Observational study of tornadic cells that hit Corsica during the ADRIAN storm on the 29th October 2018

The north-western Mediterranean basin often experiences thunderstorms with heavy precipitation, strong wind, lightning activity and sometimes waterspouts/tornadoes. One of the objectives of the EXAEDRE (EXploiting new Atmospheric Electricity Data for Research and the Environment) project is to better monitor the thunderstorms in this area through a better understanding of the physical processes that drive the dynamics, the microphysics and the electrical activity of the convective systems. Characteristics of the electrical activity such as flash rate, charge layer distribution or flash polarity are good proxies for thunderstorm monitoring and good evidences of the storm severity.The 29th October 2018, an intense trough developed over Mediterranean Sea between Balearic Islands and Corsica. This storm, called ADRIAN, produced several hazards (heavy precipitation, strong winds, intense lightning activity and hailstorm) in Corsica. Two tornadoes and one waterspout were observed in the morning at Porto Vecchio (EF2 tornado and waterspout) and Aleria (EF1 tornado), causing significant damages.In this study, we take a look at electrical and microphysical characteristics of the two tornadic cells. For that, observations of the LMA (Lightning Mapping Array) SAETTA network, deployed in Corsica, are used to document in 3D the total lightning activity. Complementary 2D lightning observations recorded by the French national lightning detection network METEORAGE are also investigated. We also use weather radar data from the M&#233;t&#233;o France network. A clustering algorithm is applied on both the lightning and radar data to identify and track the cells to document the evolution of several lightning-related and microphysical characteristics during the lifetime of each cell. We also applied a new method based on lightning leader velocity to automatically infer the vertical and horizontal structure of the electrical charge regions within each electrical cell.We first introduce the different observations and methodologies applied here. Then the main electrical properties of the tornadic cells (e.g. flash duration, vertical flash extension, charge layer, flash type and polarity) and microphysical characteristics as well as their temporal evolution are presented. Overall, the studied electrical cells produced few cloud-to-ground lightning flashes predominantly of negative polarity. The peaks of electrical activity occurred when tornadoes hit the land and these storms presented all an anomalous charge structure.

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Properties of the lightning flashes in North-western Mediterranean Sea as documented during the EXAEDRE project

10.5194/egusphere-egu21-9098 ◽

2021 ◽

Author(s):

Eric Defer ◽

Serge Prieur ◽

Stephane Pedeboy

Keyword(s):

Mediterranean Sea ◽

Regional Scale ◽

Atmospheric Electricity ◽

Western Mediterranean ◽

Pulse Number ◽

Lightning Activity ◽

Similar Distribution ◽

Flash Duration ◽

Western Mediterranean Sea ◽

North Western

The EXAEDRE (EXploiting new Atmospheric Electricity Data for Research and the Environment) project aims at better understanding North-western Mediterranean Sea thunderstorms through coupled observational- and modelling-based studies with a dedicated focus on the lightning activity and its properties at flash, storm and regional scale.In this work, the lightning activity is measured by the VHF Lightning Mapping Array (LMA) network SAETTA and the operational French lightning detection network Meteorage. SAETTA VHF sources are merged in flashes based on a DBSCAN algorithm (L2 SAETTA dataset). Meteorage strokes and pulses are then combined to SAETTA flashes based on temporal and pulse/stroke-dependent spatial criteria (L2b SAETTA-Meteorage dataset). Four categories of flashes can then be investigated: 1) CG L2b flashes with at least one CG stroke, 2) pure IC L2b flashes as detected by Meteorage with only IC pulses, 3) No-MTRG flashes which are only detected by SAETTA flashes with no concurrent Meteorage records, and 4) No-SAETTA flashes which were only reported by Meteorage with no concurrent SAETTA records.Several lightning parameters have been investigated for the first three L2b flash categories listed above. It includes among others the flash duration, the vertical flash extension, the 2D horizontal flash extension, the 10/50/90 percent quantile of flash altitude, the flash trigger altitude, the stroke/pulse number per flash, and the flash vertical extension. Based on the L2b database built from the SAETTA and Meteorage records of the entire year 2018, No-MTRG flashes have tendency to be rather small in terms of 2D flash extension or short in duration. They also statically exhibit a similar distribution of their 10/50/90 percent quantile of flash altitude. CG L2b flashes exhibit mainly altitudes below 8 km while the majority of pure IC flashes show distinct distribution of 10/50/90 percent quantile flash altitude. Three trigger altitude ranges, i.e. 4-5 km, 7-9 km, 11-12 km are found in the three studied categories. Finally, for the studied year, less +CG flashes occurred compared to the -CG flashes while CG flashes with more ground connections have the tendency to last longer and to be larger.First we will introduce the instruments and the data. We will then present the different methodologies applied here to generate the L2b dataset with some typical lightning observations. We will then discuss on the characteristics of the different parameters listed above.

