scholarly journals Severe storms as an example of a natural hazard in the urban area – case studies of the area of Warsaw, Poland

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Krzysztof Piasecki ◽  
Elwira Żmudzka
Keyword(s):  
Radar Data ◽  
Fire Service ◽  
Spatial Variations ◽  
Storm Events ◽  
Severe Thunderstorms ◽  
Significant Damage ◽  
Strong Shear ◽  
Supercell Storms ◽  
Thermodynamic Conditions ◽  
Materials Used

Abstract The main objective of this research was to determine the synoptic and thermodynamic conditions accompanying the development of two severe thunderstorms that caused significant damage in Warsaw. The storm events of 17 June and 4 September 2016 were analysed. Materials used in the research included meteorological, aerological and radar data, as well as the Fire Service interventions database. These data allowed the conditions for the formation of the storms and their spatial variations in terms of intensity to be determined. It was shown that damage in Warsaw was caused by phenomena associated with supercell storms that developed in a moderate CAPE environment and a strong shear. It was confirmed that the geometry of the city increased the wind speed and modified its direction locally. In addition, it was found that the data on the number of Fire Service interventions clearly reflected the spatial variations in storm intensity by corresponding radar signatures to the high intensity of meteorological phenomena.

scholarly journals Analysis of Severe Elevated Thunderstorms over Frontal Surfaces Using DCIN and DCAPE

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 449
Author(s):  
Patrick Market ◽  
Kevin Grempler ◽  
Paula Sumrall ◽  
Chasity Henson
Keyword(s):  
Weather Prediction ◽  
Convective Available Potential Energy ◽  
Numerical Weather Prediction Model ◽  
Surface Boundary ◽  
Storm Events ◽  
Cold Side ◽  
Severe Thunderstorms ◽  
Stable Surface Layer ◽  
Different Populations ◽  
Convective Inhibition

A 10-year study of elevated severe thunderstorms was performed using The National Centers for Environmental Information Storm Events Database. A total of 80 elevated thunderstorm cases were identified, verified, and divided into “Prolific” and “Marginal” classes. These severe cases occurred at least 80 km away from, and on the cold side of, a surface boundary. The downdraft convective available potential energy (DCAPE), downdraft convective inhibition (DCIN), and their ratio are tools to help estimate the potential for a downdraft to penetrate through the depth of a stable surface layer. The hypothesis is that as the DCIN/DCAPE ratio decreases, there exists enhanced possibility of severe surface winds. Using the initial fields from the Rapid Refresh numerical weather prediction model, datasets of DCIN, DCAPE, and their ratio were created. Mann-Whitney U tests on the Prolific versus Marginal case sets were undertaken to determine if the DCAPE and DCIN values come from different populations for the two different case sets. Results show that the Prolific cases have values of DCIN closer to zero, suggesting the downdraft is able to penetrate to the surface causing severe winds. Thus, comparing DCIN and DCAPE is a viable tool in determining if downdrafts will reach the surface from elevated thunderstorms.

Assessing the future occurrence of severe thunderstorm environments in Europe: frequency, hotspots and impacts

2021 ◽  
Author(s):  
Flavio Pons ◽  
Davide Faranda
Keyword(s):  
Radiative Forcing ◽  
Value Theory ◽  
Severe Weather ◽  
Cmip5 Models ◽  
Dynamical System Theory ◽  
Economic Damage ◽  
Climate Change Scenarios ◽  
Severe Thunderstorms ◽  
Significant Damage ◽  
The Future

<p>We study the future frequency of atmospheric environments leading to severe thunderstorms over Europe under different climate change scenarios in CMIP5 models. Our method is founded on dynamical system theory, which makes it possible to detect future atmospheric configurations that are close analogues of past events in the class of interest.</p><p>We rely on the EM-DAT and the European Severe Weather Database to select an ensemble of past events leading to significant damage or disruption, including severe thunderstorms, hail storms, derechos and tornadoes, between 1950 and 2020. We consider the geopotential height field at 500 hPa in ERA5 data as a dynamical proxy of the corresponding configurations. Then, we leverage extreme value theory to detect close dynamic analogues in the output of CMIP5 climate projection models under two emission scenarios, namely RCP4.5 and RCP8.5.</p><p>First of all, we assess possible differences between the trends in severe weather frequency due to different radiative forcing. Then, we study the spatial structure of such trends, highlighting regions where the occurrence of such phenomena could see a sharp increase or decrease. Finally, we estimate potential future impact of such phenomena where the information about economic damage is available in EM-DAT.</p><p> </p>

scholarly journals Wintertime Supercell Thunderstorms in a Subtropical Environment: A Diagnostic Study

