scholarly journals Investigation of Near-Storm Environments for Tornado Events and Warnings

2016 ◽  
Vol 31 (6) ◽  
pp. 1771-1790 ◽  
Author(s):  
Alexandra K. Anderson-Frey ◽  
Yvette P. Richardson ◽  
Andrew R. Dean ◽  
Richard L. Thompson ◽  
Bryan T. Smith
Keyword(s):  
False Alarm ◽  
Parameter Space ◽  
Mixed Layer ◽  
Transition Period ◽  
Convective Available Potential Energy ◽  
Probability Of Detection ◽  
Convective Systems ◽  
Severe Convection ◽  
Tornado Event ◽  
Lifting Condensation Level

Abstract In this study, a 13-yr climatology of tornado event and warning environments, including metrics of tornado intensity and storm morphology, is investigated with particular focus on the environments of tornadoes associated with quasi-linear convective systems and right-moving supercells. The regions of the environmental parameter space having poor warning performance in various geographical locations, as well as during different times of the day and year, are highlighted. Kernel density estimations of the tornado report and warning environments are produced for two parameter spaces: mixed-layer convective available potential energy (MLCAPE) versus 0–6-km vector shear magnitude (SHR6), and mixed-layer lifting condensation level (MLLCL) versus 0–1-km storm-relative helicity (SRH1). The warning performance is best in environments characteristic of severe convection (i.e., environments featuring large values of MLCAPE and SHR6). For tornadoes occurring during the early evening transition period, MLCAPE is maximized, MLLCL heights decrease, SHR6 and SRH1 increase, tornadoes rated as 2 or greater on the enhanced Fujita scale (EF2+) are most common, the probability of detection is relatively high, and false alarm ratios are relatively low. Overall, the parameter-space distributions of warnings and events are similar; at least in a broad sense, there is no systematic problem with forecasting that explains the high overall false alarm ratio, which instead seems to stem from the inability to know which storms in a given environment will be tornadic.

scholarly journals Radar Climatology of Tornadic and Nontornadic Vortices in High-Shear, Low-CAPE Environments in the Mid-Atlantic and Southeastern United States

2014 ◽  
Vol 29 (4) ◽  
pp. 828-853 ◽  
Author(s):  
Jason M. Davis ◽  
Matthew D. Parker
Keyword(s):  
United States ◽  
False Alarm ◽  
High Probability ◽  
Southeastern United States ◽  
Vertical Wind Shear ◽  
Probability Of Detection ◽  
Radar Reflectivity ◽  
High Shear ◽  
Convective Systems ◽  
Azimuthal Shear

Abstract Tornadoes occurring in environments characterized by strong vertical wind shear [0–6-km bulk wind difference ≥35 knots (kt; 1 kt = 0.51 m s−1) (18 m s−1)] but low CAPE (<500 J kg−1) are an important challenge for forecasters, especially in the mid-Atlantic and southeastern United States. In this study, 95 tornadic and 135 nontornadic vortices were tracked in high-shear, low-CAPE (HSLC) environments. Values of azimuthal shear were recorded along the vortex tracks, and operationally relevant radar reflectivity signatures were also manually identified in association with these vortices. Statistically significant differences in azimuthal shear were found between tornadic and nontornadic vortices within 60 km of the radar, particularly near the surface. Although there were significant differences between tornadic and nontornadic vortices from nonsupercells (primarily quasi-linear convective systems), this was not the case for supercellular vortices. Beyond 60 km from the radar, no statistically significant differences were found. Numerous reflectivity signatures were also studied, including hook echoes and weak-echo regions associated with supercell vortices, as well as rear-inflow notches, bowing segments, and forward-inflow notches associated with nonsupercell vortices. These signatures were found to have a high probability of detection close to the radar, but also a high false alarm rate, and were observed much less often >100 km from the radar. Overall, while azimuthal shear and radar reflectivity signatures show the potential for high probability of detection in close proximity to operational radars, high false alarm rates, and short lead times appear to be an unavoidable trade-off in HSLC environments.

