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

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.

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

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.

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

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.

scholarly journals Linear Depolarization Ratios of Columnar Ice Crystals in a Deep Precipitating System over the Arctic Observed by Zenith-Pointing Ka-Band Doppler Radar

2015 ◽  
Vol 54 (5) ◽  
pp. 1060-1068 ◽  
Author(s):  
Mariko Oue ◽  
Matthew R. Kumjian ◽  
Yinghui Lu ◽  
Johannes Verlinde ◽  
Kultegin Aydin ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Ice Crystals ◽  
The Arctic ◽  
Doppler Velocity ◽  
Ice Crystal ◽  
Ka Band ◽  
Growth Regime ◽  
Linear Depolarization Ratio ◽  
Velocity Spectra ◽  
Ice Production

AbstractThis study demonstrates that linear depolarization ratio (LDR) values obtained from zenith-pointing Ka-band radar Doppler velocity spectra are sufficient for detecting columnar ice crystals. During a deep precipitating system over the Arctic on 7 December 2013, the radar recorded LDR values up to −15 dB at temperatures corresponding to the columnar ice crystal growth regime. These LDR values were also consistent with scattering calculations for columnar ice crystals. Enhancements in LDR were suppressed within precipitation fallstreaks because the enhanced LDR values of columnar ice crystals were masked by the returns from the particles within the fallstreaks. However, Doppler velocity spectra of LDR within the fallstreak distinguished populations of slower-falling particles with high LDR (>−15 dB) and faster-falling particles with much lower LDR, suggesting that columnar ice crystals with high LDR coexisted with larger isometric particles that produced low LDR while dominating the total copolar reflectivity, thereby decreasing LDR. The measurements suggest that the columnar ice crystals originated in liquid-cloud layers through secondary ice production.

scholarly journals Estimation of liquid water path below the melting layer in stratiform precipitation systems using radar measurements during MC3E

2019 ◽  
Vol 12 (7) ◽  
pp. 3743-3759 ◽  
Author(s):  
Jingjing Tian ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Christopher R. Williams ◽  
Peng Wu
Keyword(s):  
Liquid Water ◽  
Department Of Energy ◽  
Cloud Base ◽  
Retrieval Algorithm ◽  
Doppler Velocity ◽  
Liquid Water Path ◽  
Water Path ◽  
Melting Layer ◽  
Stratiform Precipitation ◽  
Cloud Particles

Abstract. In this study, the liquid water path (LWP) below the melting layer in stratiform precipitation systems is retrieved, which is a combination of rain liquid water path (RLWP) and cloud liquid water path (CLWP). The retrieval algorithm uses measurements from the vertically pointing radars (VPRs) at 35 and 3 GHz operated by the US Department of Energy Atmospheric Radiation Measurement (ARM) and National Oceanic and Atmospheric Administration (NOAA) during the field campaign Midlatitude Continental Convective Clouds Experiment (MC3E). The measured radar reflectivity and mean Doppler velocity from both VPRs and spectrum width from the 35 GHz radar are utilized. With the aid of the cloud base detected by a ceilometer, the LWP in the liquid layer is retrieved under two different situations: (I) no cloud exists below the melting base, and (II) cloud exists below the melting base. In (I), LWP is primarily contributed from raindrops only, i.e., RLWP, which is estimated by analyzing the Doppler velocity differences between two VPRs. In (II), cloud particles and raindrops coexist below the melting base. The CLWP is estimated using a modified attenuation-based algorithm. Two stratiform precipitation cases (20 and 11 May 2011) during MC3E are illustrated for two situations, respectively. With a total of 13 h of samples during MC3E, statistical results show that the occurrence of cloud particles below the melting base is low (9 %); however, the mean CLWP value can be up to 0.56 kg m−2, which is much larger than the RLWP (0.10 kg m−2). When only raindrops exist below the melting base, the average RLWP value is larger (0.32 kg m−2) than the with-cloud situation. The overall mean LWP below the melting base is 0.34 kg m−2 for stratiform systems during MC3E.

scholarly journals Clutter mitigation, multiple peaks, and high-order spectral moments in 35 GHz vertically pointing radar velocity spectra

