A Hydrometeor Classification Method for X-Band Polarimetric Radar: Construction and Validation Focusing on Solid Hydrometeors under Moist Environments

2015 ◽  
Vol 32 (11) ◽  
pp. 2052-2074 ◽  
Author(s):  
Takeharu Kouketsu ◽  
Hiroshi Uyeda ◽  
Tadayasu Ohigashi ◽  
Mariko Oue ◽  
Hiroto Takeuchi ◽  
...  
Keyword(s):  
Imaging System ◽  
Ice Crystals ◽  
Polarimetric Radar ◽  
X Band ◽  
Wet Snow ◽  
Moist Environment ◽  
Sampling Volume ◽  
In Situ Observations ◽  
Differential Reflectivity

AbstractA fuzzy-logic-based hydrometeor classification (HC) method for X-band polarimetric radar (X-pol), which is suitable for observation of solid hydrometeors under moist environments producing little or no hail, is constructed and validated. This HC method identifies the most likely hydrometeor at each radar sampling volume from eight categories: 1) drizzle, 2) rain, 3) wet snow aggregates, 4) dry snow aggregates, 5) ice crystals, 6) dry graupel, 7) wet graupel, and 8) rain–hail mixture. Membership functions are defined on the basis of previous studies. The HC method uses radar reflectivity Zh, differential reflectivity Zdr, specific differential phase Kdp, and correlation coefficient ρhv as its main inputs, and temperature with some consideration of relative humidity as supplemental information. The method is validated against ground and in situ observations of solid hydrometeors (dry graupel, dry snow aggregates, and ice crystals) under a moist environment. Observational data from a ground-based imaging system are used to validate the HC method for dry graupel and dry snow aggregates. For dry snow aggregates and ice crystals, the HC method is validated using simultaneous observations from a balloonborne instrument [hydrometeor videosonde (HYVIS)] and an X-pol range–height indicator directed toward the HYVIS. The HC method distinguishes effectively between dry graupel, dry snow aggregates, and ice crystals, and is therefore valid for HC under moist environments.

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 Determination of ice water content (IWC) in tropical convective clouds from X-band dual-polarization airborne radar

2019 ◽  
Vol 12 (11) ◽  
pp. 5897-5911 ◽  
Author(s):  
Cuong M. Nguyen ◽  
Mengistu Wolde ◽  
Alexei Korolev
Keyword(s):  
Water Content ◽  
Ice Crystals ◽  
Airborne Radar ◽  
Dual Polarization ◽  
Differential Phase ◽  
Convective Clouds ◽  
X Band ◽  
Ice Water Content ◽  
Differential Reflectivity ◽  
Ice Water

Abstract. This paper presents a methodology for ice water content (IWC) retrieval from a dual-polarization side-looking X-band airborne radar. Measured IWC from aircraft in situ probes is weighted by a function of the radar differential reflectivity (Zdr) to reduce the effects of ice crystal shape and orientation on the variation in IWC – specific differential phase (Kdp) joint distribution. A theoretical study indicates that the proposed method, which does not require a knowledge of the particle size distribution (PSD) and number density of ice crystals, is suitable for high-ice-water-content (HIWC) regions in tropical convective clouds. Using datasets collected during the High Altitude Ice Crystals – High Ice Water Content (HAIC-HIWC) international field campaign in Cayenne, French Guiana (2015), it is shown that the proposed method improves the estimation bias by 35 % and increases the correlation by 4 % on average, compared to the method using specific differential phase (Kdp) alone.

scholarly journals A Comparison of X-Band Polarization Parameters with In Situ Microphysical Measurements in the Comma Head of Two Winter Cyclones

2016 ◽  
Vol 55 (12) ◽  
pp. 2549-2574 ◽  
Author(s):  
Joseph A. Finlon ◽  
Greg M. McFarquhar ◽  
Robert M. Rauber ◽  
David M. Plummer ◽  
Brian F. Jewett ◽  
...  
Keyword(s):  
Sample Volume ◽  
Dual Polarization ◽  
Axis Ratio ◽  
Winter Storms ◽  
Frequency Distributions ◽  
X Band ◽  
Data Points ◽  
Measured Polarization ◽  
Differential Reflectivity

