scholarly journals Operational Response to Volcanic Ash Risks Using HOTVOLC Satellite-Based System and MOCAGE-Accident Model at the Toulouse VAAC

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 864
Author(s):  
Mathieu Gouhier ◽  
Mathieu Deslandes ◽  
Yannick Guéhenneux ◽  
Philippe Hereil ◽  
Philippe Cacault ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Source Parameters ◽  
Vertical Column ◽  
Cloud Properties ◽  
Eruptive Column ◽  
Operational Management ◽  
Remote Sensing Techniques ◽  
Ash Cloud

In 2010, the Eyjafjallajökull volcano erupted, generating an ash cloud causing unprecedented disruption of European airspace. Despite an exceptional situation, both the London and Toulouse Volcanic Ash Advisory Centres (VAAC) provided critical information on the location of the cloud and on the concentration of ash, thus contributing to the crisis management. Since then, substantial efforts have been carried out by the scientific community in order to improve remote sensing techniques and numerical modeling. Satellite instruments have proven to be particularly relevant for the characterization of ash cloud properties and a great help in the operational management of volcanic risk. In this study, we present the satellite-based system HOTVOLC developed at the Observatoire de Physique du Globe de Clermont-Ferrand (OPGC) using Meteosat geostationary satellite and designed for real-time monitoring of active volcanoes. After a brief presentation of the system we provide details on newly developed satellite products dedicated to the ash cloud characterization. This includes, in particular, ash cloud altitude and vertical column densities (VCD). Then, from the Stromboli 2018 paroxysm, we show how HOTVOLC can be used in a timely manner to assist the Toulouse VAAC in the operational management of the eruptive crisis. In the second part of the study, we provide parametric tests of the MOCAGE-Accident model run by the Toulouse VAAC from the April 17 Eyjafjallajökull eruption. For this purpose, we tested a range of eruption source parameters including the Total Grain Size Distribution (TGSD), the eruptive column profile, the top plume height and mass eruption rate (MER), as well as the fine ash partitioning. Finally, we make a comparison on this case study between HOTVOLC and MOCAGE-Accident VCD.

Integration of Satellite Remote Sensing Techniques and Landscape Metrics to Characterize Land Cover Change and Dynamics

2013 ◽  
pp. 228-244
Author(s):  
Carmelo Riccardo Fichera ◽  
Giuseppe Modica ◽  
Maurizio Pollino
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Landscape Metrics ◽  
Landsat Images ◽  
Aerial Photos ◽  
Multi Temporal ◽  
Urban Rural ◽  
Remote Sensing Techniques

One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.

scholarly journals Volcanic ash modeling with the NMMB-MONARCH-ASH model: quantification of offline modeling errors

2018 ◽  
Vol 18 (6) ◽  
pp. 4019-4038 ◽  
Author(s):  
Alejandro Marti ◽  
Arnau Folch
Keyword(s):  
Volcanic Ash ◽  
Source Parameters ◽  
Atmospheric Dispersion ◽  
Volcanic Eruptions ◽  
Systematic Errors ◽  
Cloud Detection ◽  
Coupled Modeling ◽  
Evaluation Scores ◽  
Modeling Systems ◽  
Ash Cloud

Abstract. Volcanic ash modeling systems are used to simulate the atmospheric dispersion of volcanic ash and to generate forecasts that quantify the impacts from volcanic eruptions on infrastructures, air quality, aviation, and climate. The efficiency of response and mitigation actions is directly associated with the accuracy of the volcanic ash cloud detection and modeling systems. Operational forecasts build on offline coupled modeling systems in which meteorological variables are updated at the specified coupling intervals. Despite the concerns from other communities regarding the accuracy of this strategy, the quantification of the systematic errors and shortcomings associated with the offline modeling systems has received no attention. This paper employs the NMMB-MONARCH-ASH model to quantify these errors by employing different quantitative and categorical evaluation scores. The skills of the offline coupling strategy are compared against those from an online forecast considered to be the best estimate of the true outcome. Case studies are considered for a synthetic eruption with constant eruption source parameters and for two historical events, which suitably illustrate the severe aviation disruptive effects of European (2010 Eyjafjallajökull) and South American (2011 Cordón Caulle) volcanic eruptions. Evaluation scores indicate that systematic errors due to the offline modeling are of the same order of magnitude as those associated with the source term uncertainties. In particular, traditional offline forecasts employed in operational model setups can result in significant uncertainties, failing to reproduce, in the worst cases, up to 45–70 % of the ash cloud of an online forecast. These inconsistencies are anticipated to be even more relevant in scenarios in which the meteorological conditions change rapidly in time. The outcome of this paper encourages operational groups responsible for real-time advisories for aviation to consider employing computationally efficient online dispersal models.

