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 Observations of Polarimetric Signatures in Supercells by an X-Band Mobile Doppler Radar

2013 ◽  
Vol 141 (1) ◽  
pp. 3-29 ◽  
Author(s):  
Jeffrey C. Snyder ◽  
Howard B. Bluestein ◽  
Vijay Venkatesh ◽  
Stephen J. Frasier
Keyword(s):  
Cross Correlation ◽  
Doppler Radar ◽  
Main Body ◽  
Significant Heterogeneity ◽  
Weather Radars ◽  
X Band ◽  
Central United States ◽  
Primary Focus ◽  
Left Section ◽  
Differential Reflectivity

Abstract Polarimetric weather radars significantly enhance the capability to infer the properties of scatterers within a resolution volume. Previous studies have identified several consistently seen polarimetric signatures in supercells observed in the central United States. Nearly all of these studies used data collected by fixed-site S- and C-band radars. Because there are few polarimetric mobile radars, relatively little has been documented in high-resolution polarimetric data from mobile radars. Compared to S and C bands, there has been very limited examination of polarimetric signatures at X band. The primary focus of this paper is on one signature that has not been documented previously and one that has had little documentation at X band. The first signature, seen in at least seven supercell datasets collected by a mobile, X-band, polarimetric radar, consists of a narrow band of locally reduced reflectivity factor ZH and differential reflectivity, typically near the location where the hook echo “attaches” to the main body of the storm echo. No consistent pattern is seen in radial velocity VR or copolar cross correlation ρHV. The small size of this feature suggests a significant heterogeneity in precipitation microphysics, the cause and impact of which are unknown. The greater resolution and the scattering differences at X band compared to other frequencies may make this feature more apparent. The second signature consists of anomalously low ρHV in areas of high ZH along the left section (relative to storm motion) of the bounded weak-echo region. Examples of other polarimetric signatures at X band are provided.

The Multiple-Vortex Structure of the El Reno, Oklahoma, Tornado on 31 May 2013

2018 ◽  
Vol 146 (8) ◽  
pp. 2483-2502 ◽  
Author(s):  
Howard B. Bluestein ◽  
Kyle J. Thiem ◽  
Jeffrey C. Snyder ◽  
Jana B. Houser
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Rapid Scan ◽  
X Band ◽  
Close Range ◽  
Formation And Evolution ◽  
Using Data ◽  
Secondary Vortices ◽  
The Right ◽  
Gust Front

Abstract This study documents the formation and evolution of secondary vortices associated within a large, violent tornado in Oklahoma based on data from a close-range, mobile, polarimetric, rapid-scan, X-band Doppler radar. Secondary vortices were tracked relative to the parent circulation using data collected every 2 s. It was found that most long-lived vortices (those that could be tracked for ≥15 s) formed within the radius of maximum wind (RMW), mainly in the left-rear quadrant (with respect to parent tornado motion), passing around the center of the parent tornado and dissipating closer to the center in the right-forward and left-forward quadrants. Some secondary vortices persisted for at least 1 min. When a Burgers–Rott vortex is fit to the Doppler radar data, and the vortex is assumed to be axisymmetric, the secondary vortices propagated slowly against the mean azimuthal flow; if the vortex is not assumed to be axisymmetric as a result of a strong rear-flank gust front on one side of it, then the secondary vortices moved along approximately with the wind.

Dual-Polarization Radar Data Analysis of the Impact of Ground-Based Glaciogenic Seeding on Winter Orographic Clouds. Part I: Mostly Stratiform Clouds

2015 ◽  
Vol 54 (9) ◽  
pp. 1944-1969 ◽  
Author(s):  
Xiaoqin Jing ◽  
Bart Geerts ◽  
Katja Friedrich ◽  
Binod Pokharel
Keyword(s):  
Radar Data ◽  
Control Area ◽  
Target Area ◽  
Dual Polarization ◽  
Stratiform Clouds ◽  
Orographic Clouds ◽  
Close Range ◽  
Glaciogenic Seeding ◽  
Differential Reflectivity ◽  
The Impact

