966 resultados para lightning strike


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The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18% respectively compared to LPX.

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Lightning flash rates, RL, are modulated by corotating interaction regions (CIRs) and the polarity of the heliospheric magnetic field (HMF) in near-Earth space. As the HMF polarity reverses at the heliospheric current sheet (HCS), typically within a CIR, these phenomena are likely related. In this study, RL is found to be significantly enhanced at the HCS and at 27 days prior/after. The strength of the enhancement depends on the polarity of the HMF reversal at the HCS. Near-Earth solar and galactic energetic particle fluxes are also ordered by HMF polarity, though the variations qualitatively differ from RL, with the main increase occurring prior to the HCS crossing. Thus, the CIR effect on lightning is either the result of compression/amplification of the HMF (and its subsequent interaction with the terrestrial system) or that energetic particle preconditioning of the Earth system prior to the HMF polarity change is central to solar wind lightning coupling mechanism.

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Sprites have been detected in video camera observations from Niger over mesoscale convective systems in Nigeria during the 2006 AMMA (African Monsoon Multidisciplinary Analysis) campaign The parent lightning flashes have been detected by multiple Extremely Low Frequency (ELF) receiving stations worldwide The recorded charge moments of the patent lightning flashes are often in excellent agreement between different receiving sites, and are furthermore consistent with conventional dielectric breakdown in the mesosphere as the origin of the sprites Analysis of the polarization of the horizontal magnetic field at the distant receivers provides evidence that the departure from linear magnetic polarization at ELF is caused primarily by the clay night asymmetry of the Earth-ionosphere cavity Copyright (C) 2009 Royal Meteorological Society

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Games are known for leveraging enthusiasm, engagement, energy, knowledge, and passion on gamers; areas that are fundamentally important in higher education. Our panelists will share their perspectives on how Higher Education can take advantage of the potential of game based learning to create a more engaging student learning experien

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"Design proposals for an outdoor 'exhibit' on the Shores of Narragansett Bay".

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This gaper demonstrates that artificial neural networks can be used effectively for estimation of parameters related to study of atmospheric conditions to high voltage substations design. Specifically, the neural networks are used to compute the variation of electrical field intensity and critical disruptive voltage in substations taking into account several atmospheric factors, such as pressure, temperature, humidity, so on. Examples of simulation of tests are presented to validate the proposed approach. The results that were obtained by experimental evidences and numerical simulations allowed the verification of the influence of the atmospheric conditions on design of substations concerning lightning.

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This paper describes a novel approach for mapping lightning processes using fuzzy logic. The estimation process is carried out using a fuzzy system based on Sugeno's architecture. Simulation results confirm that proposed approach can be efficiently used in these types of problem.

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This paper proposes the application of computational intelligence techniques to assist complex problems concerning lightning in transformers. In order to estimate the currents related to lightning in a transformer, a neural tool is presented. ATP has generated the training vectors. The input variables used in Artificial Neural Networks (ANN) were the wave front time, the wave tail time, the voltage variation rate and the output variable is the maximum current in the secondary of the transformer. These parameters can define the behavior and severity of lightning. Based on these concepts and from the results obtained, it can be verified that the overvoltages at the secondary of transformer are also affected by the discharge waveform in a similar way to the primary side. By using the tool developed, the high voltage process in the distribution transformers can be mapped and estimated with more precision aiding the transformer project process, minimizing empirics and evaluation errors, and contributing to minimize the failure rate of transformers. (C) 2011 Elsevier Ltd. All rights reserved.

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This work analyses the waveshapes of continuing currents and parameters of M-components in positive cloud-to-ground (CG) flashes through high-speed GPS synchronized videos. The dataset is composed of only long continuing currents (with duration longer than 40 ms) and was selected from more than 800 flashes recorded in Sao Jose dos Campos (45.864 degrees W, 23.215 degrees S) and Uruguaiana (29.806 degrees W, 57.005 degrees S) in Southeast and South of Brazil, respectively, during 2003 to 2007 summers. The videos are compared with data obtained by the Brazilian Lightning Location System (BrasilDAT) in order to determine the polarity of each flash and select only positive cases. There are only two studies of waveshapes of continuing currents in the literature. One is based on direct current measurements of triggered lightning, in which four different types of waveshapes were observed; and the other is based on measurements of luminosity variations in high-speed videos of CG negative lightning, in which besides the four types above mentioned two additional types were observed. The present work is an extension of the latter, using the same method but now applied to obtain the waveshapes of positive CG lightning. As far as the authors know, this is the first report on M-components in positive continuing currents. We also have used the luminosity-versus-time graphs to observe their occurrence and measure some parameters (duration, elapsed time and time between two successive M-components), whose statistics are presented and compared in detail to the data for negative flashes. We have plotted a histogram of the M-components elapsed time over the total duration of the continuing current for positive flashes, which presented an exponential decay (correlation coefficient: 0.83), similar to what has been observed for negative flashes. (C) 2008 Elsevier B.V. All rights reserved.

