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 Evaluation of X-Band Dual-Polarization Radar-Rainfall Estimates from OLYMPEX

2019 ◽  
Vol 20 (9) ◽  
pp. 1941-1959 ◽  
Author(s):  
Yagmur Derin ◽  
Emmanouil Anagnostou ◽  
Marios Anagnostou ◽  
John Kalogiros
Keyword(s):  
Rainfall Variability ◽  
Dual Polarization ◽  
Significant Information ◽  
Radar Rainfall ◽  
Rain Gauges ◽  
X Band ◽  
Error Characterization ◽  
Median Volume ◽  
Multiparameter Measurements

Abstract The difficulty of representing high rainfall variability over mountainous areas using ground-based sensors is an open problem in hydrometeorology. Observations from locally deployed dual-polarization X-band radar have the advantage of providing multiparameter measurements near ground that carry significant information useful for estimating drop size distribution (DSD) and surface rainfall rate. Although these measurements are at fine spatiotemporal scale and are less inhibited by complex topography than operational radar network observations, uncertainties in their estimates necessitate error characterization based upon in situ measurements. During November 2015–February 2016, a dual-polarized Doppler on Wheels (DOW) X-band radar was deployed on the Olympic Peninsula of Washington State as part of NASA’s Olympic Mountain Experiment (OLYMPEX). In this study, rain gauges and disdrometers from a dense network positioned within 40 km of DOW are used to evaluate the self-consistency and accuracy of the attenuation and brightband/vertical profile corrections, and rain microphysics estimation by SCOP-ME, an algorithm that uses optimal parameterization and best-fitted functions of specific attenuation coefficients and DSD parameters with radar polarimetric measurements. In addition, the SCOP-ME precipitation microphysical retrievals of median volume diameter D0 and normalized intercept parameter NW are evaluated against corresponding parameters derived from the in situ disdrometer spectra observations.

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.

A Bayesian Approach for Integrated Raindrop Size Distribution (DSD) Retrieval on an X-Band Dual-Polarization Radar Network

2016 ◽  
Vol 33 (2) ◽  
pp. 377-389 ◽  
Author(s):  
Eiichi Yoshikawa ◽  
V. Chandrasekar ◽  
Tomoo Ushio ◽  
Takahiro Matsuda
Keyword(s):  
Size Distribution ◽  
Estimation Accuracy ◽  
Dual Polarization ◽  
Estimation Errors ◽  
Axis Ratio ◽  
Radar Network ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Radar Measurements ◽  
Raindrop Size

AbstractA raindrop size distribution (DSD) retrieval method for a weather radar network consisting of several X-band dual-polarization radars is proposed. An iterative maximum likelihood (ML) estimator for DSD retrieval in a single radar was developed in the authors’ previous work, and the proposed algorithm in this paper extends the single-radar retrieval to radar-networked retrieval, where ML solutions in each single-radar node are integrated based on a Bayesian scheme in order to reduce estimation errors and to enhance accuracy. Statistical evaluations of the proposed algorithm were carried out using numerical simulations. The results with eight radar nodes showed that the bias and standard errors are −0.05 and 0.09 in log(Nw); and Nw (mm−1 m−3) and 0.04 and 0.09 in D0 (mm) in an environment with fluctuations in dual-polarization radar measurements (normal distributions with standard deviations of 0.8 dBZ, 0.2 dB, and 1.5° in ZHm, ZDRm, and ΦDPm, respectively). Further error analyses indicated that the estimation accuracy depended on the number of radar nodes, the ranges of varying μ, the raindrop axis ratio model, and the system bias errors in dual-polarization radar measurements.

scholarly journals Characteristic Analysis of the Downburst in Greely, Colorado on 30 July 2017 Using WPEA Method and X-Band Radar Observations

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 348 ◽  
Author(s):  
Hao Wang ◽  
Venkatachalam Chandrasekar ◽  
Jianxin He ◽  
Zhao Shi ◽  
Lijuan Wang
Keyword(s):  
Phase Distribution ◽  
Potential Temperature ◽  
Ground Surface ◽  
Dual Polarization ◽  
Characteristic Analysis ◽  
Radar Observations ◽  
X Band ◽  
Future Events ◽  
Low Altitude ◽  
Differential Reflectivity

As a manifestation of low-altitude wind shear, a downburst is a localized, strong downdraft that can lead to disastrous wind on the ground surface. For effective pre-warning and forecasting of downbursts, it is particularly critical to understand relevant weather features that occur before and during a downburst process. It is important to identify the macroscopic features associated with the downburst weather process before considering fine-scale observations because this would greatly increase the accuracy and timeliness of forecasts. Therefore, we applied the wind-vector potential-temperature energy analysis (WPEA) method and CSU-CHILL X-band dual-polarization radar to explore the features of the downburst process. Here it was found that prior to the occurrence of the downburst of interest, the specific areas that should be monitored in future events could be determined by studying the atmospherically unstable areas using the WPEA method. Combining the WPEA method with dual-polarization radar observations, we can better distinguish the phase distribution of the hydrometeor in the process and greatly enhance the judgment of the possibility of the downburst. From exploration of the microphysical features of the downburst, we further found that ‘Zdr (differential reflectivity) column’ can be regarded as an important early warning indicator of the location of the downburst. Finally, a schematic of the formation process of the downburst according to the analyses was produced.