2018 ◽  
Vol 11 (9) ◽  
pp. 4963-4980 ◽  
Author(s):  
Christopher R. Williams ◽  
Maximilian Maahn ◽  
Joseph C. Hardin ◽  
Gijs de Boer
Keyword(s):  
Processing Method ◽  
High Order ◽  
Doppler Velocity ◽  
Velocity Spectrum ◽  
Processing Methods ◽  
Ka Band ◽  
Multiple Peaks ◽  
Multiple Peak ◽  
Ground Clutter ◽  
Velocity Spectra

Abstract. This study presents and applies three separate processing methods to improve high-order moments estimated from 35 GHz (Ka band) vertically pointing radar Doppler velocity spectra. The first processing 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 (OLI), Alaska. Ground clutter resulted from multiple pathways through antenna side lobes and reflections off a rotating scanning radar antenna located 2 m away from KAZR, which 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 separate and sub-peaks in the spectra and estimates high-order moments for each peak. Multiple peaks and high-order moments were estimated for both original 2 and 15 s averaged spectra. The third processing step improves the spectrum variance, skewness, and kurtosis estimates by removing velocity variability due to turbulent broadening during 15 s averaging intervals. Applying the multiple peak processing to Doppler velocity spectra during liquid-only clouds can identify cloud and drizzle particles and during mixed-phase clouds can identify liquid cloud and frozen hydrometeors. 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 hydrometeor populations and then use multiple-peak moments for quantitative studies. Three future activities will continue this work. First, KAZR spectra from several ARM sites have been processed and are available in the ARM archive as a principal investigator (PI) product. ARM programmers are evaluating these processing methods as part of future multiple-peak products generated by ARM. Third, MATLAB code generating the Oliktok Point products has been uploaded as supplemental material for public dissemination.

scholarly journals Analysis of the microphysical properties of snowfall using scanning polarimetric and vertically pointing multi-frequency Doppler radars

2021 ◽  
Vol 14 (7) ◽  
pp. 4893-4913
Author(s):  
Mariko Oue ◽  
Pavlos Kollias ◽  
Sergey Y. Matrosov ◽  
Alessandro Battaglia ◽  
Alexander V. Ryzhkov
Keyword(s):  
Early Stage ◽  
Particle Growth ◽  
Particle Identification ◽  
Joint Analysis ◽  
Doppler Velocity ◽  
Polarimetric Radar ◽  
Dual Frequency ◽  
Growth Processes ◽  
Ka Band ◽  
Triple Frequency

Abstract. Radar dual-wavelength ratio (DWR) measurements from the Stony Brook Radar Observatory Ka-band scanning polarimetric radar (KASPR, 35 GHz), a W-band profiling radar (94 GHz), and a next-generation K-band (24 GHz) micro rain radar (MRRPro) were exploited for ice particle identification using triple-frequency approaches. The results indicated that two of the radar frequencies (K and Ka band) are not sufficiently separated; thus, the triple-frequency radar approaches had limited success. On the other hand, a joint analysis of DWR, mean Doppler velocity (MDV), and polarimetric radar variables indicated potential in identifying ice particle types and distinguishing among different ice growth processes and even in revealing additional microphysical details. We investigated all DWR pairs in conjunction with MDV from the KASPR profiling measurements and differential reflectivity (ZDR) and specific differential phase (KDP) from the KASPR quasi-vertical profiles. The DWR-versus-MDV diagrams coupled with the polarimetric observables exhibited distinct separations of particle populations attributed to different rime degrees and particle growth processes. In fallstreaks, the 35–94 GHz DWR pair increased with the magnitude of MDV corresponding to the scattering calculations for aggregates with lower degrees of riming. The DWR values further increased at lower altitudes while ZDR slightly decreased, indicating further aggregation. Particle populations with higher rime degrees had a similar increase in DWR but a 1–1.5 m s−1 larger magnitude of MDV and rapid decreases in KDP and ZDR. The analysis also depicted the early stage of riming where ZDR increased with the MDV magnitude collocated with small increases in DWR. This approach will improve quantitative estimations of snow amount and microphysical quantities such as rime mass fraction. The study suggests that triple-frequency measurements are not always necessary for in-depth ice microphysical studies and that dual-frequency polarimetric and Doppler measurements can successfully be used to gain insights into ice hydrometeor microphysics.

scholarly journals High-Resolution Observations of Mammatus in Tropical Anvils

2005 ◽  
Vol 133 (7) ◽  
pp. 2105-2112 ◽  
Author(s):  
Pavlos Kollias ◽  
Ieng Jo ◽  
Bruce A. Albrecht
Keyword(s):  
High Resolution ◽  
Power Spectra ◽  
High Sensitivity ◽  
Cloud Base ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Small Scale ◽  
Cirrus Cloud ◽  
Regional Study ◽  
Spectra Analysis