2009 ◽  
Vol 137 (1) ◽  
pp. 366-390 ◽  
Author(s):  
Chung-Chieh Wang ◽  
George Tai-Jen Chen ◽  
Shan-Chien Yang ◽  
Hung-Chi Chou
Keyword(s):  
Vertical Wind Shear ◽  
Radar Data ◽  
Diagnostic Study ◽  
Local Circulation ◽  
Cold Air ◽  
First Case ◽  
Supercell Storms ◽  
Deep Layers ◽  
Upper Level Jet ◽  
Subtropical Environment

Abstract The present study documents the environment, initiation, and evolution of three isolated supercell storms on 19 December 2002, as the first case near Taiwan reported in the literature, mainly using radar data and manual and gridded analyses. In a subtropical environment, the supercells occurred behind a winter cold front that provided a large west-southwesterly vertical wind shear of 6.4 × 10−3 s−1 at 0–3 km. This combined with weak-to-moderate instability (CAPE = 887 J kg−1) above the shallow surface cold air to yield a favorable environment for supercells. An approaching upper-level jet (ULJ) at 200 hPa also provided strong shear through deep layers farther aloft. Prior to storm initiation, significant daytime solar heating occurred over the mountain slopes along the coast of southeastern China, leading to development of local circulation and onshore/upslope winds, resulting in convergence and uplifting. Three storms were initiated about 80 km inland around 1400 LST near the peaks of local terrain with a northeast–southwest alignment. After formation, the three storms evolved into isolated supercells and each experienced multiple splits. The right-moving storms were usually stronger than left-moving ones and traveled eastward rapidly at about 18 m s−1 across the Taiwan Strait. The storms reached their maximum strength over the strait where low-level shear intensified during the day due to cold air surge. The northern storm also registered a peak reflectivity of 72 dBZ, the strongest ever recorded by any radar in Taiwan. Eventually, the three supercell storms made landfall over Taiwan, producing swaths of rain, hail, and property damages. Before they diminished after midnight, each of the three storms had lasted for about 10 h and propagated for over 550 km.

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.

Mitigating the Impact of Azimuthal Sampling on the Strength of Radar-Observed Circulations

2020 ◽  
Vol 37 (6) ◽  
pp. 1103-1116
Author(s):  
Feng Nai ◽  
Sebastián Torres ◽  
Christopher Curtis
Keyword(s):  
Computational Complexity ◽  
Rotational Velocity ◽  
Real Data ◽  
Radar Data ◽  
Sampling Interval ◽  
Severe Thunderstorms ◽  
Key Factor ◽  
Data Points ◽  
Circulation Velocity ◽  
The Impact

AbstractSevere thunderstorms and their associated tornadoes pose significant threats to life and property, and using radar data to accurately measure the rotational velocity of circulations in thunderstorms is essential for appropriate, timely warnings. One key factor in accurately measuring circulation velocity is the azimuthal spacing between radar data points, which is referred to as the azimuthal sampling interval. Previous studies have shown that reducing the azimuthal sampling interval can aid in measuring circulation velocity; however, this comes at the price of increased computational complexity. Thus, choosing the best compromise requires knowledge of the relationship between the radar azimuthal sampling interval and the accuracy of the circulation strength as measured from the radar data. In this work, we use simulations to quantify the impact of azimuthal sampling on the strength of radar-observed circulations and show that the improvements get progressively smaller as the azimuthal sampling interval decreases. Thus, improved characterization of circulations can be achieved without using the finest possible sampling grid. We use real data to validate the results of the simulations, which can be used to inform the selection of an appropriate azimuthal sampling interval that balances the accuracy of the radar-observed circulations and computational complexity.

Comparison of Evaporation and Cold Pool Development between Single-Moment and Multimoment Bulk Microphysics Schemes in Idealized Simulations of Tornadic Thunderstorms

2010 ◽  
Vol 138 (4) ◽  
pp. 1152-1171 ◽  
Author(s):  
Daniel T. Dawson ◽  
Ming Xue ◽  
Jason A. Milbrandt ◽  
M. K. Yau
Keyword(s):  
Flank Region ◽  
Real Data ◽  
Cold Pool ◽  
Cold Bias ◽  
Data Simulation ◽  
Supercell Storms ◽  
Thermodynamic Conditions ◽  
Single Moment ◽  
Size Sorting ◽  
The Impact

