Severe Thunderstorms Research Articles

Caught In A Severe Thunderstorm, Fuel Is Low, Passenger Having Heart Attack, Hydraulics Are Failing, Instruments Are Iffy, And No Airport Is In Sight: Quick As The Pilot, What Do You Do?

University administrators can take a cue from pilots. Pilots regularly face decision situations where much lies in the balance. So it is with university administrators. The department, college or university itself can be compared to an aircraft. In flight, there are times when the sun shines and winds are favorable: a comfortable flight results and the mission is accomplished. At other times, thunderstorms ravage the skies, fuel may run low, structures and people may fail, and problems arise. So it is with universities and colleges. Sometimes things are great and at other times problems arise that interfere with the institutions role and mission. It is in the parallels of flying and leading an educational institution that allows flying wisdom to be of use.

Quantifying the impact of adding gap filling radar data on forecaster wind assessments, warnings, and confidence

AbstractExperimental weather radars are being developed that could enhance the severe weather warning process by providing higher resolution data sensed closer to the ground and with faster update rates. Because wind speed is an important criterion in the issuance of severe thunderstorm warnings, this research investigates the impact of adding these new data to the forecaster decision‐making process. In a static case review setting, 30 National Weather Service (NWS) forecasters evaluated six convective weather cases under two conditions: (1) using (conventional) WSR‐88D weather radar data, and, (2) using both WSR‐88D and additional data from an experimental four‐radar network. Forecasters' predictions of ground level wind gusts, 2–5 min into the future, were compared to measurements from ground‐based wind sensors. When provided with the additional radar data participants significantly improved the accuracy of their wind speed assessments (absolute error reduced from 5.9 m s−1 to 4.0 m s−1; p < 0.001), increased their assessment confidence ratings (p < 0.001), forecasted significantly greater wind speeds (20.4 m s−1 as opposed to 17.1 m s−1; p < 0.001), and increased the number of affirmative decisions to warn from 15 to 35 (p = 0.001). While the addition of high resolution, low altitude, rapidly updating radar data is shown to have both qualitative and quantitative benefits, training and warning policy implications for the incorporation of new technology must also be carefully considered as increased accuracy, confidence and higher wind speed estimates may lead to more warnings. Copyright © 2011 Royal Meteorological Society

The Understanding Severe Thunderstorms and Alberta Boundary Layers Experiment (UNSTABLE) 2008

Severe thunderstorms are a common occurrence in summer on the Canadian prairies, with a large number originating along the Alberta, Canada, foothills, just east of the Rocky Mountains. Most of these storms move eastward to affect the Edmonton–Calgary corridor, one of the most densely populated and fastest-growing regions in Canada. Previous studies in the United States, Europe, and Canada have stressed the importance of mesoscale features in thunderstorm development. However, such processes cannot be adequately resolved using operational observation networks in many parts of Canada. Current conceptual models for severe storm outbreaks in Alberta were developed almost 20 years ago and do not focus explicitly on mesoscale boundaries that are now known to be important for thunderstorm development. The Understanding Severe Thunderstorms and Alber ta Boundary Layers Experiment (UNSTABLE) is a field and modeling study aiming to improve our understanding of the processes associated with the initiation of severe thunderstorms, to refine associated conceptual models, and to assess the ability of convectivescale NWP models to simulate relevant physical processes. As part of UNSTABLE in 2008, Environment Canada and university scientists conducted a pilot field experiment over the Alberta foothills to investigate mesoscale processes associated with the development of severe thunderstorms. Networks of fixed and mobile surface and upper-air instrumentation provided observations of the atmospheric boundary layer at a level of detail never before seen in this region. Preliminary results include the most complete documentation of a dryline in Canada and an analysis of variability in boundary layer evolution across adjacent forest and crop vegetation areas. Convective-scale NWP simulations suggest that although additional information on convective mode may be provided, there is limited benefit overall to downscaling to smaller grid spacing without assimilation of mesoscale observations.