scholarly journals Tornado Probability of Detection and Lead Time as a Function of Convective Mode and Environmental Parameters

2013 ◽  
Vol 28 (5) ◽  
pp. 1261-1276 ◽  
Author(s):  
Jerald A. Brotzge ◽  
Steven E. Nelson ◽  
Richard L. Thompson ◽  
Bryan T. Smith
Keyword(s):  
Lead Time ◽  
Wind Shear ◽  
Convective Available Potential Energy ◽  
Vertical Wind Shear ◽  
Environmental Parameters ◽  
Probability Of Detection ◽  
Lead Times ◽  
Convective Systems ◽  
Tornado Warnings ◽  
Supercell Storms

Abstract The ability to provide advanced warning on tornadoes can be impacted by variations in storm mode. This research evaluates 2 yr of National Weather Service (NWS) tornado warnings, verification reports, and radar-derived convective modes to appraise the ability of the NWS to warn across a variety of convective modes and environmental conditions. Several specific hypotheses are considered: (i) supercell morphologies are the easiest convective modes to warn for tornadoes and yield the greatest lead times, while tornadoes from more linear, nonsupercell convective modes, such as quasi-linear convective systems, are more difficult to warn for; (ii) parameters such as tornado distance from radar, population density, and tornado intensity (F scale) introduce significant and complex variability into warning statistics as a function of storm mode; and (iii) tornadoes from stronger storms, as measured by their mesocyclone strength (when present), convective available potential energy (CAPE), vertical wind shear, and significant tornado parameter (STP) are easier to warn for than tornadoes from weaker systems. Results confirmed these hypotheses. Supercell morphologies caused 97% of tornado fatalities, 96% of injuries, and 92% of damage during the study period. Tornado warnings for supercells had a statistically higher probability of detection (POD) and lead time than tornado warnings for nonsupercells; among supercell storms, tornadoes from supercells in lines were slightly more difficult to warn for than tornadoes from discrete or clusters of supercells. F-scale intensity and distance from radar had some impact on POD, with less impact on lead times. Higher mesocyclone strength (when applicable), CAPE, wind shear, and STP values were associated with greater tornado POD and lead times.

NAM Model Forecasts of Warm-Season Quasi-Stationary Frontal Environments in the Central United States

2010 ◽  
Vol 25 (4) ◽  
pp. 1281-1292 ◽  
Author(s):  
Shih-Yu Wang ◽  
Adam J. Clark
Keyword(s):  
United States ◽  
Mesoscale Model ◽  
Convective Available Potential Energy ◽  
Warm Season ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Wind Fields ◽  
Vapor Flux ◽  
Convective Systems ◽  
Central United States

Abstract Using a composite procedure, North American Mesoscale Model (NAM) forecast and observed environments associated with zonally oriented, quasi-stationary surface fronts for 64 cases during July–August 2006–08 were examined for a large region encompassing the central United States. NAM adequately simulated the general synoptic features associated with the frontal environments (e.g., patterns in the low-level wind fields) as well as the positions of the fronts. However, kinematic fields important to frontogenesis such as horizontal deformation and convergence were overpredicted. Surface-based convective available potential energy (CAPE) and precipitable water were also overpredicted, which was likely related to the overprediction of the kinematic fields through convergence of water vapor flux. In addition, a spurious coherence between forecast deformation and precipitation was found using spatial correlation coefficients. Composite precipitation forecasts featured a broad area of rainfall stretched parallel to the composite front, whereas the composite observed precipitation covered a smaller area and had a WNW–ESE orientation relative to the front, consistent with mesoscale convective systems (MCSs) propagating at a slight right angle relative to the thermal gradient. Thus, deficiencies in the NAM precipitation forecasts may at least partially result from the inability to depict MCSs properly. It was observed that errors in the precipitation forecasts appeared to lag those of the kinematic fields, and so it seems likely that deficiencies in the precipitation forecasts are related to the overprediction of the kinematic fields such as deformation. However, no attempts were made to establish whether the overpredicted kinematic fields actually contributed to the errors in the precipitation forecasts or whether the overpredicted kinematic fields were simply an artifact of the precipitation errors. Regardless of the relationship between such errors, recognition of typical warm-season environments associated with these errors should be useful to operational forecasters.

