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Prata, Fred
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- PublicationOpen AccessApplications of Ground-Based Infrared Cameras for Remote Sensing of Volcanic Plumes(2024-03-17)
; ; ; ; ; ; ; ;; ;; ; ;Ground-based infrared cameras can be used effectively and safely to provide quantitative information about small to moderate-sized volcanic eruptions. This study describes an infrared camera that has been used to measure emissions from the Mt. Etna and Stromboli (Sicily, Italy) volcanoes. The camera provides calibrated brightness temperature images in a broadband (8–14 µm) channel that is used to determine height, plume ascent rate and volcanic cloud/plume temperature and emissivity at temporal sampling rates of up to 1 Hz. The camera can be operated in the field using a portable battery and includes a microprocessor, data storage and WiFi. The processing and analyses of the data are described with examples from the field experiments. The updraft speeds of the small eruptions at Stromboli are found to decay with a timescale of ∼10 min and the volcanic plumes reach thermal equilibrium within ∼2 min. A strong eruption of Mt. Etna on 1 April 2021 was found to reach ∼9 km, with ascent speeds of 10–20 ms−1. The plume, mostly composed of the gases CO2, water vapour and SO2, became bent over by the prevailing winds at high levels, demonstrating the need for multiple cameras to accurately infer plume heights.37 8 - PublicationOpen AccessVolcanic cloud detection using Sentinel-3 satellite data by means of neural networks: the Raikoke 2019 eruption test case(2022-12-14)
; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ;; ; ; ;Accurate automatic volcanic cloud detection by means of satellite data is a challenging task and is of great concern for both the scientific community and aviation stakeholders due to well-known issues generated by strong eruption events in relation to aviation safety and health impacts. In this context, machine learning techniques applied to satellite data acquired from recent spaceborne sensors have shown promising results in the last few years. This work focuses on the application of a neural-network-based model to Sentinel-3 SLSTR (Sea and Land Surface Temperature Radiometer) daytime products in order to detect volcanic ash plumes generated by the 2019 Raikoke eruption. A classification of meteorological clouds and of other surfaces comprising the scene is also carried out. The neural network has been trained with MODIS (Moderate Resolution Imaging Spectroradiometer) daytime imagery collected during the 2010 Eyjafjallajökull eruption. The similar acquisition channels of SLSTR and MODIS sensors and the comparable latitudes of the eruptions permit an extension of the approach to SLSTR, thereby overcoming the lack in Sentinel-3 products collected in previous mid- to high-latitude eruptions. The results show that the neural network model is able to detect volcanic ash with good accuracy if compared to RGB visual inspection and BTD (brightness temperature difference) procedures. Moreover, the comparison between the ash cloud obtained by the neural network (NN) and a plume mask manually generated for the specific SLSTR images considered shows significant agreement, with an F-measure of around 0.7. Thus, the proposed approach allows for an automatic image classification during eruption events, and it is also considerably faster than time-consuming manual algorithms. Furthermore, the whole image classification indicates the overall reliability of the algorithm, particularly for recognition and discrimination between volcanic clouds and other objects.83 13 - PublicationRestrictedThe 2010 explosive eruption of Java's Merapi volcano—A ‘100-year’ event(2012)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;Surono, N.; CVGHM ;Jousset, P.; BRGM ;Pallister, J.; USGS ;Boichu, M.; University of Cambridge ;Buongiorno, M. F.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Budisantoso, A.; BPPTK ;Costa, F.; Earth Observatory of Singapore ;Andreastuti, S.; CVGHM ;Prata, F.; Norwegian Institute for Air Research ;Schneider, D.; USGS ;Clarisse, L.; Université Libre de Bruxelle ;Humaida, H.; BPPTK ;Sumarti, S.; CVGHM ;Bignami, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Griswold, J.; USGS ;Carn, S.; Norwegian Institute for Air Research ;Oppenheimer, C.; University of Cambridge ;Lavigne, F.; Laboratoire de Géographie Physique; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;Merapi volcano (Indonesia) is one of the most active and hazardous volcanoes in the world. It is known for frequent small to moderate eruptions, pyroclastic flows produced by lava dome collapse, and the large population settled on and around the flanks of the volcano that is at risk. Its usual behavior for the last decades abruptly changed in late October and early November 2010, when the volcano produced its largest and most explosive eruptions in more than a century, displacing at least a third of a million people, and claiming nearly 400 lives. Despite the