scholarly journals Sounding-derived parameters associated with severe hail events in Romania

Időjárás ◽  
2021 ◽  
Vol 125 (1) ◽  
pp. 39-52
Author(s):  
Vasilică Istrate ◽  
Radu Vlad Dobri ◽  
Florentina Bărcăcianu ◽  
Răzvan Alin Ciobanu ◽  
Liviu Apostol
Keyword(s):  
Convective Available Potential Energy ◽  
Severe Weather ◽  
Atmospheric Environment ◽  
Atmospheric Conditions ◽  
Mean Values ◽  
Unstable Environment ◽  
Threat Index ◽  
Using Data ◽  
Virtual Temperature ◽  
Instability Indices

The present paper analyzes 549 severe weather events reported to the ESWD (European Severe Weather Database) that caused large hail in the territory of Romania. Values of atmospheric instability indices have been analyzed for these episodes using data from Bucharest and Budapest sounding stations. For a period of 140 days with episodes of large hail, 24 instability indices were analyzed to describe the atmospheric conditions of the main daily convective activity. The mean values for most indices characterize an unstable atmospheric environment. Of the indices that measure potential instability, VT (vertical totals index) and TT (totals index) had values that described a conductive atmospheric environment for the development of hailstorms. In addition, the interquartile values of LIV (lifted index using virtual temperature) had values lower than zero. For SWEAT (severe weather threat index) and CAPEV (convective available potential energy index using virtual temperature), only the values in the 75th percentile describe a very unstable environment (according to the literature). Strong linear correlations were registered between several pairs of indices such as CAPEV-LIV and SWEAT-SI that can be used for the operational forecast of hail.

scholarly journals Derecho Evolving from a Mesocyclone—A Study of 11 August 2017 Severe Weather Outbreak in Poland: Event Analysis and High-Resolution Simulation

2019 ◽  
Vol 147 (6) ◽  
pp. 2283-2306 ◽  
Author(s):  
Mateusz Taszarek ◽  
Natalia Pilguj ◽  
Juliusz Orlikowski ◽  
Artur Surowiecki ◽  
Szymon Walczakiewicz ◽  
...  
Keyword(s):  
High Resolution ◽  
Initial Conditions ◽  
Convective Available Potential Energy ◽  
Severe Weather ◽  
Mature Stage ◽  
Convective System ◽  
Event Analysis ◽  
Atmospheric Conditions ◽  
Mesoscale Convective ◽  
Resolution Simulation

Abstract This study documents atmospheric conditions, development, and evolution of a severe weather outbreak that occurred on 11 August 2017 in Poland. The emphasis is on analyzing system morphology and highlighting the importance of a mesovortex in producing the most significant wind damages. A derecho-producing mesoscale convective system (MCS) had a remarkable intensity and was one of the most impactful convective storms in the history of Poland. It destroyed and partially damaged 79 700 ha of forest (9.8 million m3 of wood), 6 people lost their lives, and 58 were injured. The MCS developed in an environment of high 0–3-km wind shear (20–25 m s−1), strong 0–3-km storm relative helicity (200–600 m2 s−2), moderate most-unstable convective available potential energy (1000–2500 J kg−1), and high precipitable water (40–46 mm). Within the support of a midtropospheric jet, the MCS moved northeast with a simultaneous northeastward inflow of warm and very moist air, which contributed to strong downdrafts. A mesocyclone embedded in the convective line induced the rear inflow jet (RIJ) to descend and develop a bow echo. In the mature stage, a supercell evolved into a bookend vortex and later into a mesoscale convective vortex. Swaths of the most significant wind damage followed the aforementioned vortex features. A high-resolution simulation performed with initial conditions derived from GFS and ECMWF global models predicted the possibility of a linear MCS with widespread damaging wind gusts and embedded supercells. Simulations highlighted the importance of cloud cover in the preconvective environment, which influenced the placement and propagation of the resulting MCS.

scholarly journals Cloud-to-ground lightning in Portugal: patterns and dynamical forcing

