scholarly journals Polarimetric Radar Characteristics of Tornadogenesis Failure in Supercell Thunderstorms

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 581
Author(s):  
Matthew Van Den Broeke
Keyword(s):  
Polarimetric Radar ◽  
Low Level ◽  
Supercell Storms ◽  
Supercell Thunderstorms ◽  
Near Term ◽  
Tornadic Storms ◽  
Differential Reflectivity

Many nontornadic supercell storms have times when they appear to be moving toward tornadogenesis, including the development of a strong low-level vortex, but never end up producing a tornado. These tornadogenesis failure (TGF) episodes can be a substantial challenge to operational meteorologists. In this study, a sample of 32 pre-tornadic and 36 pre-TGF supercells is examined in the 30 min pre-tornadogenesis or pre-TGF period to explore the feasibility of using polarimetric radar metrics to highlight storms with larger tornadogenesis potential in the near-term. Overall the results indicate few strong distinguishers of pre-tornadic storms. Differential reflectivity (ZDR) arc size and intensity were the most promising metrics examined, with ZDR arc size potentially exhibiting large enough differences between the two storm subsets to be operationally useful. Change in the radar metrics leading up to tornadogenesis or TGF did not exhibit large differences, though most findings were consistent with hypotheses based on prior findings in the literature.

An Automated Python Algorithm to Quantify ZDR Arc and KDP-ZDR Separation Signatures in Supercells

2020 ◽  
Author(s):  
Matthew B. Wilson ◽  
Matthew S. Van Den Broeke
Keyword(s):  
Time Series ◽  
Recent Work ◽  
Radar Data ◽  
Dual Polarization ◽  
Low Level ◽  
Supercell Storms ◽  
Size Sorting ◽  
Supercell Thunderstorms ◽  
Differential Reflectivity

AbstractSupercell thunderstorms often have pronounced signatures of hydrometeor size sorting within their forward flank regions, including an arc-shaped region of high differential reflectivity (ZDR) along the inflow edge of the forward flank known as the ZDR arc and a clear horizontal separation between this area of high ZDP values and and an area of enhanced KDP values deeper into the storm core. Recent work has indicated that ZDR arc and KDP-ZDR separation signatures in supercell storms may be related to environmental storm-relative helicity and low-level shear. Thus, characteristics of these signatures may be helpful to indicate whether a given storm is likely to produce a tornado. Although ZDR arc and KDP-ZDR separation signatures are typically easy to qualitatively identify in dual-polarization radar fields, quantifying their characteristics can be time-consuming and makes research into these signatures and their potential operational applications challenging. To address this problem, this paper introduces an automated Python algorithm to objectively identify and track these signatures in Weather Surveillance Radar-1988 Doppler (WSR-88D) radar data and quantify their characteristics. This paper will discuss the development of the algorithm, demonstrate its performance through comparisons with manually-generated time series of ZDR arc and KDP-ZDR separation signature characteristics, and briefly explore potential uses of this algorithm in research and operations.

A Preliminary Polarimetric Radar Comparison of Pretornadic and Nontornadic Supercell Storms

2020 ◽  
Vol 148 (4) ◽  
pp. 1567-1584 ◽  
Author(s):  
Matthew S. Van Den Broeke
Keyword(s):  
Drop Size ◽  
Polarimetric Radar ◽  
Supercell Storms ◽  
Supercell Thunderstorms ◽  
Differential Reflectivity

Abstract Supercell thunderstorms produce a variety of hazards, including tornadoes. A supercell will often exist for some time prior to producing a tornado, while other supercells never become tornadic. In this study, a series of hypotheses is tested regarding the ability of S-band polarimetric radar fields to distinguish pretornadic from nontornadic supercell storms. Several quantified polarimetric radar metrics are examined that are related to storm inflow, updraft, and hailfall characteristics in samples of 19–30 pretornadic and 18–31 nontornadic supercells. The results indicate that pretornadic supercells are characterized by smaller hail extent and echo appendages with larger mean drop size. Additionally, differential reflectivity ZDR column size is larger and less variable in the pretornadic storms in the 25–30 min prior to initial tornadogenesis. Many of the results indicate relatively small polarimetric differences that will likely be difficult to translate to operational use. Hail extent and ZDR column size, however, may exhibit operationally useful differences between pretornadic and nontornadic supercells.

