris loading was the greatest. The 10th percentile of ρhv decreased markedly after large amounts of debris were lofted after the tornado leveled a number of structures. Subsequently, ρhv quickly recovered to higher values. This recovery suggests that the largest debris had been centrifuged or fallen out whereas light debris remained or continued to be lofted. Range–height profiles of the dual-Doppler analyses that were azimuthally averaged around the tornado revealed a zone of maximum radial convergence at a smaller radius relative to the leading edge of lofted debris. Low-level inflow into the tornado encountering a positive bias in the tornado-relative radial velocities could explain the existence of the zone. The vertical structure of the convergence zone was shown for the first time.

scholarly journals The Impact of Raindrop Collisional Processes on the Polarimetric Radar Variables

2014 ◽  
Vol 71 (8) ◽  
pp. 3052-3067 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Olivier P. Prat
Keyword(s):  
Electromagnetic Scattering ◽  
Vertical Profiles ◽  
Polarimetric Radar ◽  
Horizontal Polarization ◽  
One Dimensional ◽  
Microphysical Process ◽  
Warm Rain ◽  
Microphysical Processes ◽  
Differential Reflectivity ◽  
The Impact

Abstract The impact of the collisional warm-rain microphysical processes on the polarimetric radar variables is quantified using a coupled microphysics–electromagnetic scattering model. A one-dimensional bin-microphysical rain shaft model that resolves explicitly the evolution of the drop size distribution (DSD) under the influence of collisional coalescence and breakup, drop settling, and aerodynamic breakup is coupled with electromagnetic scattering calculations that simulate vertical profiles of the polarimetric radar variables: reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, and specific differential phase KDP. The polarimetric radar fingerprint of each individual microphysical process is quantified as a function of the shape of the initial DSD and for different values of nominal rainfall rate. Results indicate that individual microphysical processes (collisional processes, evaporation) display a distinctive signature and evolve within specific areas of ZH–ZDR and ZDR–KDP space. Furthermore, a comparison of the resulting simulated vertical profiles of the polarimetric variables with radar and disdrometer observations suggests that bin-microphysical parameterizations of drop breakup most frequently used are overly aggressive for the largest rainfall rates, resulting in very “tropical” DSDs heavily skewed toward smaller drops.

scholarly journals Correction of Radar Reflectivity and Differential Reflectivity for Rain Attenuation at X Band. Part II: Evaluation and Application

2005 ◽  
Vol 22 (11) ◽  
pp. 1633-1655 ◽  
Author(s):  
S-G. Park ◽  
M. Maki ◽  
K. Iwanami ◽  
V. N. Bringi ◽  
V. Chandrasekar
Keyword(s):  
Drop Size ◽  
Earth Science ◽  
Radar Data ◽  
Rain Gauge ◽  
Radar Rainfall ◽  
X Band ◽  
Rain Events ◽  
Differential Reflectivity ◽  
Rainfall Estimates ◽  
Good Agreement

Abstract In this paper, the attenuation-correction methodology presented in Part I is applied to radar measurements observed by the multiparameter radar at the X-band wavelength (MP-X) of the National Research Institute for Earth Science and Disaster Prevention (NIED), and is evaluated by comparison with scattering simulations using ground-based disdrometer data. Further, effects of attenuation on the estimation of rainfall amounts and drop size distribution parameters are also investigated. The joint variability of the corrected reflectivity and differential reflectivity show good agreement with scattering simulations. In addition, specific attenuation and differential attenuation, which are derived in the correction procedure, show good agreement with scattering simulations. In addition, a composite rainfall-rate algorithm is proposed and evaluated by comparison with eight gauges. The radar-rainfall estimates from the uncorrected (or observed) ZH produce severe underestimation, even at short ranges from the radar and for stratiform rain events. On the contrary, the reflectivity-based rainfall estimates from the attenuation-corrected ZH does not show such severe underestimation and does show better agreement with rain gauge measurements. More accurate rainfall amounts can be obtained from a simple composite algorithm based on specific differential phase KDP, with the R(ZH_cor) estimates being used for low rainfall rates (KDP ≤ 0.3° km−1 or ZH_cor ≤ 35 dBZ). This improvement in accuracy of rainfall estimation based on KDP is a result of the insensitivity of the rainfall algorithm to natural variations of drop size distributions (DSDs). The ZH, ZDR, and KDP data are also used to infer the parameters (median volume diameter D0 and normalized intercept parameter Nw) of a normalized gamma DSD. The retrieval of D0 and Nw from the corrected radar data show good agreement with those from disdrometer data in terms of the respective relative frequency histograms. The results of this study demonstrate that high-quality hydrometeorological information on rain events such as rainfall amounts and DSDs can be derived from X-band polarimetric radars.

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