Assessment of the return period of near‐PMP point and catchment rainfall for England and Wales

AbstractThe return periods of sub‐daily rainfall events approaching Probable Maximum Precipitation (PMP) have been estimated for point locations and catchment areas using the assumptions made in a previously published storm model. It has been assumed that PMP of around 12 h duration is the result of severe thunderstorms for catchments up to about 200 km2 and of mesoscale convective systems (MCSs) for larger catchments. The analysis suggests return periods ranging from around 1 in 10 000 years for point locations to 1 in 500 000 years for large catchments, though these are very dependent on the assumptions. The results are compared with estimates from a number of other sources. Copyright © 2010 Royal Meteorological Society

Probabilistic forecast guidance for severe thunderstorms based on the identification of extreme phenomena in convection-allowing model forecasts

Probabilistic forecast guidance for severe thunderstorms based on the identification of extreme phenomena in convection-allowing model forecasts

Analysis of Lightning Characteristics in a Thunderstorm with Gust

One severe thunderstorm with damaging straight-line wind occurred on 21 June 2005 in north Shandong Province. Based on the analysis of lightning activities, radar echo and cloud image, it was found that the cloud-to-ground (CG) flash rates increased rapidly at the initial stage, and kept in a high level (about above 20 fl/5min) during the whole mature stage. At the dissipating stage, positive CG flashes gradually became dominant. For the advent of the peak value, the hourly flash rate lagged behind the minimum brightness temperature, and the area of cold cloud shield with temperature <−50°C lagged behind the hourly flash rate. The pulse of CG flash rate was slightly ahead of the occurrence of severe surface wind. Downburst caused the damaging wind with the maximum measured value of wind speed approximately the same to the maximum potential speed calculated by WINDEX.

The Relationship between Tornadic and Nontornadic Convective Wind Fatalities and Warnings

Abstract A database of tornado fatalities, nontornadic convective wind fatalities, severe thunderstorm warnings, and tornado warnings was compiled for the period 1986–2007 to assess the spatial and temporal distribution of warned and unwarned fatalities. The time of fatality and location as reported in Storm Data was compared to tornado and severe thunderstorm warnings to determine if a warning was in effect when the fatality occurred. Overall, 23.7% of tornado fatalities were unwarned, while 53.2% of nontornadic convective wind fatalities were unwarned. Most unwarned tornado fatalities occurred prior to the mid-1990s—coinciding with modernization of the National Weather Service—while unwarned nontornadic convective wind fatalities remained at a relatively elevated frequency throughout the study period. Geographic locations with high numbers of unwarned tornado and nontornadic convective wind fatalities were associated with one high-magnitude event that was unwarned rather than a series of smaller unwarned events over the period. There are many factors that contribute to warning response by the public, and the issuance of a severe thunderstorm or tornado warning is an important initial step in the warning process. A better understanding of the characteristics of warned and unwarned fatalities is important to future reduction of unwarned fatalities.

Ensemble prediction for nowcasting with a convection-permitting model—I: description of the system and the impact of radar-derived surface precipitation rates

A key strategy to improve the skill of quantitative predictions of precipitation, as well as hazardous weather such as severe thunderstorms and flash floods is to exploit the use of observations of convective activity (e.g. from radar). In this paper, a convection-permitting ensemble prediction system (EPS) aimed at addressing the problems of forecasting localized weather events with relatively short predictability time scale and based on a 1.5 km grid-length version of the Met Office Unified Model is presented. Particular attention is given to the impact of using predicted observations of radar-derived precipitation intensity in the ensemble transform Kalman filter (ETKF) used within the EPS. Our initial results based on the use of a 24-member ensemble of forecasts for two summer case studies show that the convectivescale EPS produces fairly reliable forecasts of temperature, horizontal winds and relative humidity at 1 h lead time, as evident from the inspection of rank histograms. On the other hand, the rank histograms seem also to show that the EPS generates too much spread for forecasts of (i) surface pressure and (ii) surface precipitation intensity. These may indicate that for (i) the value of surface pressure observation error standard deviation used to generate surface pressure rank histograms is too large and for (ii) may be the result of non-Gaussian precipitation observation errors. However, further investigations are needed to better understand these findings. Finally, the inclusion of predicted observations of precipitation from radar in the 24-member EPS considered in this paper does not seem to improve the 1-h lead time forecast skill.