scholarly journals Long-Term Performance Metrics for National Weather Service Tornado Warnings

2018 ◽  
Vol 33 (6) ◽  
pp. 1501-1511 ◽  
Author(s):  
Harold E. Brooks ◽  
James Correia
Keyword(s):  
False Alarm ◽  
Lead Time ◽  
Performance Metrics ◽  
Warning System ◽  
Probability Of Detection ◽  
False Alarms ◽  
National Weather Service ◽  
False Alarm Ratio ◽  
Tornado Warnings ◽  
Weather Service

Abstract Tornado warnings are one of the flagship products of the National Weather Service. We update the time series of various metrics of performance in order to provide baselines over the 1986–2016 period for lead time, probability of detection, false alarm ratio, and warning duration. We have used metrics (mean lead time for tornadoes warned in advance, fraction of tornadoes warned in advance) that work in a consistent way across the official changes in policy for warning issuance, as well as across points in time when unofficial changes took place. The mean lead time for tornadoes warned in advance was relatively constant from 1986 to 2011, while the fraction of tornadoes warned in advance increased through about 2006, and the false alarm ratio slowly decreased. The largest changes in performance take place in 2012 when the default warning duration decreased, and there is an apparent increased emphasis on reducing false alarms. As a result, the lead time, probability of detection, and false alarm ratio all decrease in 2012. Our analysis is based, in large part, on signal detection theory, which separates the quality of the warning system from the threshold for issuing warnings. Threshold changes lead to trade-offs between false alarms and missed detections. Such changes provide further evidence for changes in what the warning system as a whole considers important, as well as highlighting the limitations of measuring performance by looking at metrics independently.

scholarly journals An approach of constant false alarm ratio for improved target tracking

2020 ◽  
Vol 70 (3) ◽  
pp. 17-23
Author(s):  
Zvonko Radosavljević ◽  
Dejan Ivković
Keyword(s):  
False Alarm ◽  
Tracking Error ◽  
Probability Of Detection ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Moving Targets ◽  
False Alarm Ratio ◽  
Motion Models ◽  
Areas Of Interest

Each radar has the function of surveillance of certain areas of interest. In particular, the radar also has the function of tracking moving targets in that territory with some probability of detection, which depends on the type of detector. Constant false alarm ratio (CFAR) is a very commonly used detector. Changing the probability of target detection can directly affect the quality of tracking the moving targets. The paper presents the theoretical basis of the influence of CFAR detectors on the quality of tracking, as well as an approach to the selection of CFAR detectors, CATM CFAR, which enables better monitoring by the Interacting Multiple Model (IMM) algorithm with two motion models. Comparative analysis of CA and CATM algorithm realized by numerical simulations has shown that CATM CFAR gives less tracking error with proportionally the same computer resources.

scholarly journals A Method for Identifying Midlatitude Mesoscale Convective Systems in Radar Mosaics. Part I: Segmentation and Classification

2018 ◽  
Vol 57 (7) ◽  
pp. 1575-1598 ◽  
Author(s):  
Alex M. Haberlie ◽  
Walker S. Ashley
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Probability Of Detection ◽  
Machine Learning Algorithms ◽  
Mesoscale Convective Systems ◽  
Gradient Boosting ◽  
Moist Convection ◽  
Probabilistic Prediction ◽  
Convective Systems ◽  
Mesoscale Convective

