Use of X-Band Differential Reflectivity Measurements to Study Shallow Arctic Mixed-Phase Clouds

AbstractMicrophysical processes in shallow Arctic precipitation clouds are illustrated using measurements of differential reflectivity ZDR from the U.S. Department of Energy Atmospheric Radiation Measurement Program polarimetric X-band radar deployed in Barrow, Alaska. X-band hemispheric range height indicator scans used in conjunction with Ka-band radar and lidar measurements revealed prolonged periods dominated by vapor depositional, riming, and/or aggregation growth. In each case, ice precipitation fell through at least one liquid-cloud layer in a seeder–feeder situation before reaching the surface. A long period of sustained low radar reflectivity ZH (<0–5 dBZ) and high ZDR (6–7.5 dB) throughout the depth of the cloud and subcloud layer, coinciding with observations of large pristine dendrites at the surface, suggests vapor depositional growth of large dendrites at low number concentrations. In contrast, ZDR values decreased to 2–3 dB in the mean profile when surface precipitation was dominated by aggregates or rimed dendrites. Small but consistent differences in zenith Ka-band radar Doppler velocity and lidar depolarization measurements were found between aggregation- and riming-dominated periods. The clean Arctic environment can enhance ZDR signals relative to more complex midlatitude cases, producing higher values.

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Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra

10.5194/amt-2021-27 ◽

2021 ◽

Author(s):

Christopher R. Williams ◽

Karen L. Johnson ◽

Scott E. Giangrande ◽

Joseph C. Hardin ◽

Ruşen Öktem ◽

...

Keyword(s):

Power Spectra ◽

Department Of Energy ◽

Cloud Base ◽

Doppler Velocity ◽

Polarimetric Radar ◽

Ka Band ◽

Ice Particles ◽

Linear Depolarization Ratio ◽

Velocity Spectra ◽

Discrimination Method

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The insect-hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects versus cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra linear depolarization ratio (LDR) produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives this need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Comparison with a collocated ceilometer indicates that hydrometeor mask column bottoms are within +/-100 meters of simultaneous ceilometer cloud base heights. Forty-seven (47) summer-time days were processed with the insect-hydrometeor discrimination method using U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma (USA). All datasets and images are available on public repositories.

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Automated rain rate estimates using the Ka-band ARM zenith radar (KAZR)

Atmospheric Measurement Techniques ◽

10.5194/amt-8-3685-2015 ◽

2015 ◽

Vol 8 (9) ◽

pp. 3685-3699 ◽

Cited By ~ 13

Author(s):

A. Chandra ◽

C. Zhang ◽

P. Kollias ◽

S. Matrosov ◽

W. Szyrmer

Keyword(s):

Rain Rate ◽

Tropical Indian Ocean ◽

Rain Gauge ◽

Signal Attenuation ◽

Ka Band ◽

Automated Algorithm ◽

Atmospheric Radiation Measurement ◽

Microphysical Processes ◽

The Tropics ◽

Rain Rates

Abstract. The use of millimeter wavelength radars for probing precipitation has recently gained interest. However, estimation of precipitation variables is not straightforward due to strong signal attenuation, radar receiver saturation, antenna wet radome effects and natural microphysical variability. Here, an automated algorithm is developed for routinely retrieving rain rates from the profiling Ka-band (35-GHz) ARM (Atmospheric Radiation Measurement) zenith radars (KAZR). A 1-dimensional, simple, steady state microphysical model is used to estimate impacts of microphysical processes and attenuation on the profiles of radar observables at 35-GHz and thus provide criteria for identifying situations when attenuation or microphysical processes dominate KAZR observations. KAZR observations are also screened for signal saturation and wet radome effects. The algorithm is implemented in two steps: high rain rates are retrieved by using the amount of attenuation in rain layers, while low rain rates are retrieved from the reflectivity–rain rate (Ze–R) relation. Observations collected by the KAZR, rain gauge, disdrometer and scanning precipitating radars during the DYNAMO/AMIE field campaign at the Gan Island of the tropical Indian Ocean are used to validate the proposed approach. The differences in the rain accumulation from the proposed algorithm are quantified. The results indicate that the proposed algorithm has a potential for deriving continuous rain rate statistics in the tropics.

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X-Band Polarimetric and Ka-Band Doppler Spectral Radar Observations of a Graupel-Producing Arctic Mixed-Phase Cloud

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-14-0315.1 ◽

2015 ◽

Vol 54 (6) ◽

pp. 1335-1351 ◽

Cited By ~ 19

Author(s):

Mariko Oue ◽

Matthew R. Kumjian ◽

Yinghui Lu ◽

Zhiyuan Jiang ◽

Eugene E. Clothiaux ◽

...