Abstract Idealized simulations of the 3 May 1999 Oklahoma tornadic supercell storms are conducted at various horizontal grid spacings ranging from 1 km to 250 m, using a sounding extracted from a prior 3-km grid spacing real-data simulation. A sophisticated multimoment bulk microphysics parameterization scheme capable of predicting up to three moments of the particle or drop size distribution (DSD) for several liquid and ice hydrometeor species is evaluated and compared with traditional single-moment schemes. The emphasis is placed on the impact of microphysics, specifically rain evaporation and size sorting, on cold pool strength and structure, and on the overall reflectivity structure of the simulated storms. It is shown through microphysics budget analyses and examination of specific processes within the low-level downdraft regions that the multimoment scheme has important advantages, which lead to a weaker and smaller cold pool and better reflectivity structure, particularly in the forward-flank region of the simulated supercells. Specifically, the improved treatment of evaporation and size sorting, and their effects on the predicted rain DSDs by the multimoment scheme helps to control the cold bias often found in the simulations using typical single-moment schemes. The multimoment results are more consistent with observed (from both fixed and mobile mesonet platforms) thermodynamic conditions within the cold pools of the discrete supercells of the 3 May 1999 outbreak.

scholarly journals Preliminary reflectivity analysis of severe convective events in in the proximity of Goczałkowice-Zdrój, Poland

2019 ◽  
Vol 7 (2) ◽  
pp. 32-38
Author(s):  
Wojciech Pilorz ◽  
Philip Ciaramella
Keyword(s):  
Water Management ◽  
Lower Troposphere ◽  
Radar Data ◽  
Radar System ◽  
Severe Weather ◽  
Storm Events ◽  
Radar Systems ◽  
X Band ◽  
Scanning Area ◽  
Local Weather

Abstract At the beginning of 2018, the X-band radar in Goczałkowice-Zdrój (southern Poland) was launched. The scanning area corresponds with the scanning area of the POLRAD C-band radar system operated by the Polish Institute of Meteorology and Water Management. New opportunities were created for imaging phenomena by comparing some reflectivity features from C-Band radar and X-Band local weather radar. Moreover, some of the signatures located in the lower troposphere can be better documented by local X-Band radar. Firstly, reports from the ESWD (European Severe Weather Database) have been thoroughly analysed. All severe weather reports in the proximity of Goczałkowice-Zdrój (100-km radius) were gathered into one-storm events. Then the reflectivity from both radars was analysed to determine which reflectivity patterns occurred and when. X-band radars are known from the more intensive attenuation of the radar beam by the scatterers located closer to the radar, thus it is essential to compare capabilities of these two different radar systems. It was found that the average reflectivity for all convective incidents is higher when using POLRAD C-band radar data. In some events it was possible to find some spatial reflectivity signatures. We also discuss other reflectivity signatures previously described in the literature. Taking into account stronger Goczałkowice-Zdrój X-band radar attenuation, we suggest that some of these should be reviewed by reduction of the reflectivity thresholds.

scholarly journals Observations of the 14 July 2011 Fort Collins Hailstorm: Implications for WSR-88D-Based Hail Detection and Warnings

2014 ◽  
Vol 29 (3) ◽  
pp. 623-638 ◽  
Author(s):  
Patrick C. Kennedy ◽  
Steven A. Rutledge ◽  
Brenda Dolan ◽  
Eric Thaler
Keyword(s):  
Radar Data ◽  
Front Range ◽  
Dual Polarization ◽  
Remotely Sensed Data ◽  
Colorado State University ◽  
Freezing Level ◽  
Severe Thunderstorms ◽  
Fort Collins ◽  
Single Polarization ◽  
Real Time Identification

Abstract The issuance of timely warnings for the occurrence of severe-class hail (hailstone diameters of 2.5 cm or larger) remains an ongoing challenge for operational forecasters. This study examines the application of two remotely sensed data sources between 0100 and 0400 UTC 14 July 2011 when pulse-type severe thunderstorms occurred in the jurisdiction of the Denver/Boulder National Weather Service (NWS) Forecast Office in Colorado. First, a developing hailstorm was jointly observed by the dual-polarization Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) research radar and by the operational, single-polarization NWS radar at Denver/Front Range (KFTG). During the time period leading up to the issuance of the initial severe thunderstorm warning, the dual-polarization radar data near the 0 °C altitude contained a positive differential reflectivity ZDR column (indicating a strong updraft lofting supercooled raindrops above the freezing level). Correlation coefficient ρHV reductions to ~0.93, probably due to the presence of growing hailstones, were observed above the freezing level in portions of the developing >55-dBZ echo core. Second, data from the National Lightning Detection Network (NLDN), including the locations and polarity of cloud-to-ground (CG) discharges produced by several of the evening’s storms, were processed. Some association was found between the prevalence of positive CGs and storms that produced severe hail. The analyses indicate that the use of the dual-polarization data provided by the upgraded Weather Surveillance Radar-1988 Doppler (WSR-88D), in combination with the NLDN data stream, can assist operational forecasters in the real-time identification of thunderstorms that pose a severe hail threat.