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Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy

Water ◽

10.3390/w13131727 ◽

2021 ◽

Vol 13 (13) ◽

pp. 1727

Author(s):

Valerio Capecchi ◽

Andrea Antonini ◽

Riccardo Benedetti ◽

Luca Fibbi ◽

Samantha Melani ◽

...

Keyword(s):

Extreme Event ◽

Wrf Model ◽

Heavy Precipitation ◽

Radar Data ◽

Flash Floods ◽

Precipitation Event ◽

Weather Research And Forecasting ◽

Limited Area ◽

Heavy Precipitation Event ◽

The Town

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts.

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Cloud-Precipitation Hybrid Regimes and their Projection onto IMERG Precipitation Data

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-20-0253.1 ◽

2021 ◽

Author(s):

Daeho Jin ◽

Lazaros Oreopoulos ◽

Dongmin Lee ◽

Jackson Tan ◽

Nayeong Cho

Keyword(s):

Clustering Algorithm ◽

Relative Weight ◽

Heavy Precipitation ◽

Optimal Number ◽

Hybrid Regimes ◽

Precipitation Regimes ◽

Moderate Resolution ◽

Application Potential ◽

Moderate Resolution Imaging Spectroradiometer ◽

Cloud Top Pressure

AbstractIn order to better understand cloud-precipitation relationships, we extend the concept of cloud regimes (CRs) developed from two-dimensional joint histograms of cloud optical thickness and cloud top pressure from the Moderate Resolution Imaging Spectroradiometer (MODIS), to include precipitation information. Taking advantage of the high-resolution Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation dataset, we derive cloud-precipitation “hybrid” regimes by implementing a k-means clustering algorithm with advanced initialization and objective measures to determine the optimal number of clusters. By expressing the variability of precipitation rates within 1-degree grid cells as histograms and varying the relative weight of cloud and precipitation information in the clustering algorithm, we obtain several editions of hybrid cloud-precipitation regimes (CPRs), and examine their characteristics.In the deep tropics, when precipitation is weighted weakly, the cloud part centroids of the hybrid regimes resemble their counterparts of cloud-only regimes, but combined clustering tightens the cloud-precipitation relationship by decreasing each regime’s precipitation variability. As precipitation weight progressively increases, the shape of the cloud part centroids becomes blunter, while the precipitation part sharpens. When cloud and precipitation are weighted equally, the CPRs representing high clouds with intermediate to heavy precipitation exhibit distinct enough features in the precipitation parts of the centroids to allow us to project them onto the 30-min IMERG domain. Such a projection overcomes the temporal sparseness of MODIS cloud observations associated with substantial rainfall, suggesting great application potential for convection-focused studies where characterization of the diurnal cycle is essential.

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Separating precipitation and evapotranspiration from noise – a new filter routine for high resolution lysimeter data

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-10-14645-2013 ◽

2013 ◽

Vol 10 (12) ◽

pp. 14645-14674 ◽

Cited By ~ 1

Author(s):

A. Peters ◽

T. Nehls ◽

H. Schonsky ◽

G. Wessolek

Keyword(s):