AbstractSince the advent of dual-polarization radar, methods of classifying hydrometeors by type from measured polarization variables have been developed. The deterministic approach of existing hydrometeor classification algorithms of assigning only one dominant habit to each radar sample volume does not properly consider the distribution of habits present in that volume, however. During the Profiling of Winter Storms field campaign, the “NSF/NCAR C-130” aircraft, equipped with in situ microphysical probes, made multiple passes through the comma heads of two cyclones as the Mobile Alabama X-band dual-polarization radar performed range–height indicator scans in the same plane as the C-130 flight track. On 14–15 February and 21–22 February 2010, 579 and 202 coincident data points, respectively, were identified when the plane was within 10 s (~1 km) of a radar gate. For all particles that occurred for times within different binned intervals of radar reflectivity ZHH and of differential reflectivity ZDR, the reflectivity-weighted contribution of each habit and the frequency distributions of axis ratio and sphericity were determined. This permitted the determination of habits that dominate particular ZHH and ZDR intervals; only 40% of the ZHH–ZDR bins were found to have a habit that contributes over 50% to the reflectivity in that bin. Of these bins, only 12% had a habit that contributes over 75% to the reflectivity. These findings show the general lack of dominance of a given habit for a particular ZHH and ZDR and suggest that determining the probability of specific habits in radar volumes may be more suitable than the deterministic methods currently used.

scholarly journals Hydrometeor Shape Variability in Snowfall as Retrieved from Polarimetric Radar Measurements

2020 ◽  
Vol 59 (9) ◽  
pp. 1503-1517
Author(s):  
Sergey Y. Matrosov ◽  
Alexander V. Ryzhkov ◽  
Maximilian Maahn ◽  
Gijs de Boer
Keyword(s):  
Aspect Ratio ◽  
Doppler Radar ◽  
Particle Model ◽  
Polarimetric Radar ◽  
Aspect Ratios ◽  
Air Temperatures ◽  
Radar Measurements ◽  
Differential Reflectivity ◽  
Particle Shapes

AbstractA polarimetric radar–based method for retrieving atmospheric ice particle shapes is applied to snowfall measurements by a scanning Ka-band radar deployed at Oliktok Point, Alaska (70.495°N, 149.883°W). The mean aspect ratio, which is defined by the hydrometeor minor-to-major dimension ratio for a spheroidal particle model, is retrieved as a particle shape parameter. The radar variables used for aspect ratio profile retrievals include reflectivity, differential reflectivity, and the copolar correlation coefficient. The retrievals indicate that hydrometeors with mean aspect ratios below 0.2–0.3 are usually present in regions with air temperatures warmer than approximately from −17° to −15°C, corresponding to a regime that has been shown to be favorable for growth of pristine ice crystals of planar habits. Radar reflectivities corresponding to the lowest mean aspect ratios are generally between −10 and 10 dBZ. For colder temperatures, mean aspect ratios are typically in a range between 0.3 and 0.8. There is a tendency for hydrometeor aspect ratios to increase as particles transition from altitudes in the temperature range from −17° to −15°C toward the ground. This increase is believed to result from aggregation and riming processes that cause particles to become more spherical and is associated with areas demonstrating differential reflectivity decreases with increasing reflectivity. Aspect ratio retrievals at the lowest altitudes are consistent with in situ measurements obtained using a surface-based multiangle snowflake camera. Pronounced gradients in particle aspect ratio profiles are observed at altitudes at which there is a change in the dominant hydrometeor species, as inferred by spectral measurements from a vertically pointing Doppler radar.

scholarly journals Glaciological Investigations Using the Synthetic Aperture Radar Imaging System

1987 ◽  
Vol 9 ◽  
pp. 11-19 ◽  
Author(s):  
R.A. Bindschadler ◽  
K.C. Jezek ◽  
J. Crawford
Keyword(s):  
Synthetic Aperture Radar ◽  
Imaging System ◽  
Synthetic Aperture ◽  
Data Sets ◽  
Landsat Images ◽  
Minimal Distortion ◽  
X Band ◽  
Wet Snow ◽  
Sar Imagery ◽  
Aperture Radar

Numerous examples of synthetic aperture radar (SAR) imagery of ice sheets are shown and prominent features of glaciological importance which appear in the images are discussed. Features which can be identified include surface undulations, ice-flow lines, crevasses, icebergs, lakes, and streams (even lakes and streams which are inactive or covered by snow), and possibly, the extent of the ablation and wet snow zones. SAR images presented here include both L-band data from the Seasat satellite and X-band data from an airborne radar. These two data sets overlap at a part of eastern Greenland where a direct comparison can be made between two images. Comparison is also made between SAR and Landsat images in western Greenland. It is concluded that SAR and Landsat are highly complementary instruments; Landsat images contain minimal distortion while SAR’s all-weather, day/night capability plus its ability to penetrate snow provide glaciologists with an additional and very powerful tool for research.

scholarly journals Use of Ground Clutter to Monitor Polarimetric Radar Calibration