AbstractThe impact of ground-based glaciogenic seeding on wintertime orographic, mostly stratiform clouds is analyzed by means of data from an X-band dual-polarization radar, the Doppler-on-Wheels (DOW) radar, positioned on a mountain pass. This study focuses on six intensive observation periods (IOPs) during the 2012 AgI Seeding Cloud Impact Investigation (ASCII) project in Wyoming. In all six storms, the bulk upstream Froude number below mountaintop exceeded 1 (suggesting unblocked flow), the clouds were relatively shallow (with bases below freezing), some liquid water was present, and orographic flow conditions were mostly steady. To examine the silver iodide (AgI) seeding effect, three study areas are defined (a control area, a target area upwind of the crest, and a lee target area), and comparisons are made between measurements from a treated period and those from an untreated period. Changes in reflectivity and differential reflectivity observed by the DOW at low levels during seeding are consistent with enhanced snow growth, by vapor diffusion and/or aggregation, for a case study and for the composite analysis of all six IOPs, especially at close range upwind of the mountain crest. These low-level changes may have been affected by natural changes aloft, however, as evident from differences in the evolution of the echo-top height in the control and target areas. Even though precipitation in the target region is strongly correlated with that in the control region, the authors cannot definitively attribute the change to seeding because there is a lack of knowledge about natural variability, nor can the outcome be generalized, because the sample size is small.

Does the weather affect the Chinese stock markets? Evidence from the analysis of DCCA cross-correlation coefficient

2014 ◽  
Vol 29 (01) ◽  
pp. 1450236 ◽  
Author(s):  
Guangxi Cao ◽  
Yan Han
Keyword(s):  
Correlation Coefficient ◽  
Stock Markets ◽  
Cross Correlation ◽  
Sunshine Duration ◽  
Statistical Test ◽  
Nonlinear Method ◽  
Weather Variables ◽  
Chinese Stock Markets ◽  
The Cross ◽  
The Relationship

Recent studies confirm that weather affects the Chinese stock markets, based on a linear model. This paper revisits this topic using DCCA cross-correlation coefficient (ρ DCCA (n)), which is a nonlinear method, to determine if weather variables (i.e., temperature, humidity, wind and sunshine duration) affect the returns/volatilities of the Shanghai and Shenzhen stock markets. We propose an asymmetric ρ DCCA (n) by improving the traditional ρ DCCA (n) to determine if different cross-correlated properties exist when one time series trending is either positive or negative. Further, we improve a statistical test for the asymmetric ρ DCCA (n). We find that cross-correlation exists between weather variables and the stock markets on certain time scales and that the cross-correlation is asymmetric. We also analyze the cross-correlation at different intervals; that is, the relationship between weather variables and the stock markets at different intervals is not always the same as the relationship on the whole.

scholarly journals Radar Remote Sensing of Precipitation in High Mountains: Detection and Characterization of Melting Layer in the Grenoble Valley, French Alps

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 784 ◽  
Author(s):  
Anil Kumar Khanal ◽  
Guy Delrieu ◽  
Frédéric Cazenave ◽  
Brice Boudevillain
Keyword(s):  
Remote Sensing ◽  
Correlation Coefficient ◽  
Vertical Profiles ◽  
Radar Remote Sensing ◽  
French Alps ◽  
X Band ◽  
The Mean ◽  
Velocity Spectra ◽  
Differential Reflectivity ◽  
Polar Correlation