scholarly journals Atmospheric Dispersion Modelling at the London VAAC: A Review of Developments since the 2010 Eyjafjallajökull Volcano Ash Cloud

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 352 ◽  
Author(s):  
Frances M. Beckett ◽  
Claire S. Witham ◽  
Susan J. Leadbetter ◽  
Ric Crocker ◽  
Helen N. Webster ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Dispersion Model ◽  
Source Parameters ◽  
Atmospheric Dispersion ◽  
Lessons Learned ◽  
Dispersion Modelling ◽  
Atmospheric Dispersion Modelling ◽  
Volcanic Ash Cloud ◽  
Atmospheric Dispersion Model ◽  
Ash Cloud

It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused unprecedented disruption to air traffic across Europe. During this event, the London Volcanic Ash Advisory Centre (VAAC) provided advice and guidance on the expected location of volcanic ash in the atmosphere using observations and the atmospheric dispersion model NAME (Numerical Atmospheric-Dispersion Modelling Environment). Rapid changes in regulatory response and procedures during the eruption introduced the requirement to also provide forecasts of ash concentrations, representing a step-change in the level of interrogation of the dispersion model output. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. We present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned. Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep moist atmospheric convection and parametrizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Finally, upper air wind field data used by the dispersion model is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event.

scholarly journals Volcanic ash forecast using ensemble-based data assimilation: the Ensemble Transform Kalman Filter coupled with FALL3D-7.2 model (ETKF-FALL3D, version 1.0)

2019 ◽  
Author(s):  
Soledad Osores ◽  
Juan Ruiz ◽  
Arnau Folch ◽  
Estela Collini
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Volcanic Ash ◽  
Source Parameters ◽  
Joint Estimation ◽  
Volcanic Ash Cloud ◽  
Ensemble Transform Kalman Filter ◽  
Ensemble Transform ◽  
Ash Cloud ◽  
Ash Dispersal

Abstract. Quantitative volcanic ash cloud forecasts are prone to uncertainties coming from the source term quantification (e.g. eruption strength or vertical distribution of the emitted particles), with consequent implications on operational ash impact assessment. We present an ensemble-based data assimilation and forecast system for volcanic ash dispersal and deposition aimed at reducing uncertainties related to eruption source parameters. The FALL3D atmospheric dispersal model is coupled with the Ensemble Transform Kalman Filter (ETKF) data assimilation technique by combining ash mass loading observations with ash dispersal simulations in order to obtain a better joint estimation of 3D ash concentration and source parameters. The ETKF-FALL3D data assimilation system is evaluated performing Observation System Simulation Experiments (OSSE) in which synthetic observations of fine ash mass loadings are assimilated. The evaluation of the ETKF-FALL3D system considering reference states of steady and time-varying eruption source parameters shows that the assimilation process gives both better estimations of ash concentration and time-dependent optimized values of eruption source parameters. The joint estimation of concentrations and source parameters leads to a better analysis and forecast of the 3D ash concentrations. Results show the potential of the methodology to improve volcanic ash cloud forecasts in operational contexts.

scholarly journals Volcanic ash detection and retrievals from MODIS data by means of Neural Networks

2011 ◽  
Vol 4 (3) ◽  
pp. 2567-2598 ◽  
Author(s):  
M. Picchiani ◽  
M. Chini ◽  
S. Corradini ◽  
L. Merucci ◽  
P. Sellitto ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Confusion Matrix ◽  
Classification Problem ◽  
Cloud Detection ◽  
Cloud Properties ◽  
Mandatory Requirement ◽  
Mt Etna ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Time Basis ◽  
Ash Cloud