Moving Average ◽

Heavy Precipitation ◽

Threshold Value ◽

Sensitivity Study ◽

Small Data ◽

Strong Wind ◽

Weight Changes ◽

Atmospheric Sciences ◽

Window Width ◽

Real Mass

Abstract. Weighing lysimeters yield the most precise and realistic measures for evapotranspiration (ET) and precipitation (P), which are of great importance for many questions regarding soil and atmospheric sciences. An increase or a decrease of the system mass (lysimeter plus seepage) indicate P or ET. These real mass changes of the lysimeter system have to be separated from measurement noise (e.g. caused by wind). The typical way to filter noisy lysimeter data is (i) to introduce a smoothing routine, like a moving average with a certain averaging window w, and then (ii) to apply a certain threshold value δ, accounting for measurement accuracy, separating significant from insignificant weight changes. Thus, two filter parameters are used, namely w and δ. Especially the time variable noise due to wind and strong signals due to heavy precipitation pose challenges for such noise reduction algorithms. If w is too small, data noise might be interpreted as real system changes. If w is too wide, small weight changes in short time intervals might be disregarded. The same applies to too small or too large values for δ. Application of constant w and δ lead either to unnecessary losses of accuracy or to faulty data due to noise. The aim of this paper is to solve that problem with a new filter routine, which is appropriate for any event, ranging from smooth evaporation to strong wind and heavy precipitation. Therefore, the new routine uses adaptive w and δ in dependence on signal strength and noise (AWAT – Adaptive Window and Adaptive Threshold filter). The AWAT filter, a moving average filter and the Savitzky–Golay filter with constant w and δ were applied to real lysimeter data comprising the above mentioned events. The AWAT filter was the only filter which could handle the data of all events very well. A sensitivity study shows that the magnitude of the maximum threshold value has practically no influence on the results, so that only the maximum window width must be predefined by the user.

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Statistical modeling of fire brigade operations with respect to extreme precipitation events over Berlin

10.5194/egusphere-egu21-14913 ◽

2021 ◽

Author(s):

Alexander Pasternack ◽

Ines Langer ◽

Henning W. Rust ◽

Uwe Ulbrich

Keyword(s):

Urban Climate ◽

Heavy Precipitation ◽

Radar Data ◽

Climate Conditions ◽

Large Cities ◽

Fire Brigade ◽

Extreme Precipitation Events ◽

Highly Sensitive ◽

Part Modeling ◽

Precipitation Events

Large cities and urban regions are highly sensitive to impacts caused by extreme events (e.g. heavy rainfall). As problems caused by hazardous atmospheric events are expected to intensify due to the Anthropogenic Climate Change, adequate adaptation planning of urban infrastructure is needed. Planning adaptations not only requires further research on potential impacts under changing climate conditions as a basis, but also a check of the practical feasibility for stakeholders.Under the BMBF research program &#8220;Urban Climate Under Change&#8221; ([UC]&#178;), we relate heavy precipitation events over Berlin to the respective fire brigade operations. Here, the precipitation data are based on temporally high resolved radar data. The fire brigade operation data are available on time and location, but the number of recorded events is small, and their distribution is highly overdispersive compared&#160;to&#160;a&#160;Poisson&#160;model. To account for this problem we apply a two part hurdle model with one part modeling the probability of the occurrence of fire brigade operations and one part modeling the actual number of operations given that at least one operation occurs. In the corresponding statistical models the parameters of the distributions are described by additive predictors, which are based on precipitation duration and intensity as well as building density. Based on 10 years of data with a cross validation setup, both the occurrence model and the model for the number of operations significantly outperform the reference climatology for certain areas over Berlin.

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The snow storm of 8 March 2010 in Catalonia (Spain): a paradigmatic wet-snow event with a high societal impact

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-427-2014 ◽

2014 ◽

Vol 14 (2) ◽

pp. 427-441 ◽

Cited By ~ 8

Author(s):

M. C. Llasat ◽

M. Turco ◽

P. Quintana-Seguí ◽

M. Llasat-Botija

Keyword(s):