Comparison of Two Raindrop Size Distribution Retrieval Algorithms for X-Band Dual Polarization Observations

2008 ◽  
Vol 9 (3) ◽  
pp. 589-600 ◽  
Author(s):  
Marios N. Anagnostou ◽  
Emmanouil N. Anagnostou ◽  
Jothiram Vivekanandan ◽  
Fred L. Ogden
Keyword(s):  
Size Distribution ◽  
Empirical Relation ◽  
Shape Parameters ◽  
Dual Polarization ◽  
Axis Ratio ◽  
Differential Phase Shift ◽  
Drop Shape ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Raindrop Size

Abstract In this study the authors evaluate two algorithms, the so-called beta (β) and constrained methods, proposed for retrieving the governing parameters of the “normalized” gamma drop size distribution (DSD) from dual-polarization radar measurements. The β method treats the drop axis ratio as a variable and computes drop shape and DSD parameters from radar reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase shift (KDP). The constrained method assumes that the axis-ratio relation is fixed and computes DSD parameters from ZH, ZDR, and an empirical relation between the DSD slope and shape parameters. The two techniques are evaluated for polarimetric X-band radar observations by comparing retrieved DSD parameters with disdrometer observations and examining simulated radar parameters for consistency. Error effects on the β method and constrained method retrievals are analyzed. The β approach is found to be sensitive to errors in KDP and to be less consistent with observations. Large retrieved β values are found to be associated with large retrieved DSD shape parameters and small median drop diameters. The constrained method provides reasonable rain DSD retrievals that agree better with disdrometer observations.

Correction of X-Band Radar Observation for Propagation Effects Based on the Self-Consistency Principle

2006 ◽  
Vol 23 (12) ◽  
pp. 1668-1681 ◽  
Author(s):  
Eugenio Gorgucci ◽  
V. Chandrasekar ◽  
Luca Baldini
Keyword(s):  
Attenuation Correction ◽  
Rain Attenuation ◽  
The Self ◽  
Dual Polarization ◽  
Adaptive Sensing ◽  
Rain Medium ◽  
X Band ◽  
Differential Reflectivity ◽  
Self Consistency ◽  
New Algorithms

Abstract New algorithms for rain attenuation correction of reflectivity factor and differential reflectivity are presented. Following the methodology suggested for the first time by Gorgucci et al., the new algorithms are developed based on the self-consistency principle, describing the interrelation between polarimetric measurements along the rain medium. There is an increasing interest in X-band radar systems, owing to the early success of the attenuation-correction procedures as well as the initiative of the Center for Collaborative Adaptive Sensing of the Atmosphere to deploy X-band radars in a networked fashion. In this paper, self-consistent algorithms for correcting attenuation and differential attenuation are developed. The performance of the algorithms for application to X-band dual-polarization radars is evaluated extensively. The evaluation is conducted based on X-band dual-polarization observations generated from S-band radar measurements. Evaluation of the new self-consistency algorithms shows significant improvement in performance compared to the current class of algorithms. In the case that reflectivity and differential reflectivity are calibrated between ±1 and ±0.2 dB, respectively, the new algorithms can estimate both attenuation and differential attenuation with less than 10% bias and 15% random error. In addition, the attenuation-corrected reflectivity and differential reflectivity are within 1–0.2 dB 96% and 99% of the time, respectively, demonstrating the good performance.

scholarly journals Close-Range Observations of Tornadoes in Supercells Made with a Dual-Polarization, X-Band, Mobile Doppler Radar

2007 ◽  
Vol 135 (4) ◽  
pp. 1522-1543 ◽  
Author(s):  
Howard B. Bluestein ◽  
Michael M. French ◽  
Robin L. Tanamachi ◽  
Stephen Frasier ◽  
Kery Hardwick ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Cross Correlation ◽  
Doppler Radar ◽  
Dual Polarization ◽  
Radar Beam ◽  
X Band ◽  
Close Range ◽  
Debris Cloud ◽  
The Cross ◽  
Differential Reflectivity

Abstract A mobile, dual-polarization, X-band, Doppler radar scanned tornadoes at close range in supercells on 12 and 29 May 2004 in Kansas and Oklahoma, respectively. In the former tornadoes, a visible circular debris ring detected as circular regions of low values of differential reflectivity and the cross-correlation coefficient was distinguished from surrounding spiral bands of precipitation of higher values of differential reflectivity and the cross-correlation coefficient. A curved band of debris was indicated on one side of the tornado in another. In a tornado and/or mesocyclone on 29 May 2004, which was hidden from the view of the storm-intercept team by precipitation, the vortex and its associated “weak-echo hole” were at times relatively wide; however, a debris ring was not evident in either the differential reflectivity field or in the cross-correlation coefficient field, most likely because the radar beam scanned too high above the ground. In this case, differential attenuation made identification of debris using differential reflectivity difficult and it was necessary to use the cross-correlation coefficient to determine that there was no debris cloud. The latter tornado’s parent storm was a high-precipitation (HP) supercell, which also spawned an anticyclonic tornado approximately 10 km away from the cyclonic tornado, along the rear-flank gust front. No debris cloud was detected in this tornado either, also because the radar beam was probably too high.

scholarly journals Determination of Ice Water Content (IWC) in tropical convective clouds from X-band dual-polarization airborne radar

2019 ◽  
Author(s):  
Cuong M. Nguyen ◽  
Mengistu Wolde ◽  
Alexei Korolev
Keyword(s):  
Water Content ◽  
Airborne Radar ◽  
Ice Crystal ◽  
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 of 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 Crystal – 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 15 % on average and reduces the root mean squared difference by 6 %, compared to the method using specific differential phase (Kdp) alone.

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.

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