984 resultados para volcanic ash


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The requirement to forecast volcanic ash concentrations was amplified as a response to the 2010 Eyjafjallajökull eruption when ash safety limits for aviation were introduced in the European area. The ability to provide accurate quantitative forecasts relies to a large extent on the source term which is the emissions of ash as a function of time and height. This study presents source term estimations of the ash emissions from the Eyjafjallajökull eruption derived with an inversion algorithm which constrains modeled ash emissions with satellite observations of volcanic ash. The algorithm is tested with input from two different dispersion models, run on three different meteorological input data sets. The results are robust to which dispersion model and meteorological data are used. Modeled ash concentrations are compared quantitatively to independent measurements from three different research aircraft and one surface measurement station. These comparisons show that the models perform reasonably well in simulating the ash concentrations, and simulations using the source term obtained from the inversion are in overall better agreement with the observations (rank correlation = 0.55, Figure of Merit in Time (FMT) = 25–46%) than simulations using simplified source terms (rank correlation = 0.21, FMT = 20–35%). The vertical structures of the modeled ash clouds mostly agree with lidar observations, and the modeled ash particle size distributions agree reasonably well with observed size distributions. There are occasionally large differences between simulations but the model mean usually outperforms any individual model. The results emphasize the benefits of using an ensemble-based forecast for improved quantification of uncertainties in future ash crises.

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1] We apply a novel computational approach to assess, for the first time, volcanic ash dispersal during the Campanian Ignimbrite (Italy) super-eruption providing insights into eruption dynamics and the impact of this gigantic event. The method uses a 3D time-dependent computational ash dispersion model, a set of wind fields, and more than 100 thickness measurements of the CI tephra deposit. Results reveal that the CI eruption dispersed 250–300 km3 of ash over ∼3.7 million km2. The injection of such a large quantity of ash (and volatiles) into the atmosphere would have caused a volcanic winter during the Heinrich Event 4, the coldest and driest climatic episode of the Last Glacial period. Fluorine-bearing leachate from the volcanic ash and acid rain would have further affected food sources and severely impacted Late Middle-Early Upper Paleolithic groups in Southern and Eastern Europe

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The plume from the 2011 eruption of Grímsvötn was highly electrically charged, as shown by the considerable lightning activity measured by the United Kingdom Met Office’s low-frequency lightning detection network. Previous measurements of volcanic plumes have shown that ash particles are electrically charged up to hundreds of kilometers away from the vent, which indicates that the ash continues to charge in the plume [R. G. Harrison, K. A. Nicoll, Z. Ulanowski, and T. A. Mather, Environ. Res. Lett. 5 024004 (2010); H. Hatakeyama J. Meteorol. Soc. Jpn. 27 372 (1949)]. In this Letter, we study triboelectric charging of different size fractions of a sample of volcanic ash experimentally. Consistently with previous work, we find that the particle size distribution is a determining factor in the charging. Specifically, our laboratory experiments demonstrate that the normalized span of the particle size distribution plays an important role in the magnitude of charging generated. The influence of the normalized span on plume charging suggests that all ash plumes are likely to be charged, with implications for remote sensing and plume lifetime through scavenging effects.

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The Eyjafjallajökull volcano in Iceland emitted a cloud of ash into the atmosphere during April and May 2010. Over the UK the ash cloud was observed by the FAAM BAe-146 Atmospheric Research Aircraft which was equipped with in-situ probes measuring the concentration of volcanic ash carried by particles of varying sizes. The UK Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME) has been used to simulate the evolution of the ash cloud emitted by the Eyjafjallajökull volcano during the period 4–18 May 2010. In the NAME simulations the processes controlling the evolution of the concentration and particle size distribution include sedimentation and deposition of particles, horizontal dispersion and vertical wind shear. For travel times between 24 and 72 h, a 1/t relationship describes the evolution of the concentration at the centre of the ash cloud and the particle size distribution remains fairly constant. Although NAME does not represent the effects of microphysical processes, it can capture the observed decrease in concentration with travel time in this period. This suggests that, for this eruption, microphysical processes play a small role in determining the evolution of the distal ash cloud. Quantitative comparison with observations shows that NAME can simulate the observed column-integrated mass if around 4% of the total emitted mass is assumed to be transported as far as the UK by small particles (< 30 μm diameter). NAME can also simulate the observed particle size distribution if a distal particle size distribution that contains a large fraction of < 10 μm diameter particles is used, consistent with the idea that phraetomagmatic volcanoes, such as Eyjafjallajökull, emit very fine particles.