2012 ◽  
Vol 29 (2) ◽  
pp. 159-176 ◽  
Author(s):  
L. Borowska ◽  
D. Zrnic
Keyword(s):  
Environmental Factors ◽  
Heavy Precipitation ◽  
Cold Season ◽  
Polarimetric Radar ◽  
Operational Monitoring ◽  
Ground Clutter ◽  
X Band ◽  
Hot Days ◽  
Radar Calibration ◽  
Differential Reflectivity

Abstract It is suggested that urban ground clutter can have a role in monitoring calibration of reflectivity factor ZH and differential reflectivity ZDR on polarimetric radars. The median and average values of these variables are considered. Analysis of data from 1 month of cold season in Germany (X-band radar) and 3.5 hot days in Oklahoma (S-band radar) is presented. In the presence of up to moderate rain or snow a reflectivity threshold suffices for separating significant clutter from precipitation observed with an X-band radar. The same threshold was suitable on observations with an S-band radar in Oklahoma because heavy precipitation was not present. The tests suggest the scheme is worthy considering for operational monitoring of ZH as its median values at both locations were within the quantization interval of 0.5 dB. Environmental factors that can influence reflectivities from clutter are examined. The effects on ZDR can be significant. These are quantified in the data and possible uses for calibration and monitoring radar status are indicated.

scholarly journals A new look at the environmental conditions favorable to secondary ice production

2019 ◽  
Author(s):  
Alexei Korolev ◽  
Ivan Heckman ◽  
Mengistu Wolde ◽  
Andrew S. Ackerman ◽  
Ann M. Fridlind ◽  
...  
Keyword(s):  
Ice Crystals ◽  
Liquid Drops ◽  
Melting Layer ◽  
Convective Systems ◽  
Spatially Correlated ◽  
Ice Particles ◽  
Mesoscale Convective ◽  
In Situ Observations ◽  
Ice Production

Abstract. This study attempts identification of mechanisms of secondary ice production (SIP) based on the observation of small faceted ice crystals (hexagonal plates or columns) with characteristic sizes smaller than 100 μm. Due to their young age, such small ice crystals can be used as tracers for identifying the conditions for SIP. Observations reported here were conducted in oceanic tropical mesoscale convective systems (MCS) and mid-latitude frontal clouds in the temperature range from 0 °C to −15 °C heavily seeded by aged ice particles. It was found that both in MCSs and frontal clouds, SIP was observed right above the melting layer and extended to the higher altitudes with colder temperatures. It is proposed that the initiation of SIP above the melting layer is related to the circulation of liquid drops through the melting layer. Liquid drops formed via melting ice particles are advected by the convective updrafts above the melting layer, where they impact with aged ice, freeze and shatter. The ice splinters generated by shattering initiate the chain reaction of SIP. The size of the splinters generated during SIP were estimated as 10 μm or less. In most SIP cases, small secondary ice particles spatially correlated with liquid phase, vertical updrafts and aged rimed ice particles. However, in many cases neither graupel nor liquid drops were observed in the SIP regions, and therefore, the conditions for an active Hallett-Mossop process were not met. A principal conclusion of this work is that the freezing drop shattering mechanism is alone among established SIP mechanisms is plausibly accounting for the measured ice concentrations in the observed conditions. No other SIP mechanisms could be confidently identified from the airborne in-situ observations.

scholarly journals Glaciological Investigations Using the Synthetic Aperture Radar Imaging System

1987 ◽  
Vol 9 ◽  
pp. 11-19 ◽  
Author(s):  
R.A. Bindschadler ◽  
K.C. Jezek ◽  
J. Crawford
Keyword(s):  
Synthetic Aperture Radar ◽  
Imaging System ◽  
Synthetic Aperture ◽  
Data Sets ◽  
Landsat Images ◽  
Minimal Distortion ◽  
X Band ◽  
Wet Snow ◽  
Sar Imagery ◽  
Aperture Radar

Numerous examples of synthetic aperture radar (SAR) imagery of ice sheets are shown and prominent features of glaciological importance which appear in the images are discussed. Features which can be identified include surface undulations, ice-flow lines, crevasses, icebergs, lakes, and streams (even lakes and streams which are inactive or covered by snow), and possibly, the extent of the ablation and wet snow zones. SAR images presented here include both L-band data from the Seasat satellite and X-band data from an airborne radar. These two data sets overlap at a part of eastern Greenland where a direct comparison can be made between two images. Comparison is also made between SAR and Landsat images in western Greenland. It is concluded that SAR and Landsat are highly complementary instruments; Landsat images contain minimal distortion while SAR’s all-weather, day/night capability plus its ability to penetrate snow provide glaciologists with an additional and very powerful tool for research.