A Probe for Consistency in CAPE and CINE During the Prevalence of Severe Thunderstorms:Statistical – Fuzzy Coupled Approach

Thunderstorms of pre-monsoon season (April – May) over Kolkata (22° 32’N, 88° 20’E), India are invariably accompanied with lightning flashes, high wind gusts, torrential rainfall, occasional hail and tornadoes which significantly affect the life and property on the ground and aviation aloft. The societal and economic impact due to such storms made accurate prediction of the weather phenomenon a serious concern for the meteorologists of India. The initiation of such storms requires sufficient moisture in lower troposphere, high surface temperature, conditional instability and a source of lift to initiate the convection. Convective available potential energy (CAPE) is a measure of the energy realized when conditional instability is released. It plays an important role in meso-scale convective systems. Convective inhibition energy (CINE) on the other hand acts as a possible barrier to the release of convection even in the presence of high value of CAPE. The main idea of the present study is to see whether a consistent quantitative range of CAPE and CINE can be identified for the prevalence of such thunderstorms that may aid in operational forecast. A statistical – fuzzy coupled method is implemented for the purpose. The result reveals that a definite range of CINE within 0 – 150 Jkg-1 is reasonably pertinent whereas no such range of CAPE depicts any consistency for the occurrence of severe thunderstorms over Kolkata. The measure of CINE mainly depends upon the altitude of the level of free convection (LFC), surface temperature (T) and surface mixing ratio (q). The box-and-whisker plot of LFC, T and q are drawn to select the most dependable parameter for the consistency of CINE in the prevalence of such thunderstorms. The skills of the parameters are evaluated through skill score analyses. The percentage error during validation with the observation of 2010 is estimated to be 0% for the range of CINE and 3.9% for CAPE.

Quantitative comparison of METEOSAT thunderstorm detection and nowcasting with in situ reports in the European Severe Weather Database (ESWD)

Severe thunderstorms constitute a major weather hazard in Europe, with an estimated total damage of €5–8 billion each year. Yet a pan-European database of severe weather reports in a homogeneous data format has become available only recently: the European Severe Weather Database (ESWD). We demonstrate the large potential of ESWD applications for storm detection and forecast evaluation purposes. The study of six warm season severe weather days in Europe from 2007 to 2008 revealed that up to 47% of the ESWD reports were located exactly within the polygons detected by the Cb-TRAM algorithm for three different stages of deep moist convection. The cool-season case study of extratropical cyclone “Emma” on 1 March 2008 showed that low-topped winter thunderstorms provide a challenge for satellite storm detection and nowcasting adapted to warm season storms with high, cold cloud tops. However, this case also demonstrated how ESWD reports alone can still be valuable to identify the hazardous regions along the cold front of the cyclone. The analysis of all warm season (JJA) severe weather days in Europe in 2008 corroborated these findings. There is good agreement between ESWD reports and Cb-TRAM detected thunderstorms, even though no exact correspondence between ESWD reports and Cb-TRAM cells is required (e.g., due to storm morphology). Correspondingly, a large portion of ESWD reports regarded as misses by our strict in/out-of-Cb-TRAM-polygon criterion were still located close to a Cb-TRAM cell. Quantitatively, only the probability of detection (POD) can be evaluated due to the different characteristics of the two data sources. For the JJA 2008 period, the POD for storm detection was 0.24 on average, with maximum values up to 0.58. The respective analysis for the 30 and 60 minute nowcasts yielded average POD values of 0.11 and 0.08, respectively, with maximum values of POD exceeding 0.4 on three different days for the 30 minute nowcast and on one day for the 60 minute nowcast.

Forecasting challenges during the severe weather outbreak in Central Europe on 25 June 2008