scholarly journals Polarimetric Signatures in Supercell Thunderstorms

2008 ◽  
Vol 47 (7) ◽  
pp. 1940-1961 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Alexander V. Ryzhkov
Keyword(s):  
Polarimetric Radar ◽  
Geographic Locations ◽  
Convective Storms ◽  
Supercell Storms ◽  
Different Seasons ◽  
Supercell Thunderstorms ◽  
Very High ◽  
Insight Into

Abstract Data from polarimetric radars offer remarkable insight into the microphysics of convective storms. Numerous tornadic and nontornadic supercell thunderstorms have been observed by the research polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN); additional storm data come from the Enterprise Electronics Corporation “Sidpol” C-band polarimetric radar in Enterprise, Alabama, as well as the King City C-band polarimetric radar in Ontario, Canada. A number of distinctive polarimetric signatures are repeatedly found in each of these storms. The forward-flank downdraft (FFD) is characterized by a signature of hail observed as near-zero ZDR and high ZHH. In addition, a shallow region of very high ZDR is found consistently on the southern edge of the FFD, called the ZDR “arc.” The ZDR and KDP columns and midlevel “rings” of enhanced ZDR and depressed ρHV are usually observed in the vicinity of the main rotating updraft and in the rear-flank downdraft (RFD). Tornado touchdown is associated with a well-pronounced polarimetric debris signature. Similar polarimetric features in supercell thunderstorms have been reported in other studies. The data considered here are taken from both S- and C-band radars from different geographic locations and during different seasons. The consistent presence of these features may be indicative of fundamental processes intrinsic to supercell storms. Hypotheses on the origins, as well as microphysical and dynamical interpretations of these signatures, are presented. Implications about storm morphology for operational applications are suggested.

scholarly journals Polarimetric Radar Metrics Related to Tornado Life Cycles and Intensity in Supercell Storms

2017 ◽  
Vol 145 (9) ◽  
pp. 3671-3686 ◽  
Author(s):  
Matthew S. Van Den Broeke
Keyword(s):  
Time Series ◽  
Life Cycle ◽  
Environmental Variability ◽  
Mean Value ◽  
Life Cycles ◽  
Polarimetric Radar ◽  
New Methods ◽  
Storm Evolution ◽  
Supercell Storms ◽  
Differential Reflectivity

Polarimetric radar signatures have been related to the typical evolution of supercell storms, including through tornado life cycles. Now that polarimetric radar observations are available for a large sample of supercell storms, time series of new radar metrics can be derived. These metrics can be compared with phases of known tornado life cycles in an effort to develop new methods of anticipating tornadoes and to increase understanding of storm-scale structural and microphysical changes through supercell and tornado life cycles. In this paper, radar metrics including measures of differential reflectivity ZDR columns, ZDR arcs, polarimetrically inferred hailfall regions, and mean value of copolar correlation coefficient ρhv in the echo appendage are compared to the tornado life cycle and to storm-maximum tornado intensity in a sample of 35 tornadic supercells. It is shown that these radar metrics may change repeatedly and thus can be used to distinguish tornadic and nontornadic periods in single supercell storms, tornadogenesis from tornado demise times, and modes of storm evolution relative to tornadoes (e.g., if a storm produces one tornado or several). The polarimetric radar metrics are nearly as predictive of tornado intensity as commonly used measures of environmental variability for this sample.

