Volcanic ash retrieval at Mt. Etna using AVHRR and MODIS data

Spinetti, Claudia; Corradini, Stefano; Buongiorno, M. F.

doi:10.1117/12.752664

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…This algorithm is suitable for detecting volcanic aerosol, especially small‐sized aerosol, whereas coarser volcanic ash is commonly detected using the brightness temperature difference technique [ Prata , ; Wen and Rose , ; Spinetti et al ., ; Corradini et al ., ]. Another retrieval technique is based on a UV volcanic ash algorithm that is sensitive to both fine and coarse ash particles [ Krotkov et al , ].…”

Section: Methodology and Techniquesmentioning

confidence: 99%

Investigation of the complex dynamics and structure of the 2010 Eyjafjallajökull volcanic ash cloud using multispectral images and numerical simulations

et al. 2013

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[1] We investigated the structure and evolution of the 2010 Eyjafjallajökull volcanic cloud and its dispersal over Iceland and Europe integrating satellite multispectral images and numerical simulations. Data acquired by Medium Resolution Imaging Spectrometer (MERIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) have been analyzed to quantify the cloud extent and composition. The VOL-CALPUFF dispersal code was applied to reconstruct the transient and 3-D evolution of the cloud. Source parameters estimated on the base of available a posteriori volcanological data sets have been used. Quantitative comparisons between satellite retrievals and modeling results were performed for two selected instants of time during the first and third eruptive phases on a regional scale. Sensitivity of the model to initial volcanological conditions has been analyzed at continental scale. Several complex non intuitive features of cloud dynamics have been highlighted and strengths and limitations of the adopted methods identified. The main findings are: the level of quantitative agreement between satellite observations and numerical results depends on ash cloud composition (particle sizes and concentration) with better agreement for smaller particles and higher concentrations; the agreement between observations and modeling outcomes also depends on the temporal stability of volcanological conditions and the complexity of the meteorological wind field; the irregular dispersion of ash, as reconstructed from satellite data and numerical modeling, can be well explained by the different response of particle sizes to strong vertical wind-shear, and by resuspension processes acting at ground level; eruptive source conditions are the main source of uncertainty in modeling, especially during an ongoing crisis and at long-range scales.

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Section: Methodology and Techniquesmentioning

confidence: 99%

Investigation of the complex dynamics and structure of the 2010 Eyjafjallajökull volcanic ash cloud using multispectral images and numerical simulations

et al. 2013

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“…The analysis presented in this work has been performed for dispersal conditions representative of the event of 24 November 2006, at Mount Etna, Italy (Figure 1). According to Spinetti et al [2007] and Andronico et al [2014], this eruption took place at the Southeast Crater, one of Mount Etna's summit craters, and it represented the most voluminous episode, in terms of mass of ash emitted, that occurred in 2006. This episode has been subdivided by Andronico et al [2014] into three main eruption phases: resumption, paroxysmal, and conclusive.…”

Section: The Mount Etna Reference Eventmentioning

confidence: 99%

Grain size distribution uncertainty quantification in volcanic ash dispersal and deposition from weak plumes

et al. 2016

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We present the results of uncertainty quantification and sensitivity analysis applied to volcanic ash dispersal from weak plumes with focus on the uncertainties associated to the original grain size distribution of the mixture. The Lagrangian particle model Lagrangian Particles Advection Code is used to simulate the transport of inertial particles under the action of realistic atmospheric conditions. The particle motion equations are derived by expressing the particle acceleration as the sum of forces acting along its trajectory, with the drag force calculated as a function of particle diameter, density, shape, and Reynolds number. Simulations are representative of a weak plume event of Mount Etna (Italy) and aimed at quantifying the effect on the dispersal process of the uncertainty in the mean and standard deviation of a lognormal function describing the initial grain size distribution and in particle sphericity. In order to analyze the sensitivity of particle dispersal to these uncertain variables with a reasonable number of simulations, response surfaces in the parameter space are built by using the generalized polynomial chaos expansion technique. The mean diameter and standard deviation of particle size distribution, and their probability density functions, at various distances from the source, both airborne and on ground, are quantified. Results highlight that uncertainty ranges in these quantities are drastically reduced with distance from source, making them largely dependent just on the location. Moreover, at a given distance from source, the distribution is mostly controlled by particle sphericity, particularly on the ground, whereas in air also mean diameter and sorting play a main role.

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“…This is because volcanic ash contains large amounts of silicates that scatter and absorb infrared radiation in a different way than meteorological water and ice clouds in [20]. A BTD of 11-12 μm is generally negative for volcanic ash and dust and positive for ice and water clouds [11,20,21]. Bands 31 (11 μm) and 32 (12 μm) of MODIS data were used for volcanic ash monitoring in this study.…”

Section: Methodology For Volcanic Ash Trackingmentioning

confidence: 99%

Monitoring of the 2008 Chaitén Eruption Cloud Using MODIS Data and its Impacts

Zhang¹,

Tsou²,

Huang³

et al. 2016

Geospatial Technology - Environmental and Social Applications

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This chapter presents the monitoring of the 2008 Chaitén eruption cloud using Moderate Resolution Imaging Spectroradiometer (MODIS) data and its impacts. The 8-day MODIS data from 3 to 10 May 2008 were used to track the movement and dispersion of the eruption cloud of the Chaitén volcano in Chile following the eruption on 2 May 2008. For detecting volcanic particulates, the procedure is adopted based on the brightness temperature difference (BTD) algorithm, by which the thermal infrared channels were centered on 11-12 μm of multispectral satellite sensors. The BTD is generally negative for volcanic ash but positive for ice and water vapor. The eruption cloud was found to drift northeastward, eastward, and southeastward crossing the central and northern part of Argentina and over the Atlantic Ocean. The timing of heavy rainfall in South Africa during May-June, in central Australia during June 2008 and in Hong Kong during June (the wettest since record began in 1884), was considered to have been connected to the dispersion of the particulates from this Chaitén eruption to further impact downstream.

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Volcanic ash retrieval at Mt. Etna using AVHRR and MODIS data

Cited by 6 publications

References 7 publications

Investigation of the complex dynamics and structure of the 2010 Eyjafjallajökull volcanic ash cloud using multispectral images and numerical simulations

Investigation of the complex dynamics and structure of the 2010 Eyjafjallajökull volcanic ash cloud using multispectral images and numerical simulations

Grain size distribution uncertainty quantification in volcanic ash dispersal and deposition from weak plumes

Monitoring of the 2008 Chaitén Eruption Cloud Using MODIS Data and its Impacts

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