On 25 June 2008, severe thunderstorms caused widespread damage and two fatalities in the Czech Republic. Significant features of the storms included numerous downbursts on a squall line that exhibited a bow echo reflectivity pattern, with sustained wind gusts over 32 m/s at several reporting stations. Moreover, a tornado and several downbursts of F2 intensity occurred within the convective system, collocated with the development of mesovortices within the larger scale bow echo. The extent of the event was sufficient to call it a derecho, as the windstorm had affected Eastern Germany, Southern Poland, Slovakia, Austria and Northern Hungary as well. Ahead of the squall line, several well-organized isolated cells occurred, exhibiting supercellular characteristics, both from a radar and visual perspective. These storms produced large hail and also isolated severe wind gusts. This paper deals mostly with the forecasting challenges that were experienced by the meteorologist on duty during the evolution of this convective scenario. The main challenge of the day was to identify the region that would be most affected by severe convection, especially as the numerical weather prediction failed to anticipate the extent and the progress of the derecho-producing mesoscale convective systems (MCSs). Convective storms developed in an environment conducive to severe thunderstorms, with strong wind shear confined mostly to the lower half of the troposphere. These developments also were strongly influenced by mesoscale factors, especially a mesolow centered over Austria and its trough stretching to Eastern Bohemia. The paper demonstrates how careful mesoscale analysis could prove useful in dealing with such convective situations. Remote-sensing methods are also shown to be useful in such situations, especially when they can offer sufficient lead time to issue a warning, which is not always the case.

Initiation of a severe thunderstorm over the Mediterranean Sea

The Mediterranean basin is regularly affected by severe weather associated with deep convection. Although convective systems are usually linked to coastal orography, some severe thunderstorms develop and mature over the sea. A recent example is the severe thunderstorm that affected the island of Mallorca in the afternoon of 4 October 2007. The storm formed early in the morning offshore of Murcia, and steadily became organized into a squall line. Arriving in Palma city, this squall line produced severe gusts, heavy rain and several tornadoes. The initiation and evolution of convection in these kinds of maritime events depend on both synoptic and mesoscale features. Representing such interactions is a challenge for numerical weather prediction. The aim of this study is to determine the prominent factors involved in the initiation and evolution of the damaging squall line, by means of high resolution numerical experiments. We also focus on squall line mesovortices to explain the potential for tornado development and the role of Mallorcan orography on their evolution. Simulations performed with the mesoscale model Méso-NH allowed relevant mechanisms for initiation and development of the strong squall line to be identified. The squall line initiates in an area with conditional instability, characterized by a cut-off and a southerly jet aloft and by moist, warm air at low-levels along a front. In addition, the area of low-level convergence offshore of Murcia, associated with the front and enhanced by a low downstream of the Atlas range, was shown to be crucial during the early stage of the convective system. The dry layer in the mid-troposphere and the strong sheared environment provide elements for understanding the development of such a damaging squall line. Moreover, a very high resolution experiment (600 m mesh) gave a very realistic representation of the squall line, including mesovortices ahead of the gust front, which confirmed the potential of this strong convective system for the genesis of small-scale vortices that may precede tornado development. A sensitivity experiment pointed out the prominent role of Mallorcan orography in straightening mesovortices approaching Palma city, and provided interesting elements for the understanding of the localization of tornadoes that occurred on 4 October 2007.

Numerical simulation of a severe late afternoon thunderstorm over Peninsular Malaysia

This paper presents a numerical study of the genesis and development of a tropical afternoon thunderstorm system over the central part of the western coast of Peninsular Malaysia on 10 June 2007. An attempt was made to numerically simulate the occurrence of the westward propagating rain system using the Pennsylvania State University — National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5). The prevailing wind convergence at the lower troposphere increased the humidity and instability of the atmosphere. The results illustrate that convection was initiated due to surface heating and became stronger in the early afternoon. The convective activity was further enhanced by the interaction between the sea breeze from the Straits of Malacca and the strong easterly winds from the South China Sea. Due to orographic settings, the convergence of these wind systems occurred in the vicinity of the Klang Valley area and led to heavy rainfall that caused a flash flood in the affected region. This case study suggests that land and sea breeze circulations, modified by local topography are potentially crucial to the initialization and development of severe afternoon thunderstorms over the western coast of Peninsular Malaysia.