scholarly journals Lightning in the Anvils of Supercell Thunderstorms

2012 ◽  
Vol 140 (7) ◽  
pp. 2064-2079 ◽  
Author(s):  
Stephanie A. Weiss ◽  
Donald R. MacGorman ◽  
Kristin M. Calhoun
Keyword(s):  
Warm Season ◽  
Opposite Polarity ◽  
Layer Charge ◽  
Supercell Storm ◽  
Lightning Detection ◽  
Supercell Storms ◽  
Mapping Array ◽  
Storm Dynamics ◽  
Supercell Thunderstorms

Abstract This study uses data from the Oklahoma Lightning Mapping Array (OK-LMA), the National Lightning Detection Network, and the Norman, Oklahoma (KOUN), prototype Weather Surveillance Radar-1988 Doppler (WSR-88D) radar to examine the evolution and structure of lightning in the anvils of supercell storms as they relate to storm dynamics and microphysics. Several supercell storms within the domain of the OK-LMA were examined to determine whether they had lightning in the anvil region, and if so, the time and location of the initiation of the anvil flashes were determined. Every warm-season supercell storm had some flashes that were initiated in or near the stronger reflectivities of the parent storm and propagated 40–70 km downstream to penetrate well into the anvil. Some supercell storms also had flashes that were initiated within the anvil itself, 40–100 km beyond the closest 30-dBZ contour of the storm. These flashes were typically initiated in one of three locations: 1) coincident with a local reflectivity maximum, 2) between the uppermost storm charge and a screening-layer charge of opposite polarity near the cloud boundary, or 3) in a region in which the anvils from two adjoining storms intersected. In some storms, anvil flashes struck ground beneath a reflectivity maximum in which reflectivity ≥20 dBZ had extended below the 0°C isotherm, possibly leading to the formation of embedded convection. This relationship may be useful for identifying regions in which there is a heightened risk for cloud-to-ground strikes beneath anvil clouds. In one storm, however, anvil lightning struck ground even though this reflectivity signature was absent.

Microphysical and Polarimetric Radar Modeling of Hydrometeor Refreezing

2021 ◽  
Author(s):  
Dana M. Tobin ◽  
Matthew R. Kumjian
Keyword(s):  
Polarimetric Radar ◽  
Horizontal Polarization ◽  
Radar Signature ◽  
Liquid Portion ◽  
Linear Depolarization Ratio ◽  
Bin Microphysics ◽  
Ice Shell ◽  
Differential Reflectivity ◽  
The Impact ◽  
Polar Correlation

AbstractA unique polarimetric radar signature indicative of hydrometeor refreezing during ice pellet events has been documented in several recent studies, yet the underlying microphysical causes remain unknown. The signature is characterized by enhancements in differential reflectivity (ZDR), specific differential phase (KDP), and linear depolarization ratio (LDR), and a reduction in co-polar correlation coefficient (ρhv) within a layer of decreasing radar reflectivity factor at horizontal polarization (ZH). In previous studies, the leading hypothesis for the observed radar signature is the preferential refreezing of small drops. Here, a simplified, one-dimensional, explicit bin microphysics model is developed to simulate the refreezing of fully melted hydrometeors, and coupled with a polarimetric radar forward operator to quantify the impact of preferential refreezing on simulated radar signatures. The modeling results demonstrate that preferential refreezing is insufficient by itself to produce the observed signatures. In contrast, simulations considering an ice shell growing asymmetrically around a freezing particle (i.e., emulating a thicker ice shell on the bottom of a falling particle) produce realistic ZDR enhancements, and also closely replicate observed features in ZH, KDP, LDR, and ρhv. Simulations that assume no increase in particle wobbling with freezing produce an even greater ZDR enhancement, but this comes at the expense of reducing the LDR enhancement. It is suggested that the polarimetric refreezing signature is instead strongly related to both the distribution of the unfrozen liquid portion within a freezing particle, and the orientation of this liquid with respect to the horizontal.

scholarly journals A Background Investigation of Tornado Activity across the Southern Cumberland Plateau Terrain System of Northeastern Alabama