2012 ◽  
Vol 12 (3) ◽  
pp. 639-649 ◽  
Author(s):  
J. A. Santos ◽  
M. A. Reis ◽  
J. Sousa ◽  
S. M. Leite ◽  
S. Correia ◽  
...  
Keyword(s):  
Large Scale ◽  
Bimodal Distribution ◽  
Lightning Activity ◽  
Atmospheric Conditions ◽  
Remote Forcing ◽  
Cloud To Ground Lightning ◽  
Using Data ◽  
Number Of Discharges ◽  
Low Pressures ◽  
Large Scale Atmospheric Circulation

Abstract. An analysis of the cloud-to-ground discharges (CGD) over Portugal is carried out using data collected by a network of sensors maintained by the Portuguese Meteorological Institute for 2003–2009 (7 yr). Only cloud-to-ground flashes are considered and negative polarity CGD are largely dominant. The total number of discharges reveals a considerable interannual variability and a large irregularity in their distribution throughout the year. However, it is shown that a large number of discharges occur in the May–September period (71%), with a bimodal distribution that peaks in May and September, with most of the lightning activity recorded in the afternoon (from 16:00 to 18:00 UTC). In spring and autumn the lightning activity tends to be scattered throughout the country, whereas in summer it tends to be more concentrated over northeastern Portugal. Winter generally presents low lightning activity. Furthermore, two significant couplings between the monthly number of days with discharges and the large-scale atmospheric circulation are isolated: a regional forcing, predominantly in summer, and a remote forcing. In fact, the identification of daily lightning regimes revealed three important atmospheric conditions for triggering lightning activity: regional cut-off lows, cold troughs induced by remote low pressure systems and summertime regional low pressures at low-tropospheric levels combined with a mid-tropospheric cold trough.

scholarly journals Gap-Filling Mobile Radar Observations of a Snow Squall in the San Luis Valley

2018 ◽  
Vol 146 (8) ◽  
pp. 2469-2481 ◽  
Author(s):  
Andrew A. Rosenow ◽  
Kenneth Howard ◽  
José Meitín
Keyword(s):  
Convective Available Potential Energy ◽  
Radar Data ◽  
Gap Filling ◽  
San Luis Valley ◽  
San Luis ◽  
Radar Network ◽  
X Band ◽  
Using Data ◽  
Convective Cells ◽  
Large Improvement

Abstract On 24 January 2017, a convective snow squall developed in the San Luis Valley of Colorado. This squall produced rapidly varying winds at San Luis Valley airport in Alamosa, Colorado, with gusts up to 12 m s−1, and an associated visibility drop to 1.4 km from unlimited in less than 10 min. This snow squall was largely undetected by the operational WSR-88D network because of the Sangre de Cristo Range of the Rocky Mountains lying between the valley and the nearest WSR-88D in Pueblo, Colorado. This study presents observations of the snow squall from the X-band NOAA X-Pol radar, which was deployed in the San Luis Valley during the event. These observations document the squall developing from individual convective cells and growing upscale into a linear squall, with peak radial velocities of 15 m s−1. The environment conducive to the development of this snow squall is examined using data from the High-Resolution Rapid Refresh model, which shows an environment unstable to ascending surface-based parcels, with surface-based convective available potential energy (SBCAPE) values up to 600 J kg−1 in the San Luis Valley. The mobile radar data are integrated into the Multi-Radar Multi-Sensor (MRMS) mosaic to illustrate both the large improvement in detectability of this event gained from a gap-filling radar as well as the capability of MRMS to incorporate data from new radars designed to fill gaps in the current radar network.

scholarly journals The Advantages of a Mixed-Band Radar Network for Severe Weather Operations: A Case Study of 13 May 2009

2014 ◽  
Vol 29 (1) ◽  
pp. 78-98 ◽  
Author(s):  
Vivek N. Mahale ◽  
Jerald A. Brotzge ◽  
Howard B. Bluestein
Keyword(s):  
Situational Awareness ◽  
Severe Weather ◽  
Combined System ◽  
Low Level ◽  
Dynamic Events ◽  
Temporal Sampling ◽  
Radar Network ◽  
Upper Level ◽  
Using Data