scholarly journals Characterization of Hydrometeors in Sahelian Convective Systems with an X-Band Radar and Comparison with In Situ Measurements. Part I: Sensitivity of Polarimetric Radar Particle Identification Retrieval and Case Study Evaluation

2016 ◽  
Vol 55 (2) ◽  
pp. 231-249 ◽  
Author(s):  
F. Cazenave ◽  
M. Gosset ◽  
M. Kacou ◽  
M. Alcoba ◽  
E. Fontaine ◽  
...  
Keyword(s):  
Relative Proportion ◽  
In Situ Measurements ◽  
Particle Identification ◽  
Squall Line ◽  
Polarimetric Radar ◽  
Dense Particle ◽  
Convective Systems ◽  
X Band ◽  
Study Evaluation

AbstractThe particle identification scheme developed by Dolan and Rutledge for X-band polarimetric radar is tested for the first time in Africa and compared with in situ measurements. The data were acquired during the Megha-Tropiques mission algorithm-validation campaign that occurred in Niger in 2010. The radar classification is compared with the in situ observations gathered by an instrumented aircraft for the 13 August 2010 squall-line case. An original approach has been developed for the radar–in situ comparison: it consists of simulating synthetic radar variables from the microphysical-probe information and comparing the two datasets in a common “radar space.” The consistency between the two types of observation is good considering the differences in sampling illustrated in the paper. The time evolution of the hydrometeor types and their relative proportion in the convective and stratiform regions are analyzed. The farther away from the convection one looks, the more aggregation dominates, riming diminishes, and hydrometeors are less dense. Particle identification based on the polarimetric radar will be applied to a 5-yr African dataset in the future.

scholarly journals Retrieval of lower-order moments of the drop size distribution using CSU-CHILL X-band polarimetric radar: a case study

2020 ◽  
Vol 13 (9) ◽  
pp. 4727-4750
Author(s):  
Viswanathan Bringi ◽  
Kumar Vijay Mishra ◽  
Merhala Thurai ◽  
Patrick C. Kennedy ◽  
Timothy H. Raupach
Keyword(s):  
Size Distribution ◽  
Lower Order ◽  
Drop Size ◽  
Radar Data ◽  
Drop Size Distribution ◽  
Polarimetric Radar ◽  
X Band ◽  
Double Moment ◽  
Differential Reflectivity

Abstract. The lower-order moments of the drop size distribution (DSD) have generally been considered difficult to retrieve accurately from polarimetric radar data because these data are related to higher-order moments. For example, the 4.6th moment is associated with a specific differential phase and the 6th moment with reflectivity and ratio of high-order moments with differential reflectivity. Thus, conventionally, the emphasis has been to estimate rain rate (3.67th moment) or parameters of the exponential or gamma distribution for the DSD. Many double-moment “bulk” microphysical schemes predict the total number concentration (the 0th moment of the DSD, or M0) and the mixing ratio (or equivalently, the 3rd moment M3). Thus, it is difficult to compare the model outputs directly with polarimetric radar observations or, given the model outputs, forward model the radar observables. This article describes the use of double-moment normalization of DSDs and the resulting stable intrinsic shape that can be fitted by the generalized gamma (G-G) distribution. The two reference moments are M3 and M6, which are shown to be retrievable using the X-band radar reflectivity, differential reflectivity, and specific attenuation (from the iterative correction of measured reflectivity Zh using the total Φdp constraint, i.e., the iterative ZPHI method). Along with the climatological shape parameters of the G-G fit to the scaled/normalized DSDs, the lower-order moments are then retrieved more accurately than possible hitherto. The importance of measuring the complete DSD from 0.1 mm onwards is emphasized using, in our case, an optical array probe with 50 µm resolution collocated with a two-dimensional video disdrometer with about 170 µm resolution. This avoids small drop truncation and hence the accurate calculation of lower-order moments. A case study of a complex multi-cell storm which traversed an instrumented site near the CSU-CHILL radar is described for which the moments were retrieved from radar and compared with directly computed moments from the complete spectrum measurements using the aforementioned two disdrometers. Our detailed validation analysis of the radar-retrieved moments showed relative bias of the moments M0 through M2 was <15 % in magnitude, with Pearson’s correlation coefficient >0.9. Both radar measurement and parameterization errors were estimated rigorously. We show that the temporal variation of the radar-retrieved mass-weighted mean diameter with M0 resulted in coherent “time tracks” that can potentially lead to studies of precipitation evolution that have not been possible so far.

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