scholarly journals Severe Convective Storms across Europe and the United States. Part I: Climatology of Lightning, Large Hail, Severe Wind, and Tornadoes

2020 ◽  
Vol 33 (23) ◽  
pp. 10239-10261 ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Pieter Groenemeijer ◽  
Roger Edwards ◽  
Harold E. Brooks ◽  
...  
Keyword(s):  
United States ◽  
Great Plains ◽  
The United States ◽  
Maximum Activity ◽  
Severe Weather ◽  
Eastern United States ◽  
Convective Storms ◽  
Convective Systems ◽  
Lightning Detection ◽  
Mesoscale Convective

AbstractAs lightning-detection records lengthen and the efficiency of severe weather reporting increases, more accurate climatologies of convective hazards can be constructed. In this study we aggregate flashes from the National Lightning Detection Network (NLDN) and Arrival Time Difference long-range lightning detection network (ATDnet) with severe weather reports from the European Severe Weather Database (ESWD) and Storm Prediction Center (SPC) Storm Data on a common grid of 0.25° and 1-h steps. Each year approximately 75–200 thunderstorm hours occur over the southwestern, central, and eastern United States, with a peak over Florida (200–250 h). The activity over the majority of Europe ranges from 15 to 100 h, with peaks over Italy and mountains (Pyrenees, Alps, Carpathians, Dinaric Alps; 100–150 h). The highest convective activity over continental Europe occurs during summer and over the Mediterranean during autumn. The United States peak for tornadoes and large hail reports is in spring, preceding the maximum of lightning and severe wind reports by 1–2 months. Convective hazards occur typically in the late afternoon, with the exception of the Midwest and Great Plains, where mesoscale convective systems shift the peak lightning threat to the night. The severe wind threat is delayed by 1–2 h compared to hail and tornadoes. The fraction of nocturnal lightning over land ranges from 15% to 30% with the lowest values observed over Florida and mountains (~10%). Wintertime lightning shares the highest fraction of severe weather. Compared to Europe, extreme events are considerably more frequent over the United States, with maximum activity over the Great Plains. However, the threat over Europe should not be underestimated, as severe weather outbreaks with damaging winds, very large hail, and significant tornadoes occasionally occur over densely populated areas.

A Climatology of Quasi-Linear Convective Systems and Their Hazards in the United States

2019 ◽  
Vol 34 (6) ◽  
pp. 1605-1631 ◽  
Author(s):  
Walker S. Ashley ◽  
Alex M. Haberlie ◽  
Jacob Strohm
Keyword(s):  
United States ◽  
Great Plains ◽  
Mississippi River ◽  
The United States ◽  
Classification Systems ◽  
Ohio River ◽  
Eastern United States ◽  
Convective Systems ◽  
Intensity Information ◽  
River Valleys

Abstract This research uses image classification and machine learning methods on radar reflectivity mosaics to segment, classify, and track quasi-linear convective systems (QLCSs) in the United States for a 22-yr period. An algorithm is trained and validated using radar-derived spatial and intensity information from thousands of manually labeled QLCS and non-QLCS event slices. The algorithm is then used to automate the identification and tracking of over 3000 QLCSs with high accuracy, affording the first, systematic, long-term climatology of QLCSs. Convective regions determined by the procedure to be QLCSs are used as foci for spatiotemporal filtering of observed severe thunderstorm reports; this permits an estimation of the number of severe storm hazards due to this morphology. Results reveal that nearly 32% of MCSs are classified as QLCSs. On average, 139 QLCSs occur annually, with most of these events clustered from April through August in the eastern Great Plains and central/lower Mississippi and Ohio River Valleys. QLCSs are responsible for a spatiotemporally variable proportion of severe hazard reports, with a maximum in QLCS-report attribution (30%–42%) in the western Ohio and central Mississippi River Valleys. Over 21% of tornadoes, 28% of severe winds, and 10% of severe hail reports are due to QLCSs across the central and eastern United States. The proportion of QLCS-affiliated tornado and severe wind reports maximize during the overnight and cool season, with more than 50% of tornadoes and wind reports in some locations due to QLCSs. This research illustrates the utility of automated storm-mode classification systems in generating extensive, systematic climatologies of phenomena, reducing the need for time-consuming and spatiotemporal-limiting methods where investigators manually assign morphological classifications.

scholarly journals Severe Convective Storms across Europe and the United States. Part II: ERA5 Environments Associated with Lightning, Large Hail, Severe Wind, and Tornadoes