Keyword(s):

Mixed Phase ◽

Growth Stages ◽

Bottom Edge ◽

Ka Band ◽

The Core ◽

Low Concentrations ◽

X Band ◽

Spatial Sorting ◽

Differential Reflectivity ◽

Different Growth Stages

AbstractCharacteristics of graupel in an Arctic deep mixed-phase cloud on 7 December 2013 were identified with observations from an X-band scanning polarimetric radar and a Ka-band zenith-pointing radar in conjunction with scattering calculations. The cloud system produced generating cells and strongly sheared precipitation fall streaks. The X-band radar hemispheric RHI observables revealed spatial sorting of polarimetric signatures: decreasing (with increasing range) differential propagation phase shift φDP, negative specific differential phase KDP collocated with negative differential reflectivity ZDR in the upper half of the fall streak, and increasing or near-constant φDP with positive ZDR at the bottom edge of the fall streak. The negative KDP and ZDR, indicating prolate particles with vertically oriented maximum dimensions, were consistent with small, slow-falling conical graupel coexisting with low concentrations of more isometric graupel. The observed negative KDP values were best matched by scattering calculations for small, dense conical graupel with 30°–40° cone angles. The positive KDP and ZDR and the Doppler spectra indicate that large isometric graupel coexisted with a second population of slower-falling rimed platelike particles in the lower half of the fall streak. Through the core of the fall streak, φDP decreased in range while ZDR was slightly positive, indicating that the prolate conical graupel dominated φDP while the isometric larger graupel dominated reflectivity (and thus ZDR). These results demonstrate the capability of polarimetric observables and Doppler spectra to distinguish different growth stages of rimed particles, allowing for the improvement of hydrometeor classification methods.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-15-0020.1 ◽

2016 ◽

Vol 33 (3) ◽

pp. 551-562 ◽

Cited By ~ 58

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.

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Signal Postprocessing and Reflectivity Calibration of the Atmospheric Radiation Measurement Program 915-MHz Wind Profilers

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-12-00146.1 ◽

2013 ◽

Vol 30 (6) ◽

pp. 1038-1054 ◽

Cited By ~ 18

Author(s):

Frédéric Tridon ◽

Alessandro Battaglia ◽

Pavlos Kollias ◽

Edward Luke ◽

Christopher R. Williams

Keyword(s):

Department Of Energy ◽

Dual Wavelength ◽

Doppler Velocity ◽

Atmospheric Radiation ◽

Absolute Calibration ◽

Wind Profiler ◽

Radiation Measurement ◽

High Quality ◽

Atmospheric Radiation Measurement ◽

Wind Profilers

Abstract The Department of Energy Atmospheric Radiation Measurement (ARM) Program has recently initiated a new research avenue toward a better characterization of the transition from cloud to precipitation. Dual-wavelength techniques applied to millimeter-wavelength radars and a Rayleigh reference have a great potential for rain-rate retrievals directly from dual-wavelength ratio measurements. In this context, the recent reconfiguration of the ARM 915-MHz wind profilers in a vertically pointing mode makes these instruments the ideal candidate for providing the Rayleigh reflectivity/Doppler velocity reference. Prior to any scientific study, the wind profiler data must be carefully quality checked. This work describes the signal postprocessing steps that are essential for the delivery of high-quality reflectivity and mean Doppler velocity products—that is, the estimation of the noise floor from clear-air echoes, the absolute calibration with a collocated disdrometer, the dealiasing of Doppler velocities, and the merging of the different modes of the wind profiler. The improvement added by the proposed postprocessing is confirmed by comparison with a high-quality S-band profiler deployed at the ARM Southern Great Plains site during the Midlatitude Continental Convective Clouds Experiment. With the addition of a vertically pointing mode and with the postprocessing described in this work in place, besides being a key asset for wind research wind profilers observations may therefore become a centerpiece for rain studies in the years to come.

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Connecting Microphysical Processes in Colorado Winter Storms with Vertical Profiles of Radar Observations

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-15-0338.1 ◽

2016 ◽

Vol 55 (8) ◽

pp. 1771-1787 ◽

Cited By ~ 15

Author(s):

Robert S. Schrom ◽

Matthew R. Kumjian

Keyword(s):

Dendritic Growth ◽

Doppler Velocity ◽

Front Range ◽

Horizontal Polarization ◽

Winter Storms ◽

Radar Observations ◽

Velocity Magnitude ◽

Microphysical Processes ◽

Project Data ◽

Differential Reflectivity

AbstractTo better connect radar observations to microphysical processes, the authors analyze concurrent polarimetric radar observations at vertical incidence and roughly side incidence during the Front Range Orographic Storms (FROST) project. Data from three events show signatures of riming, aggregation, and dendritic growth. Riming and the growth of graupel are suggested by negative differential reflectivity ZDR and vertically pointing Doppler velocity magnitude |VR| > 2.0 m s−1; aggregation is indicated by maxima in the downward-relative gradient of radar reflectivity at horizontal polarization ZH below the −15°C isotherm and positive downward-relative gradients in |VR| when averaged over time. A signature of positive downward-relative gradients in ZH, negative downward-relative gradients in |VR|, and maxima in ZDR is observed near −15°C during all three events. This signature may be indicative of dendritic growth; preexisting, thick platelike crystals fall faster and grow slower than dendrites, allowing for |VR| to shift toward the slower-falling, rapidly growing dendrites. To test this hypothesis, simplified calculations of the ZH and |VR| gradients are performed for a range of terminal fall speeds of dendrites and isometric crystals. The authors prescribe linear profiles of ZH for the dendrites and isometric crystals, with the resulting profiles and gradients of |VR| determined from a range of particle fall speeds. Both the observed ZH and |VR| gradients are reproduced by the calculations for a large range of fall speeds. However, more observational data are needed to fully constrain these calculations and reject or support explanations for this signature.