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The long duration of the 2010 Eyjafjallajökull eruption provided a unique opportunity to measure a widely dispersed volcanic ash cloud. Layers of volcanic ash were observed by the European Aerosol Research Lidar Network with a mean depth of 1.2 km and standard deviation of 0.9 km. In this paper we evaluate the ability of the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) to simulate the observed ash layers and examine the processes controlling their depth. NAME simulates distal ash layer depths exceptionally well with a mean depth of 1.2 km and standard deviation of 0.7 km. The dominant process determining the depth of ash layers over Europe is the balance between the vertical wind shear (which acts to reduce the depth of the ash layers) and vertical turbulent mixing (which acts to deepen the layers). Interestingly, differential sedimentation of ash particles and the volcano vertical emission profile play relatively minor roles.

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The decision to close airspace in the event of a volcanic eruption is based on hazard maps of predicted ash extent. These are produced using output from volcanic ash transport and dispersion (VATD)models. In this paper an objectivemetric to evaluate the spatial accuracy of VATD simulations relative to satellite retrievals of volcanic ash is presented. The 5 metric is based on the fractions skill score (FSS). Thismeasure of skill provides more information than traditional point-bypoint metrics, such as success index and Pearson correlation coefficient, as it takes into the account spatial scale overwhich skill is being assessed. The FSS determines the scale overwhich a simulation has skill and can differentiate between a "near miss" and a forecast that is badly misplaced. The 10 idealised scenarios presented show that even simulations with considerable displacement errors have useful skill when evaluated over neighbourhood scales of 200–700km2. This method could be used to compare forecasts produced by different VATDs or using different model parameters, assess the impact of assimilating satellite retrieved ash data and evaluate VATD forecasts over a long time period.

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A data insertion method, where a dispersion model is initialized from ash properties derived from a series of satellite observations, is used to model the 8 May 2010 Eyjafjallajökull volcanic ash cloud which extended from Iceland to northern Spain. We also briefly discuss the application of this method to the April 2010 phase of the Eyjafjallajökull eruption and the May 2011 Grímsvötn eruption. An advantage of this method is that very little knowledge about the eruption itself is required because some of the usual eruption source parameters are not used. The method may therefore be useful for remote volcanoes where good satellite observations of the erupted material are available, but little is known about the properties of the actual eruption. It does, however, have a number of limitations related to the quality and availability of the observations. We demonstrate that, using certain configurations, the data insertion method is able to capture the structure of a thin filament of ash extending over northern Spain that is not fully captured by other modeling methods. It also verifies well against the satellite observations according to the quantitative object-based quality metric, SAL—structure, amplitude, location, and the spatial coverage metric, Figure of Merit in Space.

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In the event of a volcanic eruption the decision to close airspace is based on forecast ash maps, produced using volcanic ash transport and dispersion models. In this paper we quantitatively evaluate the spatial skill of volcanic ash simulations using satellite retrievals of ash from the Eyja allajökull eruption during the period from 7 to 16 May 2010. We find that at the start of this period, 7–10 May, the model (FLEXible PARTicle) has excellent skill and can predict the spatial distribution of the satellite-retrieved ash to within 0.5∘ × 0.5∘ latitude/longitude. However, on 10 May there is a decrease in the spatial accuracy of the model to 2.5∘× 2.5∘ latitude/longitude, and between 11 and 12 May the simulated ash location errors grow rapidly. On 11 May ash is located close to a bifurcation point in the atmosphere, resulting in a rapid divergence in the modeled and satellite ash locations. In general, the model skill reduces as the residence time of ash increases. However, the error growth is not always steady. Rapid increases in error growth are linked to key points in the ash trajectories. Ensemble modeling using perturbed meteorological data would help to represent this uncertainty, and assimilation of satellite ash data would help to reduce uncertainty in volcanic ash forecasts.

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Air-fall volcanic ash recovered at Deep Sea Drilling Project Sites 541, 542, and 543 on and east of the toe of the Barbados Ridge delineate middle and late Miocene, early Pliocene, and Pleistocene-Quaternary pulses of explosive volcanism in the Lesser Antilles arc. The ash beds at Site 541 allow precise correlation of intervals repeated by a probable reverse fault at this convergent margin.

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In this study of volcanic ash retrieved from Shatsky Rise during Ocean Drilling Program Leg 198, the texture and composition of the volcanic components (glass and crystals) were used to fingerprint ash layers for detailed correlation. Correlations among ash layers in holes drilled at the same site as well as between sites, including sites on different parts (highs) of the rise, were tested. Although high-to-high correlations failed, intrahigh correlations were more successful. Our data suggest a significantly different source for some pyroclastic debris, especially at Site 1208, possibly associated with pumice rafts carried northward from the Izu-Bonin arc by the Kuroshio Current. Other ashes are consistent with rhyolitic to dacitic air fall ash from Asian arc volcanoes. We were not able to texturally distinguish between air fall ash and pumice-raft fallout but suspect that the latter is associated with higher percentages of vesiculated ash components, as we demonstrate occur in more proximal Izu-Bonin pyroclastic deposits.

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