Anomalous electric field changes and high flash rate beneath a thunderstorm in northeast India

In spite of many experimental and theoretical studies the relationships between storm dynamics, severe weather, and lightning activity have been least understood. Measurements of electric field made under a severe thunderstorm at a northeastern Indian station, Guwahati, India are reported. Lightning flash rate increases drastically to about 84 flashes per minute (fpm) during the active stage which lasted for about 7 minutes, from about 15 flashes per minute during the initial phase of thunderstorm. Sudden increase in lightning flash rate (‘lightning jump’) of about 65 fpm/min is also observed in the beginning of the active stage. The dissipating stage is marked by slow and steady decrease in lightning frequency. Despite very high flash rate during the active stage, no severe weather conditions are observed at the ground. It is proposed that the short duration of the active stage might be the reason for the non-observance of severe weather conditions at the ground. Analysis of Skew-t graph at Guwahati suggests that vertical distribution of Convective Available Potential Energy (CAPE) also may play some role in non-occurrence of severe weather at ground in spite of large lightning flash rate and lightning jump observed in this thunderstorm. Further, all electric field changes after a lightning discharge indicates the presence of strong Lower Positive Charge Centers (LPCC) in the active and dissipation stages. This suggests that LPCC plays an important role in initiation of lightning discharges in these stages.

Evaluation of European Storm Forecast Experiment (ESTOFEX) forecasts

Three years of forecasts of lightning and severe thunderstorms from the European Storm Forecast Experiment (ESTOFEX) have been evaluated. The forecasts exhibit higher quality in summer than in winter and there is some evidence that they have improved over the course of the evaluation. Five individual forecasters made the majority of the forecasts and differences in their forecasts are on the order of the overall variability of the forecast quality. As a result, the forecasts appear to come from a single unit, rather than from a group of individuals. The graphical description of the probability of detection and frequency of hits recently developed by Roebber is a valuable tool for displaying the time series of lightning forecast performance. It also appears that, even though they are not intended for that purpose, using the lightning forecasts as a low-end forecast of severe thunderstorms is potentially useful for decision makers.

Climatology of Thunderstorms for North Dakota, 2002–06

Abstract Radar and surface thunderstorm data in North Dakota were investigated to obtain the climatology of thunderstorms in the state. A life cycle analysis for the individual storm cells between 2002 and 2006 was carried out, and it was found that June and July were the peak months, late afternoon to early morning was the peak time for thunderstorms, the average lifetime of storm cells was 23.6 min, the average gust wind speed was 16.5 m s−1, the average track length was 21.8 km, and the average movement speed was 16.4 m s−1. The average movement of storm cells varied with months, and the storms moved toward the north, the northeast, and the east. It was also demonstrated that there were 19–35 thunderstorm days each year in North Dakota and that, of these, 9–14 thunderstorm days each year were associated with high speed winds. Severe thunderstorms composed 1.7% of all the thunderstorms in 2002–06. The most intense thunderstorm in North Dakota between 2002 and 2006 was associated with a 5-yr-high wind speed of 31.4 m s−1. It was also found that the longer-lasting storms were the stronger storms.

Nowcasting and assessing thunderstorm risk on the Lombardy region (Italy)

The problem of severe thunderstorm risk in the Lombardy region (Italy) is serious. In fact during the warm season many thunderstorms (TS) occur in high density populated area located between the river Po and the Alps. In the year 2003, about 90 TS caused damage to people, houses, cars, agriculture and electrical lines. About 30 municipalities undergo damage by tornadoes. The 2003 summer was not particularly anomalous with respect to others for TS activity. In this region storms are well detected by some C-band radars and the Meteosat satellites, but the study of the correlation between these variables and the TS severity needs the collection of many met-data at the ground. Unfortunately the lack of a fine mesh met-station network forces the use of local press news or subjective reports to identify the impact of TS. Since 2006 ERSE has been collaborating with the Lombardy Region – Civil Protection Service/Office – in developing and testing a system to detect and nowcast severe thunderstorms, STAF (Storm Track Alert and Forecast). STAF is a nowcasting tool based on Radar and MSG (Meteosat Second Generation) data that selects only severe TS, tracks them and produces alert messages to users. In order to evaluate the severity of a TS, a crucial issue for STAF is the correlation between variables detected by the remote-sensing instruments and the effects at the ground. The paper describes a method to classify the severity of a TS by computing an index named “probability of damage” (PD). The index has been carried out by means of a storm archive, where radar and satellite data are stored together with damages reports from newspapers, all collected in 2003 summer. The index has been verified during the 2009 summer, when STAF was applied in a field test involving a group of Civil Protection observers and users. The results of this test are reported in the paper. The test has been also an occasion for verifying the effectiveness of information provided by STAF to selected people locally responsible for public alert and rescue in the case of a severe weather event.