Abstract Adding a mix of X- or C-band radars to the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network could address several limitations of the network, including improvements to spatial gaps in low-level coverage and temporal sampling of volume scans. These limitations can result in missing critical information in highly dynamic events, such as tornadoes and severe straight-line wind episodes. To evaluate the potential value of a mixed-band radar network for severe weather operations, a case study is examined using data from X- and S-band radars. On 13 May 2009, a thunderstorm complex associated with a cold front moved southward into southwest Oklahoma. A tornado rapidly developed from an embedded supercell within the complex. The life cycle of the tornado and subsequent wind event was sampled by the experimental Collaborative Adaptive Sensing of the Atmosphere (CASA) radar testbed of four X-band radars as well as two operational WSR-88Ds. In this study, the advantages of a mixed-band radar network are demonstrated through a chronological analysis of the event. The two radar networks provided enhanced overall situational awareness. Data from the WSR-88Ds provided 1) clear-air sensitivity, 2) a broad overview of the storm complex, 3) a large maximum unambiguous range, and 4) upper-level scans up to 19.5°. Data from the CASA radars provided 1) high-temporal, 1-min updates; 2) overlapping coverage for dual-Doppler analysis; and 3) dense low-level coverage. The combined system allowed for detailed, dual- and single-Doppler observations of a wind surge, a mesocyclone contraction, and a downburst.

scholarly journals A Note on Nonlinearity Bias and Dichotomous Choice CVM: Implications for Aggregate Benefits Estimation

1996 ◽  
Vol 25 (1) ◽  
pp. 54-59 ◽  
Author(s):  
R.A. Souter ◽  
J.M. Bowker
Keyword(s):  
Logit Model ◽  
Nonlinear Models ◽  
Nonlinear Function ◽  
Dichotomous Choice ◽  
Sample Mean ◽  
Mean Values ◽  
Concomitant Variables ◽  
The Mean ◽  
Using Data ◽  
Single Response

It is a generally known statistical fact that the mean of a nonlinear function of a set of random variables is not equivalent to the function evaluated at the means of the variables. However, in dichotomous choice contingent valuation studies a common practice is to calculate an overall mean (or median) by integrating over offer space (numerically or analytically) an estimated logit or probit function in which sample mean values for the concomitant variables are used. We demonstrate this procedure to be incorrect and we statistically test the procedure against the correct method for nonlinear models. Using data resulting in a well-behaved logit model, we reject the hypothesis of congruence between the two means. Such a finding should be considered in future single response dichotomous choice CVM studies, particularly when aggregation is of interest.

scholarly journals Evaluation of the Effect of Environmental Parameters on the Spread of COVID-19: A Fuzzy Logic Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-5
Author(s):  
Mohammad Asaduzzaman Chowdhury ◽  
Quazi Zobaer Shah ◽  
Mohammod Abul Kashem ◽  
Abdus Shahid ◽  
Nasim Akhtar
Keyword(s):  
Environmental Parameters ◽  
Developed Countries ◽  
Atmospheric Conditions ◽  
Uv Index ◽  
Mean Values ◽  
Infected People ◽  
Surface Graph ◽  
Fuzzy Logic Approach ◽  
Effective Role ◽  
Logic Approach

In recent months, the world has experienced the outbreak and spread of a new infectious disease, COVID-19. The spread of this disease has been so severe, and even many developed countries have struggled to manage this situation. However, some countries, such as China and Australia, have shown success in taking effective steps towards tackling the crisis. So far, some preventive measures to contain the spread of infection have emerged. Numerous studies have been undertaken worldwide in parallel in order to develop strategies to contain the virus, as well as to determine climatic or atmospheric conditions favoring COVID-19 spread. In this research, an artificial intelligence (AI) system has been adopted to assess the effective role of various environmental conditions in the spread of COVID-19. Temperature, relative humidity (RH), and UV index (UVI) of some affected countries were considered as input parameters while the total number of infected people is taken as the output variable. After plotting all available data as linguistic variables, a relationship is established between temperature, RH, UVI, and the number of infected people. From the surface graph, it can be stated that in addition to UVI, temperature and RH have a significant impact on the number of affected people. The maximum and minimum temperatures as well as other parameters are considered on the basis of mean values.

