Rainfall estimation from X-band dual polarization radar using reflectivity and differential reflectivity

Abstract This paper presents new methods for rainfall estimation from X-band dual-polarization radar observations along with advanced techniques for quality control, hydrometeor classification, and estimation of specific differential phase. Data collected from the Hydrometeorology Testbed (HMT) in orographic terrain of California are used to demonstrate the methodology. The quality control and hydrometeor classification are specifically developed for X-band applications, which use a “fuzzy logic” technique constructed from the magnitude of the copolar correlation coefficient and the texture of differential propagation phase. In addition, an improved specific differential phase retrieval and rainfall estimation method are also applied. The specific differential phase estimation is done for both the melting region and rain region, where it uses a conventional filtering method for the melting region and a self-consistency-based method that distributes the total differential phase consistent with the reflectivity factor for the rain region. Based on the specific differential phase, rainfall estimations were computed using data obtained from the NOAA polarimetric X-band radar for hydrometeorology (HYDROX) and evaluated using HMT rain gauge observations. The results show that the methodology works well at capturing the high-frequency rainfall variations for the events analyzed herein and can be useful for mountainous terrain applications.

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

Atmospheric Measurement Techniques ◽

10.5194/amt-12-5897-2019 ◽

2019 ◽

Vol 12 (11) ◽

pp. 5897-5911 ◽

Cited By ~ 5

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.

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On the performance of X-band dual-polarization radar-rainfall estimation algorithms during the SMAPVEX-16 field campaign

10.17077/etd.r2jq-i3ql ◽

2019 ◽

Author(s):

John R. Brammeier

Keyword(s):

Dual Polarization ◽

Rainfall Estimation ◽

Radar Rainfall ◽

Field Campaign ◽

Estimation Algorithms ◽

X Band

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A New Dual-Polarization Radar Rainfall Algorithm: Application in Colorado Precipitation Events

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2010jtecha1488.1 ◽

2011 ◽

Vol 28 (3) ◽

pp. 352-364 ◽

Cited By ~ 110

Author(s):

R. Cifelli ◽

V. Chandrasekar ◽

S. Lim ◽

P. C. Kennedy ◽

Y. Wang ◽

...

Keyword(s):

Estimation Algorithm ◽

State University ◽

Dual Polarization ◽

Rainfall Estimation ◽

Radar Rainfall ◽

Colorado State University ◽

Differential Phase ◽

Precipitation Estimation ◽

The One ◽

Differential Reflectivity

Abstract The efficacy of dual-polarization radar for quantitative precipitation estimation (QPE) has been demonstrated in a number of previous studies. Specifically, rainfall retrievals using combinations of reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) have advantages over traditional Z–R methods because more information about the drop size distribution (DSD) and hydrometeor type are available. In addition, dual-polarization-based rain-rate estimators can better account for the presence of ice in the sampling volume. An important issue in dual-polarization rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? At Colorado State University (CSU), an optimization algorithm has been developed and used for a number of years to estimate rainfall based on thresholds of Zh, Zdr, and Kdp. Although the algorithm has demonstrated robust performance in both tropical and midlatitude environments, results have shown that the retrieval is sensitive to the selection of the fixed thresholds. In this study, a new rainfall algorithm is developed using hydrometeor identification (HID) to guide the choice of the particular rainfall estimation algorithm. A separate HID algorithm has been developed primarily to guide the rainfall application with the hydrometeor classes, namely, all rain, mixed precipitation, and all ice. Both the data collected from the S-band Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar and a network of rain gauges are used to evaluate the performance of the new algorithm in mixed rain and hail in Colorado. The evaluation is also performed using an algorithm similar to the one developed for the Joint Polarization Experiment (JPOLE). Results show that the new CSU HID-based algorithm provides good performance for the Colorado case studies presented here.

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

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0059.1 ◽

2016 ◽

Vol 55 (12) ◽

pp. 2549-2574 ◽

Cited By ~ 7

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.

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

Atmosphere ◽

10.3390/atmos9090348 ◽

2018 ◽

Vol 9 (9) ◽

pp. 348 ◽

Cited By ~ 2

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.

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Urban flash flood applications of high-resolution rainfall estimation by X-band dual-polarization radar network

10.1117/12.977602 ◽

2012 ◽

Cited By ~ 4

Author(s):

V. Chandrasekar ◽

Haonan Chen ◽

Masayuki Maki

Keyword(s):

High Resolution ◽

Flash Flood ◽

Dual Polarization ◽

Rainfall Estimation ◽

Radar Network ◽

X Band

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech1950.1 ◽

2006 ◽

Vol 23 (12) ◽

pp. 1668-1681 ◽

Cited By ~ 45

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.

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

Monthly Weather Review ◽

10.1175/mwr3349.1 ◽

2007 ◽

Vol 135 (4) ◽

pp. 1522-1543 ◽

Cited By ~ 89

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.

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