Nowcasting thunderstorms in the Mediterranean region using lightning data

Thunderstorms are often the cause of severe and disastrous flash floods. Lightning activity within these storms can be detected and monitored continuously from thousands of kilometers away and can therefore be very useful in improving forecasts and now-casts of severe thunderstorms. An improvement in the now-casting of such storms can assist in reducing damages and saving lives. Using the ZEUS ground-based VLF lightning detection network and the Warning Decision Support System–Integrated Information (WDSS–II) software, we performed now-casting simulations using 1 year of lightning data over the Mediterranean area. Thousands of thunderstorms were observed and now-cast 30, 60, 90 and 120 min ahead. Statistical analysis was then done by calculating the hit, miss and false-alarm rates, as well as the POD, FAR and CSI scores in order to determine the success of the now-casting. The results show that the algorithm is overall successful in now-casting the location of the lightning clusters, especially when applied to strong and consistent lightning events (it is these events which also have the strongest connection to flash floods). The probability of detection (POD) values range between 0.46 for 30 minute now-casts and 0.25 for 120 minute now-casts. The critical success index (CSI) values are quite similar, but slightly lower. The now-casting has a low false-alarm rate, 0.03 for 30 minute now-casts, which is also beneficial for operational use. This method has been implemented for the use in real-time now-casting and is used in the EU FLASH project to seek and track areas of thunderstorm risk according to lightning intensity. The experimental now-casts appear on the project website ( www.flashproject.org/).

Numerical simulation of macro- and micro-structures of intense convective clouds with a spectral bin microphysics model

By use of a three-dimensional compressible non-hydrostatic convective cloud model with detailed microphysics featuring spectral bins of cloud condensation nuclei (CCN), liquid droplets, ice crystals, snow and graupel particles, the spatial and temporal distributions of hydrometeors in a supercell observed by the (Severe Thunderstorm Electrification and Precipitation Study) STEPS triple-radar network are simulated and analyzed. The bin model is also employed to study the effect of CCN concentration on the evolution characteristics of the supercell. It is found that the CCN concentration not only affects the concentration and spectral distribution of water droplets, but also influences the characteristics of ice crystals and graupel particles. With a larger number of CCN, more water droplets and ice crystals are produced and the growth of graupel is restrained. With a small quantity of CCN the production of large size water droplets are promoted by initially small concentrations of water droplets and ice crystals, leading to earlier formation of small size graupel and restraining the recycling growth of graupel, and thus inhibiting the formation of large size graupel (or small size hail). It can be concluded that both the macroscopic airflow and microphysical processes influence the formation and growth of large size graupel (or small size hail). In regions with heavy pollution, a high concentration of CCN may restrain the formation of graupel and hail, and in extremely clean regions, excessively low concentrations of CCN may also limit the formation of large size graupel (hail).

A Velocity Dealiasing Technique Using Rapidly Updated Analysis from a Four-Dimensional Variational Doppler Radar Data Assimilation System

Abstract A Doppler velocity dealiasing algorithm is developed within the storm-scale four-dimensional radar data assimilation system known as the Variational Doppler Radar Analysis System (VDRAS). The innovative aspect of the algorithm is that it dealiases Doppler velocity at each grid point independently by using three-dimensional wind fields obtained either from an objective analysis using conventional observations and mesoscale model output or from a rapidly updated analysis of VDRAS that assimilates radar data. This algorithm consists of three steps: preserving horizontal shear, global dealiasing using reference wind from the objective analysis or the VDRAS analysis, and local dealiasing. It is automated and intended to be used operationally for radar data assimilation using numerical weather prediction models. The algorithm was tested with 384 volumes of radar data observed from the Next Generation Weather Radar (NEXRAD) for a severe thunderstorm that occurred during 15 June 2002. It showed that the algorithm was effective in dealiasing large areas of aliased velocities when the wind from the objective analysis was used as the reference and that more accurate dealiasing was achieved by using the continuously cycled VDRAS analysis.