Abstract Unprecedented high-resolution observations of mammatus from a profiling 94-GHz Doppler radar during the NASA Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL–FACE) are presented. Because of its high sensitivity and temporal and spatial resolution, the cloud radar used was able to resolve the fine structure of individual mammatus clouds and record significant vertical Doppler velocity perturbations (−6 to +1 m s−1). Strong perturbations of the Doppler velocity within the mammatus as it extends below the main cirrus cloud base are captured by the radar observations. Upward motions in the periphery of descending mammatus cores are documented. Areas of intense, small-scale turbulent mixing near the cirrus cloud base are identified using the Doppler spectrum width. Power spectra analysis of the mean Doppler velocity field supports the presence of gravity waves and the development of higher-frequency structures near the cirrus anvil base, where the mammatus clouds are observed. The observations provide strong evidence for dynamical forcing from coherent vertical motions 500 m above the cloud base contributing to the mammatus formation. The results are discussed in the context of suggested theories for mamma formation and morphology.

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

2016 ◽  
Vol 55 (2) ◽  
pp. 403-424 ◽  
Author(s):  
Mariko Oue ◽  
Michele Galletti ◽  
Johannes Verlinde ◽  
Alexander Ryzhkov ◽  
Yinghui Lu
Keyword(s):  
Department Of Energy ◽  
Doppler Velocity ◽  
Ka Band ◽  
Surface Precipitation ◽  
X Band ◽  
Lidar Measurements ◽  
Atmospheric Radiation Measurement ◽  
Microphysical Processes ◽  
Mixed Phase Clouds ◽  
Differential Reflectivity

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.

Supplementary material to "Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra"

2021 ◽  
Author(s):  
Christopher R. Williams ◽  
Karen L. Johnson ◽  
Scott E. Giangrande ◽  
Joseph C. Hardin ◽  
Ruşen Öktem ◽  
...  
Keyword(s):  
Doppler Velocity ◽  
Polarimetric Radar ◽  
Supplementary Material ◽  
Velocity Spectra

scholarly journals Estimation of Liquid Water Path in Stratiform Precipitation Systems using Radar Measurements during MC3E

2019 ◽  
Author(s):  
Jingjing Tian ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Christopher R. Williams ◽  
Peng Wu
Keyword(s):  
Liquid Layer ◽  
Liquid Water ◽  
Department Of Energy ◽  
Cloud Base ◽  
Retrieval Algorithm ◽  
Doppler Velocity ◽  
Liquid Water Path ◽  
Water Path ◽  
Stratiform Precipitation ◽  
Cloud Particles

Abstract. In this study, the liquid water path (LWP) in stratiform precipitation systems is retrieved, which is a combination of rain liquid water path (RLWP) and cloud liquid water path (CLWP). The retrieval algorithm uses measurements from the vertically pointing radars (VPRs) at 35 GHz and 3 GHz operated by the U.S Department of Energy Atmospheric Radiation Measurement (ARM) and National Oceanic and Atmospheric Administration (NOAA) during the field campaign Midlatitude Continental Convective Clouds Experiment (MC3E). The measured radar reflectivity and mean Doppler velocity from both VPRs and spectrum width from the 35 GHz radar are utilized. With the aid of the cloud base detected by ceilometer, the LWP in the liquid layer is retrieved under two different situations: (I) no cloud exists below the melting base, and (II) cloud exists below the melting base. In (I), LWP is primarily contributed from raindrops only, i.e., RLWP, which is estimated by analyzing the Doppler velocity differences between two VPRs. In (II), cloud particles and raindrops coexist in the liquid layer. The CLWP is estimated using a modified attenuation-based algorithm. Two stratiform precipitation cases (20 May 2011 and 11 May 2011) during MC3E are illustrated for two situations, respectively. With a total of 14 hours of samples during MC3E, statistical results show that the occurrence of cloud particles below the melting base is low (8 %), however, the mean CLWP value can be up to 0.87 kg m−2, which is much larger than the RLWP (0.22 kg m−2). When only raindrops exist below the melting base, the averaged RLWP value is larger (0.33 kg m−2) than the with cloud situation. The overall mean LWP below the melting base is 0.39 kg m−2 for stratiform systems during MC3E.

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