Convective Modes for Significant Severe Thunderstorms in the Contiguous United States. Part I: Storm Classification and Climatology

2012 ◽  
Vol 27 (5) ◽  
pp. 1114-1135 ◽  
Author(s):  
Bryan T. Smith ◽  
Richard L. Thompson ◽  
Jeremy S. Grams ◽  
Chris Broyles ◽  
Harold E. Brooks
Keyword(s):  
United States ◽  
Great Plains ◽  
Radar Data ◽  
High Plains ◽  
Deep South ◽  
Southern Great Plains ◽  
Convective Systems ◽  
Severe Thunderstorms ◽  
Wind Events ◽  
Convective Mode

Abstract Radar-based convective modes were assigned to a sample of tornadoes and significant severe thunderstorms reported in the contiguous United States (CONUS) during 2003–11. The significant hail (≥2-in. diameter), significant wind (≥65-kt thunderstorm gusts), and tornadoes were filtered by the maximum event magnitude per hour on a 40-km Rapid Update Cycle model horizontal grid. The filtering process produced 22 901 tornado and significant severe thunderstorm events, representing 78.5% of all such reports in the CONUS during the sample period. The convective mode scheme presented herein begins with three radar-based storm categories: 1) discrete cells, 2) clusters of cells, and 3) quasi-linear convective systems (QLCSs). Volumetric radar data were examined for right-moving supercell (RM) and left-moving supercell characteristics within the three radar reflectivity designations. Additional categories included storms with marginal supercell characteristics and linear hybrids with a mix of supercell and QLCS structures. Smoothed kernel density estimates of events per decade revealed clear geographic and seasonal patterns of convective modes with tornadoes. Discrete and cluster RMs are the favored convective mode with southern Great Plains tornadoes during the spring, while the Deep South displayed the greatest variability in tornadic convective modes in the fall, winter, and spring. The Ohio Valley favored a higher frequency of QLCS tornadoes and a lower frequency of RM compared to the Deep South and the Great Plains. Tornadoes with nonsupercellular/non-QLCS storms were more common across Florida and the high plains in the summer. Significant hail events were dominated by Great Plains supercells, while variations in convective modes were largest for significant wind events.

Convective Modes for Significant Severe Thunderstorms in the Contiguous United States. Part II: Supercell and QLCS Tornado Environments

2012 ◽  
Vol 27 (5) ◽  
pp. 1136-1154 ◽  
Author(s):  
Richard L. Thompson ◽  
Bryan T. Smith ◽  
Jeremy S. Grams ◽  
Andrew R. Dean ◽  
Chris Broyles
Keyword(s):  
United States ◽  
Radar Data ◽  
Convective System ◽  
Severe Thunderstorm ◽  
Severe Thunderstorms ◽  
Real Time Identification ◽  
Environmental Archive ◽  
Tornado Damage ◽  
Effective Layer ◽  
Convective Mode

Abstract A sample of 22 901 tornado and significant severe thunderstorm events, filtered on an hourly 40-km grid, was collected for the period 2003–11 across the contiguous United States (CONUS). Convective mode was assigned to each case via manual examination of full volumetric radar data (Part I of this study), and environmental information accompanied each grid-hour event from the hourly objective analyses calculated and archived at the Storm Prediction Center (SPC). Sounding-derived parameters related to supercells and tornadoes formed the basis of this investigation owing to the dominance of right-moving supercells in tornado production and the availability of supercell-related convective parameters in the SPC environmental archive. The tornado and significant severe thunderstorm events were stratified by convective mode and season. Measures of buoyancy discriminated most strongly between supercell and quasi-linear convective system (QLCS) tornado events during the winter, while bulk wind differences and storm-relative helicity were similar for both supercell and QLCS tornado environments within in each season. The larger values of the effective-layer supercell composite parameter (SCP) and the effective-layer significant tornado parameter (STP) favored right-moving supercells that produced significant tornadoes, as opposed to weak tornadoes or supercells that produced only significant hail or damaging winds. Additionally, mesocyclone strength tended to increase with increasing SCP for supercells, and STP tended to increase as tornado damage class ratings increased. The findings underscore the importance of convective mode (discrete or cluster supercells), mesocyclone strength, and near-storm environment (as represented by large values of STP) in consistent, real-time identification of intense tornadoes.

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