2018 ◽  
Vol 146 (12) ◽  
pp. 4261-4278 ◽  
Author(s):  
Anthony W. Lyza ◽  
Kevin R. Knupp
Keyword(s):  
Wind Profile ◽  
Cumberland Plateau ◽  
Activity Maximum ◽  
Low Level ◽  
Terrain Effects ◽  
Surface Data ◽  
Tennessee Valley ◽  
Profile Changes ◽  
Tornadic Storms

Abstract The effects of terrain on tornadoes are poorly understood. Efforts to understand terrain effects on tornadoes have been limited in scope, typically examining a small number of cases with limited observations or idealized numerical simulations. This study evaluates an apparent tornado activity maximum across the Sand Mountain and Lookout Mountain plateaus of northeastern Alabama. These plateaus, separated by the narrow Wills Valley, span ~5000 km2 and were impacted by 79 tornadoes from 1992 to 2016. This area represents a relative regional statistical maximum in tornadogenesis, with a particular tendency for tornadogenesis on the northwestern side of Sand Mountain. This exploratory paper investigates storm behavior and possible physical explanations for this density of tornadogenesis events and tornadoes. Long-term surface observation datasets indicate that surface winds tend to be stronger and more backed atop Sand Mountain than over the adjacent Tennessee Valley, potentially indicative of changes in the low-level wind profile supportive to storm rotation. The surface data additionally indicate potentially lower lifting condensation levels over the plateaus versus the adjacent valleys, an attribute previously shown to be favorable for tornadogenesis. Rapid Update Cycle and Rapid Refresh model output indicate that Froude numbers for the plateaus in tornadic environments are likely supportive of enhanced low-level flow over the plateaus, which further indicates the potential for favorable wind profile changes for tornado production. Examples of tornadic storms rapidly acquiring increased low-level rotation while reaching the plateaus of northeast Alabama are presented. The use of this background to inform the VORTEX-SE 2017 field campaign is discussed.

scholarly journals Analysis of Dual-Polarimetric Radar Variables and Quantitative Precipitation Estimators for Landfall Typhoons and Squall Lines Based on Disdrometer Data in Southern China

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 30 ◽  
Author(s):  
Yonghua Zhang ◽  
Liping Liu ◽  
Shuoben Bi ◽  
Zhifang Wu ◽  
Ping Shen ◽  
...  
Keyword(s):  
Drop Size ◽  
Southern China ◽  
Average Diameter ◽  
Squall Line ◽  
Polarimetric Radar ◽  
Quantitative Precipitation Estimation ◽  
Squall Lines ◽  
Fitting Method ◽  
Precipitation Estimation ◽  
Differential Reflectivity

Typhoon rainstorms often cause disasters in southern China. Quantitative precipitation estimation (QPE) with the use of polarimetric radar can improve the accuracy of precipitation estimation and enhance typhoon defense ability. On the basis of the observed drop size distribution (DSD) of raindrops, a comparison is conducted among the DSD parameters and the polarimetric radar observation retrieved from DSD in five typhoon and three squall line events that occurred in southern China from 2016 to 2017. A new piecewise fitting method (PFM) is used to develop the QPE estimators for landfall typhoons and squall lines. The performance of QPE is evaluated by two fitting methods for two precipitation types using DSD data collected. Findings indicate that the number concentration of raindrops in typhoon precipitation is large and the average diameter is small, while the raindrops in squall line rain have opposite characteristics. The differential reflectivity (ZDR) and specific differential phase (KDP) in these two precipitation types increase slowly with the reflectivity factor (ZH), whereas the two precipitation types have different ZDR and KDP in the same ZH. Thus, it is critical to fit the rainfall estimator for different precipitation types. Enhanced estimation can be obtained using the estimators for specific precipitation types, whether the estimators are derived from the conventional fitting method (CFM) or PFM, and the estimators fitted using the PFM can produce better results. The estimators for the developed polarimetric radar can be used in operational QPE and quantitative precipitation foresting, and they can improve disaster defense against typhoons and heavy rains.