Meteorological Factors ◽

Coastal Region ◽

Heavy Precipitation ◽

Precipitation Event ◽

Societal Impact ◽

Strong Wind ◽

Near Surface ◽

Wet Snow ◽

Snow Storm ◽

Meteorological Features

Abstract. A heavy precipitation event swept over Catalonia (NE Spain) on 8 March 2010, with a total amount that exceeded 100 mm locally and snowfall of more than 60 cm near the coast. Unusual for this region and at this time of the year, this snowfall event affected mainly the coastal region and was accompanied by thunderstorms and strong wind gusts in some areas. Most of the damage was due to "wet snow", a kind of snow that favours accretion on power lines and causes line-breaking and subsequent interruption of the electricity supply. This paper conducts an interdisciplinary analysis of the event to show its great societal impact and the role played by the recently developed social networks (it has been called the first "Snowfall 2.0"), as well to analyse the meteorological factors associated with the major damage, and to propose an indicator that could summarise them. With this aim, the paper introduces the event and its societal impact and compares it with other important snowfalls that have affected the Catalan coast, using the PRESSGAMA database. The second part of the paper shows the event's main meteorological features and analyses the near-surface atmospheric variables responsible for the major damage through the application of the SAFRAN (Système d'analyse fournissant des renseignements atmosphériques à la neige) mesoscale analysis, which, together with the proposed "wind, wet-snow index" (WWSI), allows to estimate the severity of the event. This snow storm provides further evidence of our vulnerability to natural hazards and highlights the importance of a multidisciplinary approach in analysing societal impact and the meteorological factors responsible for this kind of event.

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High-Resolution Simulation of the Electrification and Lightning of Hurricane Rita during the Period of Rapid Intensification

Journal of the Atmospheric Sciences ◽

10.1175/2010jas3659.1 ◽

2011 ◽

Vol 68 (3) ◽

pp. 477-494 ◽

Cited By ~ 48

Author(s):

Alexandre O. Fierro ◽

Jon M. Reisner

Keyword(s):

High Resolution ◽

Latent Heat ◽

Functional Relationship ◽

Doppler Radar ◽

Propagation Speed ◽

Radar Data ◽

Lightning Activity ◽

Rapid Intensification ◽

Hurricane Rita ◽

Resolution Simulation

Abstract In this paper, a high-resolution simulation establishing relationships between lightning and eyewall convection during the rapid intensification phase of Rita will be highlighted. The simulation is an attempt to relate simulated lightning activity within strong convective events (CEs) found within the eyewall and general storm properties for a case from which high-fidelity lightning observations are available. Specifically, the analysis focuses on two electrically active eyewall CEs that had properties similar to events observed by the Los Alamos Sferic Array. The numerically simulated CEs were characterized by updraft speeds exceeding 10 m s−1, a relatively more frequent flash rate confined in a layer between 10 and 14 km, and a propagation speed that was about 10 m s−1 less than of the local azimuthal flow in the eyewall. Within an hour of the first CE, the simulated minimum surface pressure dropped by approximately 5 mb. Concurrent with the pulse of vertical motions was a large uptake in lightning activity. This modeled relationship between enhanced vertical motions, a noticeable pressure drop, and heightened lightning activity suggests the utility of using lightning to remotely diagnose future changes in intensity of some tropical cyclones. Furthermore, given that the model can relate lightning activity to latent heat release, this functional relationship, once validated against a derived field produced by dual-Doppler radar data, could be used in the future to initialize eyewall convection via the introduction of latent heat and/or water vapor into a hurricane model.

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A Velocity Dealiasing Scheme Based on Minimization of Velocity Differences between Regions

Advances in Meteorology ◽

10.1155/2020/6157636 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Yue Yuan ◽

Ping Wang ◽

Di Wang ◽

Junzhi Shi

Keyword(s):

Radial Velocity ◽

Wind Shear ◽

Doppler Radar ◽

Heavy Precipitation ◽

Probability Of Detection ◽

Strong Wind ◽

Velocity Data ◽

Step Velocity ◽

Noise Data ◽

Radial Velocity Data

The velocity dealiasing is an essential work of automatic weather phenomenon identification, nowcasting, and disaster monitoring based on radial velocity data. The noise data, strong wind shear, and isolated echo region in the Doppler radar radial velocity data severely interfere with the velocity dealiasing algorithm. This paper proposes a two-step velocity dealiasing algorithm based on the minimization of velocity differences between regions to solve this problem. The first step is to correct aliased velocities by minimizing the sum of gradients in every region to eliminate abnormal velocity gradients between points. The interference of noise data and strong wind shear can be reduced by minimizing the whole gradients in a region. The second step is to dealiase velocities by the velocity differences between different isolated regions. The velocity of an unknown isolated region is determined by the velocities of all known regions. This step improves the dealiasing results of isolated regions. In this paper, 604 volume scan samples, including typhoons, squall lines, and heavy precipitation, were used to test the algorithm. The statistical results and analysis show that the proposed algorithm can dealiase the velocity field with a high probability of detection and a low false alarm rate.