AbstractThis research evaluates the ability of image-processing and select machine-learning algorithms to identify midlatitude mesoscale convective systems (MCSs) in radar-reflectivity images for the conterminous United States. The process used in this study is composed of two parts: segmentation and classification. Segmentation is performed by identifying contiguous or semicontiguous regions of deep, moist convection that are organized on a horizontal scale of at least 100 km. The second part, classification, is performed by first compiling a database of thousands of precipitation clusters and then subjectively assigning each sample one of the following labels: 1) midlatitude MCS, 2) unorganized convective cluster, 3) tropical system, 4) synoptic system, or 5) ground clutter and/or noise. The attributes of each sample, along with their assigned label, are used to train three machine-learning algorithms: random forest, gradient boosting, and “XGBoost.” Results using a testing dataset suggest that the algorithms can distinguish between MCS and non-MCS samples with a high probability of detection and low probability of false detection. Further, the trained algorithm predictions are well calibrated, allowing reliable probabilistic classification. The utility of this two-step procedure is illustrated by generating spatial frequency maps of automatically identified precipitation clusters that are stratified by using various reflectivity and probabilistic prediction thresholds. These results suggest that machine learning can add value by limiting the amount of false-positive (non-MCS) samples that are not removed by segmentation alone.

Synthesis of an algorithm for increasing the detection range of signals from radio-electronic means by means of radio control based on the estimated-correlation-compensation processing of signals with an unknown shape and additive noise in the receiving channel

2021 ◽  
Author(s):  
А.А. Boldyrev ◽  
А.А. Buben’shikov ◽  
D.I. Boldyrev
Keyword(s):  
False Alarm ◽  
Rapid Development ◽  
Internal Noise ◽  
Probability Of Detection ◽  
Detection Range ◽  
Signal Noise ◽  
Radio Electronic ◽  
Wide Range ◽  
Technical Systems

In modern conditions of rapid development of telecommunication technologies radio engineering means of different function are used everywhere in all spheres of ability to live of the person. Thus organizational-technical systems of civil appointment and power departments use the wide nomenclature of radio-electronic means of various classes with a wide spectrum of parameters, kinds of radiations and operating modes. In turn, it causes formation of difficult electromagnetic conditions in administrative-industrial regions and their near environment. The primary goal of services of radio control in these conditions is control over correctness of use by organizational-technical systems of the allocated resource of a radiofrequency spectrum and the parameters radiating of radio-electronic means. One of the main difficulties with which means of radio control in the course of the analysis of electromagnetic conditions in the set territorial area face a considerable quantity of radiating radio-electronic means with various parameters in a wide range of the relation a signal/noise, and also presence of stirring influence of any hindrances is. These factors make rigid demands to indicators of quality of functioning of panoramic detectors-direction finders which make a basis of mobile and stationary means of radio control. One of the basic indicators of quality of panoramic detectors-direction finders of means of radio control is range of detection of the radio-electronic means, defined by the set level of sensitivity and demanded values of probabilities of detection and a false alarm. Authors in article result results of working out of algorithm of increase of range of detection of signals by means of radio control on the basis of an estimated-correlation-compensatory way of measurement and indemnification of average capacity of additive hindrances in the reception channel. By results of the researches spent in article it is shown that: the increase in average capacity of cumulative external inadvertent and deliberate hindrances for the set typical initial data leads in VHF a range to reduction of range of detection of radio-electronic means not less, than in 1,4 times from the demanded; at demanded value of probability of detection, for example, and probabilities of a false alarm, at relative level of external set of a hindrance the panoramic detectors-direction finder of means of radio control with the realised procedure of measurement and indemnification of average value of capacity (dispersion) of inadvertent, deliberate hindrances and internal noise allows to lower the requirement to the threshold relation a signal/(noise) (on pressure) more, than in 1,3 times that will allow to approach value of range of detection to a reference value.

scholarly journals Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

2020 ◽  
Vol 21 (1) ◽  
pp. 39-57 ◽  
Author(s):  
Wenjun Cui ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Zhe Feng ◽  
Jiwen Fan
Keyword(s):  
United States ◽  
False Alarm ◽  
Stage Iv ◽  
Cloud Base ◽  
Eastern United States ◽  
Convective Systems ◽  
Precipitation Measurement ◽  
Precipitation Characteristics ◽  
Mesoscale Convective ◽  
Global Precipitation

AbstractMesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.