scholarly journals Validation of a Multilag Estimator on NJU-CPOL and a Hybrid Approach for Improving Polarimetric Radar Data Quality

2020 ◽  
Vol 12 (1) ◽  
pp. 180
Author(s):  
Shiqing Shao ◽  
Kun Zhao ◽  
Haonan Chen ◽  
Jianjun Chen ◽  
Hao Huang
Keyword(s):  
Theoretical Analysis ◽  
Correlation Coefficient ◽  
Hybrid Method ◽  
Radar Data ◽  
Noise Power ◽  
Signal Power ◽  
Polarimetric Radar ◽  
Moment Estimation ◽  
Spectrum Width ◽  
Differential Reflectivity

For the estimation of weak echo with low signal-to-noise ratio (SNR), a multilag estimator is developed, which has better performance than the conventional method. The performance of the multilag estimator is examined by theoretical analysis, simulated radar data and some specific observed data collected by a C-band polarimetric radar in previous research. In this paper, the multilag estimator is implemented and verified for Nanjing University C-band polarimetric Doppler weather radar (NJU-CPOL) during the Observation, Prediction and Analysis of Severe Convection of China (OPACC) field campaign in 2014. The implementation results are also compared with theoretical analysis, including the estimation of signal power, spectrum width, differential reflectivity, and copolar correlation coefficient. The results show that the improvement of the multilag estimator is little for signal power and differential reflectivity, but significant for spectrum width and copolar correlation coefficient when spectrum width is less than 2 ms−1, which implies a large correlation time scale. However, there are obvious biases from the multilag estimator in the regions with large spectrum width. Based on the performance analysis, a hybrid method is thus introduced and examined through NJU-CPOL observations. All lags including lag 0 of autocorrelation function (ACF) are used for moment estimation in this algorithm according to the maximum usable lag number. A case study shows that this hybrid method can improve moment estimation compared to both conventional estimator and multilag estimator, especially for weak weather echoes. The improvement will be significant if SNR decreases or the biases of noise power in the conventional estimator increase. In addition, this hybrid method is easy to implement on both operational and non-operational radars. It is also expected that the proposed hybrid method will have a better performance if applied to S-band polarimetric radars which have twice the maximum useable lags in the same conditions with C-band radars.

scholarly journals Sensitivities of Quantitative Precipitation Forecasts for Typhoon Soudelor (2015) near Landfall to Polarimetric Radar Data Assimilation

2020 ◽  
Vol 12 (22) ◽  
pp. 3711
Author(s):  
Chih-Chien Tsai ◽  
Kao-Shen Chung
Keyword(s):  
Data Assimilation ◽  
Radar Data ◽  
Convective Precipitation ◽  
Polarimetric Radar ◽  
Differential Phase ◽  
Observation Operator ◽  
Quantitative Precipitation Forecasts ◽  
Series Of Experiments ◽  
Differential Reflectivity ◽  
Radar Data Assimilation

Based on the preciousness and uniqueness of polarimetric radar observations collected near the landfall of Typhoon Soudelor (2015), this study investigates the sensitivities of very short-range quantitative precipitation forecasts (QPFs) for this typhoon to polarimetric radar data assimilation. A series of experiments assimilating various combinations of radar variables are carried out for the purpose of improving a 6 h deterministic forecast for the most intense period. The results of the control simulation expose three sources of the observation operator errors, including the raindrop shape-size relation, the limitations for ice-phase hydrometeors, and the melting ice model. Nevertheless, polarimetric radar data assimilation with the unadjusted observation operator can still improve the analyses, especially rainwater, and consequent QPFs for this typhoon case. The different impacts of assimilating reflectivity, differential reflectivity, and specific differential phase are only distinguishable at the lower levels of convective precipitation areas where specific differential phase is found most helpful. The positive effect of radar data assimilation on QPFs can last three hours in this study, and further improvement can be expected by optimizing the observation operator in the future

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