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This paper describes a novel approach for mapping lightning processes using fuzzy logic. The core regarding lightning process is to identify and to model those uncertain information on mathematical principles. In fact, the lightning process involves several nonlinear features that our current mathematical tools would not be able to model. The estimation process has been carried out using a fuzzy system based on Sugeno's architecture. Simulation results confirm that proposed approach can be efficiently used in these types of problem.

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During the TROCCINOX field experiment in January and February 2005, the contribution of lightning-induced nitrogen oxides (LNOx) from tropical and subtropical thunderstorms in Southern Brazil was investigated. Airborne trace gas measurements (NO, NOy, CO and O-3) were performed up to 12.5 km with the German research aircraft Falcon. During anvil penetrations in selected tropical and subtropical thunderstorms of 4 and 18 February, NOx mixing ratios were on average enhanced by 0.7-1.2 and 0.2-0.8 nmol mol(-1) totally, respectively. The relative contributions of boundary layer NOx (BL-NOx) and LNOx to anvil-NOx were derived from the NOx-CO correlations. on average similar to 80-90% of the anvil-NOx was attributed to LNOx. A Lightning Location Network (LINET) was set up to monitor the local distribution of cloud-to-ground (CG) and intra-cloud (IC) radiation sources (here called 'strokes') and compared with lightning data from the operational Brazilian network RINDAT (Rede Integrada Nacional de Deteccao de Descargas Atmosfericas). The horizontal LNOx mass flux out of the anvil was determined from the mean LNOx mixing ratio, the horizontal outflow velocity and the size of the vertical cross-section of the anvil, and related to the number of strokes contributing to LNOx. The values of these parameters were derived from the airborne measurements, from lightning and radar observations, and from a trajectory analysis. The amount of LNOx produced per LINET stroke depending on measured peak current was determined. The results were scaled up with the Lightning Imaging Sensor (LIS) flash rate (44 flashes s(-1)) to obtain an estimate of the global LNOx production rate. The final results gave similar to 1 and similar to 2-3 kg(N) per LIS flash based on measurements in three tropical and one subtropical Brazilian thunderstorms, respectively, suggesting that tropical flashes may be less productive than subtropical ones. The equivalent mean annual global LNOx nitrogen mass production rate was estimated to be 1.6 and 3.1 Tg a(-1), respectively. By use of LINET observations in Germany in July 2005, a comparison with the lightning activity in mid-latitude thunderstorms was also performed. In general, the same frequency distribution of stroke peak currents as for tropical thunderstorms over Brazil was found. The different LNOx production rates per stroke in tropical thunderstorms compared with subtropical and mid-latitude thunderstorms seem to be related to the different stroke lengths (inferred from comparison with laboratory data and observed lengths). In comparison, the impact of other lightning parameters as stroke peak current and stroke release height was assessed to be minor. The results from TROCCINOX suggest that the different vertical wind shear may be responsible for the different stroke lengths.

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This paper describes lightning characteristics as obtained in four sets of lightning measurements during recent field campaigns in different parts of the world from mid-latitudes to the tropics by the novel VLF/LF (very low frequency/low frequency) lightning detection network (LINET). The paper gives a general overview on the approach, and a synopsis of the statistical results for the observation periods as a whole and for one special day in each region. The focus is on the characteristics of lightning which can specifically be observed by this system like intra-cloud and cloud-to-ground stroke statistics, vertical distributions of intra-cloud strokes or peak current distributions. Some conclusions regarding lightning produced NOx are also presented as this was one of the aims of the tropical field campaigns TROCCINOX (Tropical Convection, Cirrus and Nitrogen Oxides Experiment) and TroCCiBras (Tropical Convection and Cirrus Experiment Brazil) in Brazil during January/February 2005, SCOUT-O3 (Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere) and TWP-ICE (Tropical Warm Pool-International Cloud Experiment) during November/December 2005 and January/February 2006, respectively, in the Darwin area in N-Australia, and of AMMA (African Monsoon Multidisciplinary Analyses) in W-Africa during June-November 2006.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.