Bow Echo Sensitivity to Ambient Moisture and Cold Pool Strength

2006 ◽  
Vol 134 (3) ◽  
pp. 950-964 ◽  
Author(s):  
Richard P. James ◽  
Paul M. Markowski ◽  
J. Michael Fritsch
Keyword(s):  
Convective Available Potential Energy ◽  
Three Dimensional ◽  
Cold Pool ◽  
Convective System ◽  
Cold Air ◽  
Convective Systems ◽  
Cold Pools ◽  
Bow Echo ◽  
Dry Conditions ◽  
Water Vapor Mixing Ratio

Abstract Bow echo development within quasi-linear convective systems is investigated using a storm-scale numerical model. A strong sensitivity to the ambient water vapor mixing ratio is demonstrated. Relatively dry conditions at low and midlevels favor intense cold-air production and strong cold pool development, leading to upshear-tilted, “slab-like” convection for various magnitudes of convective available potential energy (CAPE) and low-level shear. High relative humidity in the environment tends to reduce the rate of production of cold air, leading to weak cold pools and downshear-tilted convective systems, with primarily cell-scale three-dimensionality in the convective region. At intermediate moisture contents, long-lived, coherent bowing segments are generated within the convective line. In general, the scale of the coherent three-dimensional structures increases with increasing cold pool strength. The bowing lines are characterized in their developing and mature stages by segments of the convective line measuring 15–40 km in length over which the cold pool is much stronger than at other locations along the line. The growth of bow echo structures within a linear convective system appears to depend critically on the local strengthening of the cold pool to the extent that the convection becomes locally upshear tilted. A positive feedback process is thereby initiated, allowing the intensification of the bow echo. If the environment favors an excessively strong cold pool, however, the entire line becomes uniformly upshear tilted relatively quickly, and the along-line heterogeneity of the bowing line is lost.

Quasi-Stationary, Extreme-Rain-Producing Convective Systems Associated with Midlevel Cyclonic Circulations

2009 ◽  
Vol 24 (2) ◽  
pp. 555-574 ◽  
Author(s):  
Russ S. Schumacher ◽  
Richard H. Johnson
Keyword(s):  
Convective Available Potential Energy ◽  
Extreme Rainfall ◽  
Surface Boundary ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Weak Boundaries ◽  
Extreme Rain ◽  
Building Behavior ◽  
Slow Moving ◽  
Convective Vortices

Abstract This study identifies and examines the common characteristics of several nocturnal midlatitude mesoscale convective systems (MCSs) that developed near mesoscale convective vortices (MCVs) or cutoff lows. All of these MCSs were organized into convective clusters or lines that exhibited back-building behavior, remained nearly stationary for 6–12 h, and produced locally excessive rainfall (greater than 200 mm in 12 h) that led to substantial flash flooding. Examination of individual events and composite analysis reveals that the MCSs formed in thermodynamic environments characterized by very high relative humidity at low levels, moderate convective available potential energy (CAPE), and very little convective inhibition (CIN). In each case, the presence of a strong low-level jet (LLJ) and weak midlevel winds led to a pronounced reversal of the wind shear vector with height. Most of the MCSs formed without any front or preexisting surface boundary in the vicinity, though weak boundaries were apparent in two of the cases. Lifting and destabilization associated with the interaction between the LLJ and the midlevel circulation assisted in initiating and maintaining the slow-moving MCSs. Based on the cases analyzed in this study and past events described in the literature, a conceptual model of the important processes that lead to extreme rainfall near midlevel circulations is presented.

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