Abstract. Volcanic ash clouds detection and retrieval represent a key issue for the aviation safety due to the harming effects they can provoke on aircrafts. A lesson learned from the recent Icelandic Eyjafjalla volcano eruption is the need to obtain accurate and reliable retrievals on a real time basis. The current most widely adopted procedures for ash detection and retrieval are based on the Brightness Temperature Difference (BTD) inversion observed at 11 and 12 μm that allows volcanic and meteo clouds discrimination. While ash cloud detection can be readily obtained, a reliable quantitative ash cloud retrieval can be so time consuming to prevent its utilization during the crisis phase. In this work a fast and accurate Neural Network (NN) approach to detect and retrieve volcanic ash cloud properties has been developed using multispectral IR measurements collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) over Mt. Etna volcano during 2001, 2002 and 2006 eruptive events. The procedure consists in two separate steps: the ash detection and ash mass retrieval. The detection is reduced to a classification problem by identifying two classes of "ashy" and "non-ashy" pixels in the MODIS images. Then the ash mass is estimated by means of the NN, replicating the BTD-based model performances. The results obtained from the entire procedure are very encouraging; indeed the confusion matrix for the test set has an accuracy greater than 90 %. Both ash detection and retrieval show a good agreement when compared to the results achieved by the BTD-based procedure. Moreover, the NN procedure is so fast to be extremely attractive in all the cases when the quick response time of the system is a mandatory requirement.

A multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions

2009 ◽  
Vol 186 (1-2) ◽  
pp. 10-21 ◽  
Author(s):  
L.G. Mastin ◽  
M. Guffanti ◽  
R. Servranckx ◽  
P. Webley ◽  
S. Barsotti ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Source Parameters ◽  
Volcanic Ash Cloud ◽  
Ash Cloud

CASE STUDY OF THE FIRST VOLCANIC ASH EXERCISE IN ROMANIA USING REMOTE SENSING TECHNIQUES

2015 ◽  
Vol 14 (11) ◽  
pp. 2503-2514 ◽  
Author(s):  
Marius Mihai Cazacu ◽  
Livio Belegante ◽  
Adrian Timofte ◽  
Florica Toanca ◽  
Jeni Vasilescu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Volcanic Ash ◽  
Remote Sensing Techniques

Seismo-acoustic characterization of the 2019 Stromboli volcano paroxysm events

2021 ◽  
Author(s):  
Alexis Le Pichon ◽  
Emanuele Marchetti ◽  
Christoph Pilger ◽  
Lars Ceranna ◽  
Viviane Souty ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Civil Aviation ◽  
Stromboli Volcano ◽  
Efficient Tool ◽  
Propagation Modeling ◽  
Volcanic Source ◽  
Acoustic Characterization ◽  
Eruptive Column ◽  
International Monitoring

<p>Stromboli volcano is well known for its persistent explosive activity, with hundreds of explosions every day ejecting ash and scoria up to heights of several tens/few hundreds of meters. Such a mild activity is however punctuated by lava flows and major/paroxysmal explosions, that represent a much larger hazard. On July 3rd and August 28th 2019, two paroxysmal explosions occurred at Stromboli, generating an eruptive column that quickly raised up to 5 km above the sea level. The Toulouse Volcanic Ash Advisory Center (VAAC) emitted an advisory to the civil aviation with a two-hour delay. The various processes of this event were monitored near and far field by infrasonic arrays up to distance of 3,500 km and by the Italian national seismic network at range of hundreds of kilometres. Using state-of-the-art propagation modeling, we aim at identifying the various seismic and infrasound phases of the event to better characterize the volcanic source. We highlight the need for the integration of the global infrasound International Monitoring System (IMS) network with local and regional infrasound arrays capable of providing a timely early warning to VAACs. This study opens new perspectives in volcano monitoring for hazard assessment and could represent, in the future, an efficient tool in supporting VAACs activity.</p>

scholarly journals The RAMNI airborne lidar for cloud and aerosol research

2012 ◽  
Vol 5 (7) ◽  
pp. 1779-1792 ◽  
Author(s):  
F. Cairo ◽  
G. Di Donfrancesco ◽  
L. Di Liberto ◽  
M. Viterbini
Keyword(s):  
Volcanic Ash ◽  
Source Region ◽  
Airborne Lidar ◽  
Atmospheric Conditions ◽  
Volcanic Emissions ◽  
Cloud Properties ◽  
Mt Etna ◽  
Set Up ◽  
532 Nm

Abstract. We describe an airborne lidar for the characterization of atmospheric aerosol. The system has been set up in response to the need to monitor extended regions where the air traffic may be posed at risk by the presence of potentially harmful volcanic ash, and to study the characteristics of volcanic emissions both near the source region and when transported over large distances. The lidar provides backscatter and linear depolarization profiles at 532 nm, from which aerosol and cloud properties can be derived. The paper presents the characteristics and capabilities of the lidar system and gives examples of its airborne deployment. Observations from three flights, aimed at assessing the system capabilities in unperturbed atmospheric conditions, and at characterizing the emissions near a volcanic ash source (Mt. Etna) and transported far away from the source, are presented and discussed.

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