scholarly journals Instability indices and forecasting thunderstorms: the case of 30 April 2009

2012 ◽  
Vol 12 (2) ◽  
pp. 403-413 ◽  
Author(s):  
S. Tajbakhsh ◽  
P. Ghafarian ◽  
F. Sahraian
Keyword(s):  
Relative Humidity ◽  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Vertical Velocity ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Weather Station ◽  
Using Data ◽  
Instability Indices

Abstract. In this paper, one meteorological case study for two Iranian airports are presented. Attempts have been made to study the predefined threshold amounts of some instability indices such as vertical velocity and relative humidity. Two important output variables from a numerical weather prediction model have been used to survey thunderstorms. The climatological state of thunder days in Iran has been determined to aid in choosing the airports for the case studies. The synoptic pattern, atmospheric thermodynamics and output from a numerical weather prediction model have been studied to evaluate the occurrence of storms and to verify the threshold instability indices that are based on Gordon and Albert (2000) and Miller (1972). Using data from the Statistics and Data Center of the Iran Meteorological Organization, 195 synoptic stations were used to study the climatological pattern of thunderstorm days in Iran during a 15-yr period (1991–2005). Synoptic weather maps and thermodynamic diagrams have been drawn using data from synoptic stations and radiosonde data. A 15-km resolution version of the WRF numerical model has been implemented for the Middle East region with the assistance of global data from University Corporation for Atmospheric Research (UCAR). The Tabriz airport weather station has been selected for further study due to its high frequency of thunderstorms (more than 35 thunderstorm days per year) and the existence of an upper air station. Despite the fact that storms occur less often at the Tehran weather station, the station has been chosen as the second case study site due to its large amount of air traffic. Using these two case studies (Tehran at 00:00 UTC, 31 April 2009 and Tabriz at 12:00 UTC, 31 April 2009), the results of this research show that the threshold amounts of 30 °C for KI, −2 °C for LI and −3 °C for SI suggests the occurrence and non-occurrence of thunderstorms at the Tehran and Tabriz stations, respectively. The WRF model output of vertical velocity and relative humidity are the two most important indices for examining storm occurrence, and they have a numerical threshold of 1 m s−1 and 80%, respectively. These results are comparable to other studies that have examined thunderstorm occurrence.

The airport-sCAle seveRe weather nowcastinG prOject (CARGO)

2020 ◽  
Author(s):  
Riccardo Biondi ◽  
Pierre-Yves Tournigand ◽  
Enrico Solazzo ◽  
Eugenio Realini ◽  
Corrado Cimarelli ◽  
...  
Keyword(s):  
Water Vapour ◽  
Heavy Rain ◽  
Severe Weather ◽  
Time Range ◽  
Atmospheric Parameter ◽  
Atmospheric Conditions ◽  
Temporal Behaviour ◽  
Convective Systems ◽  
Integrated Water Vapour ◽  
Deep Convective Systems