2020 ◽  
Vol 33 (23) ◽  
pp. 10263-10286 ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Tomáš Púčik ◽  
Kimberly A. Hoogewind ◽  
Harold E. Brooks
Keyword(s):  
United States ◽  
Great Plains ◽  
Wind Shear ◽  
The United States ◽  
Severe Weather ◽  
Convective Initiation ◽  
Local Maxima ◽  
Severe Thunderstorms ◽  
Lightning Detection ◽  
Lapse Rates

AbstractIn this study we investigate convective environments and their corresponding climatological features over Europe and the United States. For this purpose, National Lightning Detection Network (NLDN) and Arrival Time Difference long-range lightning detection network (ATDnet) data, ERA5 hybrid-sigma levels, and severe weather reports from the European Severe Weather Database (ESWD) and Storm Prediction Center (SPC) Storm Data were combined on a common grid of 0.25° and 1-h steps over the period 1979–2018. The severity of convective hazards increases with increasing instability and wind shear (WMAXSHEAR), but climatological aspects of these features differ over both domains. Environments over the United States are characterized by higher moisture, CAPE, CIN, wind shear, and midtropospheric lapse rates. Conversely, 0–3-km CAPE and low-level lapse rates are higher over Europe. From the climatological perspective severe thunderstorm environments (hours) are around 3–4 times more frequent over the United States with peaks across the Great Plains, Midwest, and Southeast. Over Europe severe environments are the most common over the south with local maxima in northern Italy. Despite having lower CAPE (tail distribution of 3000–4000 J kg−1 compared to 6000–8000 J kg−1 over the United States), thunderstorms over Europe have a higher probability for convective initiation given a favorable environment. Conversely, the lowest probability for initiation is observed over the Great Plains, but, once a thunderstorm develops, the probability that it will become severe is much higher compared to Europe. Prime conditions for severe thunderstorms over the United States are between April and June, typically from 1200 to 2200 central standard time (CST), while across Europe favorable environments are observed from June to August, usually between 1400 and 2100 UTC.

scholarly journals Assessment of the High-Resolution Rapid Refresh Model’s Ability to Predict Mesoscale Convective Systems Using Object-Based Evaluation

2015 ◽  
Vol 30 (4) ◽  
pp. 892-913 ◽  
Author(s):  
James O. Pinto ◽  
Joseph A. Grim ◽  
Matthias Steiner
Keyword(s):  
United States ◽  
High Resolution ◽  
Size Distribution ◽  
Great Plains ◽  
Southeastern United States ◽  
Mesoscale Convective Systems ◽  
Eastern United States ◽  
Convective Systems ◽  
Object Based ◽  
Mesoscale Convective

Abstract An object-based verification technique that keys off the radar-retrieved vertically integrated liquid (VIL) is used to evaluate how well the High-Resolution Rapid Refresh (HRRR) predicted mesoscale convective systems (MCSs) in 2012 and 2013. It is found that the modeled radar VIL values are roughly 50% lower than observed. This mean bias is accounted for by reducing the radar VIL threshold used to identify MCSs in the HRRR. This allows for a more fair evaluation of the model’s skill at predicting MCSs. Using an optimized VIL threshold for each summer, it is found that the HRRR reproduces the first (i.e., counts) and second moments (i.e., size distribution) of the observed MCS size distribution averaged over the eastern United States, as well as their aspect ratio, orientation, and diurnal variations. Despite threshold optimization, the HRRR tended to predict too many (few) MCSs at lead times less (greater) than 4 h because of lead time–dependent biases in the modeled radar VIL. The HRRR predicted too many MCSs over the Great Plains and too few MCSs over the southeastern United States during the day. These biases are related to the model’s tendency to initiate too many MCSs over the Great Plains and too few MCSs over the southeastern United States. Additional low biases found over the Mississippi River valley region at night revealed a tendency for the HRRR to dissipate MCSs too quickly. The skill of the HRRR at predicting specific MCS events increased between 2012 and 2013, coinciding with changes in both the model physics and in the methods used to assimilate the three-dimensional radar reflectivity.