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Aircraft Mounted Neural Network Electrostatic Discharge (ESD) Location

Materials Science Forum ◽

10.4028/www.scientific.net/msf.721.331 ◽

2012 ◽

Vol 721 ◽

pp. 331-336

Author(s):

Paul Ratnamahilan Polycarp Hoole ◽

Nur Farah Aziz ◽

Velappa Ganapathy ◽

Kanesan Jeevan ◽

Ramiah Harikrishnan ◽

...

Keyword(s):

Neural Network ◽

Electrical Activity ◽

Electric Fields ◽

Array Antenna ◽

Lightning Activity ◽

Electronic Systems ◽

Distance Range ◽

The Neural Network ◽

Unique Shape ◽

Element Array

Abstract. Cloud to ground and cloud to cloud lightning flashes pose a threat to the aircraft body and the electronic systems inside the aircraft. In this paper we present a single unit, as opposed to a three unit, lightning locator mounted on the aircraft that uses the wave-shapes of electromagnetic fields radiated by lightning and electrical activity ahead of the aircraft to locate the distance range of lightning activity. A three element array antenna scans the area ahead of the aircraft to narrow down the area ahead where the lightning or threatening electrical activity is. Moreover, the unique shape of the electric fields depending on the distance from the lightning activity is used by a neural network to train and recognize the distance range of the lightning activity from the aircraft on which the lightning detector is mounted. The combined use of the three element array antenna and the neural network provides the required knowledge of lightning activity for the pilot to take evasive action.

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Analysis of the Evolution of a Meiyu Frontal Rainstorm Based on Doppler Radar Data Assimilation

10.5194/egusphere-egu2020-1975 ◽

2020 ◽

Author(s):

Hongli Li ◽

Yang Hu ◽

Zhimin Zhou

Keyword(s):

Heavy Rainfall ◽

Doppler Radar ◽

Heavy Precipitation ◽

Radar Data ◽

Economic Losses ◽

Mature Stage ◽

Convective System ◽

Low Level ◽

Sufficient Energy ◽

Study Results

During the Meiyu period, floods are prone to occur in the middle and lower reaches of the Yangtze River due to the highly concentrated and heavy rainfall, which caused huge life and economic losses. Based on numerical simulation by assimilating Doppler radar, radiosonde, and surface meteorological observations, the evolution mechanism for the initiation, development and decaying of a Meiyu frontal rainstorm that occurred from 4th to 5th July 2014 is analyzed in this study. Results show that the numerical experiment can well reproduce the temporal variability of heavy precipitation and successfully simulate accumulative precipitation and its evolution over the key rainstorm area. The simulated &#8220;rainbelt training&#8221; is consistent with observed &#8220;echo training&#8221; on both spatial structure and temporal evolution. The convective cells in the mesoscale convective belt propagated from southwest to northeast across the key rainstorm area, leading to large accumulative precipitation and rainstorm in this area. There existed convective instability in lower levels above the key rainstorm area, while strong ascending motion developed during period of heavy rainfall. Combined with abundant water vapor supply, the above condition was favorable for the formation and development of heavy rainfall. The Low level jet (LLJ) provided sufficient energy for the rainstorm system, and the low-level convergence intensified, which was an important reason for the maintenance of precipitation system and its eventual intensification to rainstorm. At its mature stage, the rainstorm system demonstrated vertically tilted structure with strong ascending motion in the key rainstorm area, which was favorable for the occurrence of heavy rainfall. In the decaying stage, unstable energy decreased, and the rainstorm no longer had sufficient energy to sustain. The rapid weakening of LLJ resulted in smaller energy supply to the convective system, and the stratification tended to be stable in the middle and lower levels. The ascending motion weakened correspondingly, which made it hard for the convective system to maintain.

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