<p>Monitoring and predicting extreme atmospheric events, such as deep convective systems, is very challenging especially when they develop locally in a short time range. Despite the great improvement in model parametrization and the use of satellite measurements, there are still <strong>l</strong>arge uncertainties on the knowledge of the dynamical processes of deep convective systems at local scale.</p><p>We use an innovative approach integrating a dense network of in situ measurements and satellite-based observations/products for the improvement of meteorological nowcasting at airport spatial scale focusing on the Malpensa airport (Italy). We add to the standard atmospheric parameters analysis, the information of integrated water vapour and lightning spatio-temporal behaviour (potential heavy rain precursors) during heavy rain phenomena detected by meteorological radars. The study is based on the anomaly of each atmospheric parameter during a convective event in comparison to its climatology in non-pre-convective environment, so that we are able to detect the variation with respect to the “standard” conditions. The ground based GNSS receivers (allowing the determination of the integrated water vapour trend before and during the storm), together with the lightning detectors, the weather stations (providing the trend of temperature, humidity and wind fields), the radiosondes and the GNSS radio occultations (allowing the estimation of vertical profiles of temperature, pressure and humidity) provide information on the pre-convective and non-pre-convective environment as a 3D picture of the atmospheric conditions.</p><p>The final goal is the test of a severe weather events nowcasting algorithm with high spatial resolution, and based on neural networks, for improving aviation safety. This is followed by the development of a user-friendly tailored final product, easily understandable by the Air Traffic Management stakeholder.</p><p>We have collected more than 600 cases suitable to develop the neural network algorithm. We show here the algorithm implementation and the meteorological characterization of deep convection usually developing on the Malpensa airport area.</p>

The impact of large-scale winds on thermally driven flows and exchange processes over mountainous terrain

2020 ◽  
Author(s):  
Jan Weinkaemmerer ◽  
Ivan Bašták Ďurán ◽  
Jürg Schmidli
Keyword(s):  
Boundary Layer ◽  
Large Scale ◽  
Volume Effect ◽  
Turbulent Heat ◽  
Atmospheric Conditions ◽  
Free Atmosphere ◽  
Convective Boundary ◽  
Mean Values ◽  
Mountainous Regions ◽  
The Impact

<p>In the convective boundary layer over mountainous regions, the mean values and the fluxes of quantities like heat, mass, and momentum are strongly influenced by thermally induced flows. Several studies have pointed out that the enhanced warming of the air inside a valley can be explained by the valley-volume effect whereas the cross-valley circulation leads to a net export of heat to the free atmosphere. We are interested in the influence of an upper-level wind on the local circulations and the boundary-layer properties, both locally and in terms of the horizontal mean, as this aspect has not yet received much attention. LES are carried out over idealized, two-dimensional topographies using the CM1 numerical model. For the analysis, turbulent, mean-circulation, and large-scale contributions are systematically distinguished. Also, budget analyses are performed for the turbulence kinetic energy and the turbulent heat and mass flux. Based on the first results for periodic topographies, no crucial influence on the horizontally averaged heat-flux and temperature profile can be observed, even though the flow pattern of the thermal wind is qualitatively changed. In addition to that, the impact on moisture transport will be evaluated and simulations over different topographies as well as for different atmospheric conditions and surface properties will be presented.</p>

scholarly journals Risk attribution of Campylobacter infection by age group using exposure modelling

2010 ◽  
Vol 138 (12) ◽  
pp. 1748-1761 ◽  
Author(s):  
S. BUETTNER ◽  
B. WIELAND ◽  
K. D. C. STAERK ◽  
G. REGULA
Keyword(s):  
Risk Factors ◽  
Age Groups ◽  
Poultry Meat ◽  
Exposure Model ◽  
Relative Importance ◽  
Prevention Measures ◽  
Mean Values ◽  
Exposure Pathways ◽  
Risk Attribution ◽  
Using Data

SUMMARYKnowledge on the relative importance of alternative sources of human campylobacteriosis is important in order to implement effective disease prevention measures. The objective of this study was to assess the relative importance of three key exposure pathways (travelling abroad, poultry meat, pet contact) for different patient age groups in Switzerland. With a stochastic exposure model data on Campylobacter incidence for the years 2002–2007 were linked with data for the three exposure pathways and the results of a case-control study. Mean values for the population attributable fractions (PAF) over all age groups and years were 27% (95% CI 17–39) for poultry consumption, 27% (95% CI 22–32) for travelling abroad, 8% (95% CI 6–9) for pet contact and 39% (95% CI 25–50) for other risk factors. This model provided robust results when using data available for Switzerland, but the uncertainties remained high. The output of the model could be improved if more accurate input data are available to estimate the infection rate per exposure. In particular, the relatively high proportion of cases attributed to ‘other risk factors’ requires further attention.

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