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.

scholarly journals Forecasting the Maintenance of Mesoscale Convective Systems Crossing the Appalachian Mountains

2010 ◽  
Vol 25 (4) ◽  
pp. 1179-1195 ◽  
Author(s):  
Casey E. Letkewicz ◽  
Matthew D. Parker
Keyword(s):  
Appalachian Mountains ◽  
Severe Weather ◽  
Mesoscale Convective Systems ◽  
Radiosonde Data ◽  
Eastern United States ◽  
Unique Problem ◽  
Convective Systems ◽  
Barrier Analysis ◽  
Mesoscale Convective ◽  
The Mean

Abstract Forecasting the maintenance of mesoscale convective systems (MCSs) is a unique problem in the eastern United States due to the influence of the Appalachian Mountains. At times these systems are able to traverse the terrain and produce severe weather in the lee, while at other times they instead dissipate upon encountering the mountains. To differentiate between crossing and noncrossing MCS environments, 20 crossing and 20 noncrossing MCS cases were examined. The cases were largely similar in terms of their 500-hPa patterns, MCS archetypes, and orientations with respect to the barrier. Analysis of radiosonde data, however, revealed that the environment east of the mountains discriminated between case types very well. The thermodynamic and kinematic variables that had the most discriminatory power included those associated with instability, several different bulk shear vector magnitudes, and also the mean tropospheric wind. Crossing cases were characterized by higher instability, which was found to be partially attributable to the diurnal cycle. However, these cases also tended to occur in environments with weaker shear and a smaller mean wind. The potential reasons for these results, and their forecasting implications, are discussed.

Regional, Seasonal, and Diurnal Variations of Cloud-to-Ground Lightning with Large Impulse Charge Moment Changes

2014 ◽  
Vol 142 (10) ◽  
pp. 3666-3682 ◽  
Author(s):  
Nick K. Beavis ◽  
Timothy J. Lang ◽  
Steven A. Rutledge ◽  
Walter A. Lyons ◽  
Steven A. Cummer
Keyword(s):  
United States ◽  
Atlantic Ocean ◽  
Great Plains ◽  
Southeastern United States ◽  
Northern Great Plains ◽  
Total Charge ◽  
Central Plains ◽  
Convective Systems ◽  
Seasonal And Diurnal Variations ◽  
Mesoscale Convective

Abstract The use of both total charge moment change (CMC) and impulse charge moment change (iCMC) magnitudes to assess the potential of a cloud-to-ground (CG) lightning stroke to induce a mesospheric sprite has been well described in the literature, particularly on a case study basis. In this climatological study, large iCMC discharges for thresholds of >100 and >300 C km in both positive and negative polarities are analyzed on a seasonal basis. Also presented are local solar time diurnal distributions in eight different regions covering the lower 48 states as well as the adjacent Atlantic Ocean, including the Gulf Stream. The seasonal maps show the predisposition of large positive iCMCs to dominate across the northern Great Plains, with large negative iCMCs favored in the southeastern United States year-round. During summer, the highest frequency of large positive iCMCs across the upper Midwest aligns closely with the preferred tracks of nocturnal mesoscale convective systems (MCSs). As iCMC values increase above 300 C km, the maximum shifts eastward of the 100 C km maximum in the central plains. Diurnal distributions in the eight regions support these conclusions, with a nocturnal peak in large iCMC discharges in the northern Great Plains and Great Lakes, an early to midafternoon peak in the Intermountain West and the southeastern United States, and a morning peak in large iCMC discharge activity over the Atlantic Ocean. Large negative iCMCs peak earlier in time than large positive iCMCs, which may be attributed to the growth of large stratiform charge reservoirs following initial convective development.

scholarly journals Mobile Radiosonde Deployments during the Mesoscale Predictability Experiment (MPEX): Rapid and Adaptive Sampling of Upscale Convective Feedbacks

2016 ◽  
Vol 97 (3) ◽  
pp. 329-336 ◽  
Author(s):  
Robert J. Trapp ◽  
David J. Stensrud ◽  
Michael C. Coniglio ◽  
Russ S. Schumacher ◽  
Michael E. Baldwin ◽  
...  
Keyword(s):  
United States ◽  
Great Plains ◽  
Adaptive Sampling ◽  
The United States ◽  
Sampling Strategies ◽  
Dual Frequency ◽  
Field Campaign ◽  
Convective Storms ◽  
Convective Scale