The RadAlp experiment aims at developing advanced methods for rain and snow estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed in the French Alps, Grenoble region. It is composed of a Météo-France operated X-band MOUC radar (volumetric, Doppler and polarimetric) on top of the Mt Moucherotte (1920 m ASL), the X-band XPORT research radar (volumetric, Doppler, polarimetric), a K-band micro rain radar (MRR, Doppler, vertically pointing) and in situ sensors (rain gauges, disdrometers), latter three operated on the Grenoble campus (220 m ASL). Based on the observation that the precipitation phase changes at/below the elevation of mountain-top MOUC radar for more than 60% of the significant events, an algorithm for ML identification has been developed using valley-based radar systems: it uses the quasi vertical profiles of XPORT polarimetric measurements (horizontal and vertical reflectivity, differential reflectivity, cross-polar correlation coefficient) and the MRR vertical profiles of apparent falling velocity spectra. The algorithm produces time series of the altitudes and values of peaks and inflection points of the different radar observables. A literature review allows us to link the micro-physical processes at play during the melting process with the available polarimetric and Doppler signatures, e.g., (i) regarding the altitude differences between the peaks of reflectivity, cross-polar correlation coefficient and differential reflectivity, as well as (ii) regarding the co-variation of the profiles of Doppler velocity spectra and cross-polar correlation coefficient. A statistical analysis of the ML based on 42 rain events (98 h of XPORT data) is then proposed. Among other results, this study indicates that (i) the mean value of the ML width in Grenoble is 610 m with a standard deviation of 160 m; (ii) the mean altitude difference between the horizontal reflectivity and the ρ H V peaks is 90 m and the mean altitude difference between the ρ H V and Zdr peaks is 30 m; (iii) even for the limited rainrate range in the dataset (0–8.5 mm h − 1 ), the “intensity effect” is clear on the reflectivity profile and the ML width, as well as on polarimetric variables such as ρ H V peak value and the Zdr enhancement in the upper part of the profile. On the contrary, the study of both the “density effect” and the influence of the 0   ° C isotherm altitude did not yield significant results with the considered dataset; (iv) a principal component analysis on one hand shows the richness of the dataset since the first 2 PCs explain only 50% of the total variance and on the other hand the added-value of the polarimetric variables since they rank high in a ranking of the total variance explained by individual variables.

scholarly journals Modeling Complex System Correlation Using Detrended Cross-Correlation Coefficient

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Keqiang Dong ◽  
Hong Zhang ◽  
You Gao
Keyword(s):  
Complex System ◽  
Time Series ◽  
Correlation Coefficient ◽  
Cross Correlation ◽  
Heavy Tails ◽  
Correlation Property ◽  
Traffic Time Series ◽  
Cross Correlations ◽  
The Cross ◽  
Active Research

The understanding of complex systems has become an area of active research for physicists because such systems exhibit interesting dynamical properties such as scale invariance, volatility correlation, heavy tails, and fractality. We here focus on traffic dynamic as an example of a complex system. By applying the detrended cross-correlation coefficient method to traffic time series, we find that the traffic fluctuation time series may exhibit cross-correlation characteristic. Further, we show that two traffic speed time series derived from adjacent sections exhibit much stronger cross-correlations than the two speed series derived from adjacent lanes. Similarly, we also demonstrate that the cross-correlation property between the traffic volume variables from two adjacent sections is stronger than the cross-correlation property between the volume variables of adjacent lanes.

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 Observations of Ash, Ice, and Lightning within Pyrocumulus Clouds Using Polarimetric NEXRAD Radars and the National Lightning Detection Network

2017 ◽  
Vol 145 (12) ◽  
pp. 4899-4910 ◽  
Author(s):  
Kendell T. LaRoche ◽  
Timothy J. Lang
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Case Studies ◽  
Correlation Coefficient ◽  
Convective Cloud ◽  
Past Research ◽  
Polarimetric Radar ◽  
Dual Polarization ◽  
Lightning Detection ◽  
Differential Reflectivity

A pyrocumulus is a convective cloud that can develop over a wildfire. Under certain conditions, pyrocumulus clouds become vertically developed enough to produce lightning. NEXRAD dual-polarization weather radar and upgraded National Lightning Detection Network (NLDN) data were used to analyze 10 case studies of ash plumes and pyrocumulus clouds from 2013 that either did or did not produce detected lightning. Past research has shown that pyrocumulus cases are most likely to produce lightning when there is a decrease in differential reflectivity (toward 0 dB) and an increase in the correlation coefficient (to >0.8), as measured by polarimetric radar, due to the transition from pure smoke/ash to frozen hydrometeors. All pyrocumulus cases that produced lightning in this study displayed the polarimetric characteristics of rimed ice within their respective clouds. Time series analysis of radar-inferred ash and rimed ice volumes within ash plumes and pyrocumulus clouds showed that NLDN-detected lightning occurred only after the cloud contained significant amounts of precipitation-sized rimed ice. The results suggest that the recently dual-pol-enabled NEXRADs and the more sensitive NLDN network can be used to explore ash plume and pyrocumulus microphysical structure and lightning production.

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.

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