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Evaluation of modeled summertime convective storms using polarimetric radar observations

10.5194/acp-2021-404 ◽

2021 ◽

Author(s):

Prabhakar Shrestha ◽

Silke Trömel ◽

Raquel Evaristo ◽

Clemens Simmer

Keyword(s):

Three Dimensional ◽

Freezing Process ◽

Three Dimensional Flow ◽

Convective Storms ◽

Ensemble Simulations ◽

X Band ◽

Microphysical Processes ◽

High Precipitation ◽

Differential Reflectivity ◽

Forward Operator

Abstract. Ensemble simulations were conducted for three summertime convective storms over a temperate region in northwestern Germany using the Terrestrial Systems Modeling Platform (TSMP). The simulated microphysical processes were evaluated with polarimetric observations from two X-band radars, with the help of a forward operator applied to the model data. TSMP was found to generally underestimate the convective area fraction, high reflectivities, and the width/magnitude of so-called differential reflectivity (ZDR) columns indicative of updrafts, all leading to an underestimation of the frequency distribution for high precipitation values. The statistical distributions of ZDR and specific differential phase (KDP) were however similar, while the cross-correlation coefficient (phv) was poorly simulated, probably due to little variability of assumed hydrometeor shapes and orientations in the forward operator. The observed model bias in the ZDR columns could be associated with small size of supercooled raindrops and poorly resolved three dimensional flow at km-scale simulations, besides the treatment of freezing process in the model, which warrants further research.

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Clutter Mitigation, Multiple Peaks, and High-Order Spectral Moments in 35-GHz Vertically Pointing Radar Velocity Spectra

10.5194/amt-2018-66 ◽

2018 ◽

Author(s):

Christopher R. Williams ◽

Maximilian Maahn ◽

Joseph C. Hardin ◽

Gijs de Boer

Keyword(s):

Processing Method ◽

High Order ◽

Department Of Energy ◽

Doppler Velocity ◽

Velocity Spectrum ◽

Mean Velocity ◽

Ka Band ◽

Multiple Peaks ◽

Ground Clutter ◽

Velocity Spectra

Abstract. This study presents three separate processing methods to improve high-order moments estimated from 35-GHz (Ka-band) vertically pointing radar Doppler velocity spectra. The first method removes Doppler shifted ground clutter from spectra collected by a US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar (KAZR) deployed at Oliktok Point, Alaska. Multiple pathways through antenna side-lobes and reflections off a rotating scanning radar antenna located 2 m away from KAZR caused Doppler shifts in ground clutter returns from stationary targets 2.5 km away. After removing clutter in the recorded velocity spectra, the second processing method identifies multiple atmospheric peaks in the spectra and estimates high-order moments for each unique peak. Multiple peaks and high-order moments were estimated for both original 2-s and 15-s averaged spectra. The third processing method improves the spectrum breadth, skewness, and kurtosis estimates by removing 2-s velocity variability during 15-s averaging intervals. Assuming the cloud and precipitation microphysical properties do not change during the 15-s interval, shifting individual 2-s spectra to a common 15-s mean velocity before averaging removes 2-s temporal scale turbulent broadening. Consistent with previous studies, this work found that spectrum skewness assuming only a single spectral peak was a good indicator of two hydrometeor populations (for example, cloud and drizzle particles) being present in the radar pulse volume. Yet, after dividing the spectrum into multiple peaks, velocity spectrum skewness for individual peaks is near zero, indicating nearly symmetric peaks. This suggests that future studies should use velocity skewness of single peak spectra as an indicator of possible multiple peaks and then use multiple-peak moments for quantitative studies.

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Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

Atmospheric Measurement Techniques ◽

10.5194/amt-14-4425-2021 ◽

2021 ◽

Vol 14 (6) ◽

pp. 4425-4444

Author(s):

Christopher R. Williams ◽

Karen L. Johnson ◽

Scott E. Giangrande ◽

Joseph C. Hardin ◽

Ruşen Öktem ◽

...

Keyword(s):

Power Spectra ◽

Department Of Energy ◽

Cloud Base ◽

Doppler Velocity ◽

Polarimetric Radar ◽

Ka Band ◽

Ice Particles ◽

Linear Depolarization Ratio ◽

Velocity Spectra ◽

Discrimination Method

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-20-0062.1 ◽

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.

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