Abstract The Mesoscale Predictability Experiment (MPEX) was a field campaign conducted 15 May through 15 June 2013 within the Great Plains region of the United States. One of the research foci of MPEX regarded the upscaling effects of deep convective storms on their environment, and how these feed back to the convective-scale dynamics and predictability. Balloon-borne GPS radiosondes, or “upsondes,” were used to sample such environmental feedbacks. Two of the upsonde teams employed dual-frequency sounding systems that allowed for upsonde observations at intervals as fast as 15 min. Because these dual-frequency systems also had the capacity for full mobility during sonde reception, highly adaptive and rapid storm-relative sampling of the convectively modified environment was possible. This article documents the mobile sounding capabilities and unique sampling strategies employed during MPEX.

scholarly journals Tornado Damage Rating Probabilities Derived from WSR-88D Data

2017 ◽  
Vol 32 (4) ◽  
pp. 1509-1528 ◽  
Author(s):  
Richard L. Thompson ◽  
Bryan T. Smith ◽  
Jeremy S. Grams ◽  
Andrew R. Dean ◽  
Joseph C. Picca ◽  
...  
Keyword(s):  
United States ◽  
Great Plains ◽  
Probability Distributions ◽  
Rotational Velocity ◽  
The United States ◽  
Low Level ◽  
Convective Systems ◽  
Severe Thunderstorms ◽  
Damage Indicators ◽  
Tornado Damage

Abstract Previous work with observations from the NEXRAD (WSR-88D) network in the United States has shown that the probability of damage from a tornado, as represented by EF-scale ratings, increases as low-level rotational velocity increases. This work expands on previous studies by including reported tornadoes from 2014 to 2015, as well as a robust sample of nontornadic severe thunderstorms [≥1-in.- (2.54 cm) diameter hail, thunderstorm wind gusts ≥ 50 kt (25 m s−1), or reported wind damage] with low-level cyclonic rotation. The addition of the nontornadic sample allows the computation of tornado damage rating probabilities across a spectrum of organized severe thunderstorms represented by right-moving supercells and quasi-linear convective systems. Dual-polarization variables are used to ensure proper use of velocity data in the identification of tornadic and nontornadic cases. Tornado damage rating probabilities increase as low-level rotational velocity Vrot increases and circulation diameter decreases. The influence of height above radar level (or range from radar) is less obvious, with a muted tendency for tornado damage rating probabilities to increase as rotation (of the same Vrot magnitude) is observed closer to the ground. Consistent with previous work on gate-to-gate shear signatures such as the tornadic vortex signature, easily identifiable rotation poses a greater tornado risk compared to more nebulous areas of cyclonic azimuthal shear. Additionally, tornado probability distributions vary substantially (for similar sample sizes) when comparing the southeast United States, which has a high density of damage indicators, to the Great Plains, where damage indicators are more sparse.

scholarly journals Observational Analysis of the Predictability of Mesoscale Convective Systems

2007 ◽  
Vol 22 (4) ◽  
pp. 813-838 ◽  
Author(s):  
Israel L. Jirak ◽  
William R. Cotton
Keyword(s):  
United States ◽  
Wind Shear ◽  
Vertical Wind Shear ◽  
The United States ◽  
Vertical Wind ◽  
Mesoscale Convective Systems ◽  
Convective Initiation ◽  
Low Level ◽  
Convective Systems ◽  
Mesoscale Convective

Abstract Mesoscale convective systems (MCSs) have a large influence on the weather over the central United States during the warm season by generating essential rainfall and severe weather. To gain insight into the predictability of these systems, the precursor environments of several hundred MCSs across the United States were reviewed during the warm seasons of 1996–98. Surface analyses were used to identify initiating mechanisms for each system, and North American Regional Reanalysis (NARR) data were used to examine the environment prior to MCS development. Similarly, environments unable to support organized convective systems were also investigated for comparison with MCS precursor environments. Significant differences were found between environments that support MCS development and those that do not support convective organization. MCSs were most commonly initiated by frontal boundaries; however, features that enhance convective initiation are often not sufficient for MCS development, as the environment needs also to be supportive for the development and organization of long-lived convective systems. Low-level warm air advection, low-level vertical wind shear, and convective instability were found to be the most important parameters in determining whether concentrated convection would undergo upscale growth into an MCS. Based on these results, an index was developed for use in forecasting MCSs. The MCS index assigns a likelihood of MCS development based on three terms: 700-hPa temperature advection, 0–3-km vertical wind shear, and the lifted index. An evaluation of the MCS index revealed that it exhibits features consistent with common MCS characteristics and is reasonably accurate in forecasting MCSs, especially given that convective initiation has occurred, offering the possibility of usefulness in operational forecasting.

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