challenges involved in forecasting this ‘hundred year eruption’, we show that the magnitude of precursory signals (seismicity, ground deformation, gas emissions) was proportional to the large size and intensity of the eruption. In addition and for the first time, near-real-time satellite radar imagery played an equal role with seismic, geodetic, and gas observations in monitoring eruptive activity during a major volcanic crisis. The Indonesian Center of Volcanology and Geological Hazard Mitigation (CVGHM) issued timely forecasts of the magnitude of the eruption phases, saving 10,000–20,000 lives. In addition to reporting on aspects of the crisis management, we report the first synthesis of scientific observations of the eruption. Our monitoring and petrologic data show that the 2010 eruption was fed by rapid ascent of magma from depths ranging from 5 to 30km. Magma reached the surface with variable gas content resulting in alternating explosive and rapid effusive eruptions, and released a total of ~0.44Tg of SO2. The eruptive behavior seems also related to the seismicity along a tectonic fault more than 40km from the volcano, highlighting both the complex stress pattern of the Merapi region of Java and the role of magmatic pressurization in activating regional faults. We suggest a dynamic triggering of the main explosions on 3 and 4 November by the passing seismic waves generated by regional earthquakes on these days.359 71 - PublicationOpen AccessVolcanic SO2 Near-Real Time Retrieval Using Tropomi Data and Neural Networks: The December 2018 Etna Test Case(2021)
; ; ; ; ; ; ; ; ; ; ; ;; ; ;; ; ; ;During a volcanic eruption, large quantities of Sulphur dioxide (SO2) are sometimes emitted into the atmosphere. Rapid detection and tracking ofvolcanic SO2 clouds might be beneficial to air traffic security and to predict any correlated impact on the environment; for example, the possibility of acid rain events. Within the presented work, we exploited Sentinel-5p radiance data (Level 1 b) to detect and retrieve SO2 volcanic emissions through a neural network based algorithmthat produces rapid SO2 vertical column estimates. The dataset used for training the net was composed of 13 TROPOMI Level 2 “Offline” SO2 data collected during the Etna Volcano eruption that occurred in 2018 from 22 December to 1 January. Experimental results are very encouraging and open to the perspective ofmake available a new and stable product for monitoring atmospheric SO2 clouds on a global scale based on Sentinel-5p acquisitions.43 76 - PublicationOpen AccessGround-Based Measurements of the 2014–2015 Holuhraun Volcanic Cloud (Iceland)(2018-01-18)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ;; ; ; ; ;The 2014–2015 Bárðarbunga fissure eruption at Holuhraun in central Iceland was distinguished by the high emission of gases, in total 9.6 Mt SO2, with almost no tephra. This work collates all ground-based measurements of this extraordinary eruption cloud made under particularly challenging conditions: remote location, optically dense cloud with high SO2 column amounts, low UV intensity, frequent clouds and precipitation, an extensive and hot lava field, developing ramparts, and high-latitude winter conditions. Semi-continuous measurements of SO2 flux with three scanning DOAS instruments were augmented by car traverses along the ring-road and along the lava. The ratios of other gases/SO2 were measured by OP-FTIR, MultiGAS, and filter packs. Ratios of SO2/HCl = 30–110 and SO2/HF = 30–130 show a halogen-poor eruption cloud. Scientists on-site reported extremely minor tephra production during the eruption. OPC and filter packs showed low particle concentrations similar to non-eruption cloud conditions. Three weather radars detected a droplet-rich eruption cloud. Top of eruption cloud heights of 0.3–5.5 km agl were measured with ground- and aircraft-based visual observations, web camera and NicAIR II infrared images, triangulation of scanning DOAS instruments, and the location of SO2 peaks measured by DOAS traverses. Cloud height and emission rate measurements were critical for initializing gas dispersal simulations for hazard forecasting438 109 - PublicationRestrictedThe 2019 Raikoke Eruption: ASH Detection and Retrievals Using S3-SLSTR Data(2021)
; ; ; ; ; ; ; ; ; ; ; ;; ; ;; ; ; ;In recent years many studies concerning the monitoring of volcanic activity have been carried out to develop ever more accurate and refine methods which allow to face the emergencies related to an eruption event. In our work we present different approaches for the volcanic ash cloud detection and retrieval using Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) data. As test case the SLSTR image collected on Raikoke volcano the 22 June 2019 at 00:07 UTC has been considered. A neural network based algorithm able to detect and distinguish volcanic and meteorological clouds, and the underlying surfaces, has been implemented and compared with two consolidated approaches: the RGB (Red-Green-Blue) and the Brightness Temperature Difference procedures. For the ash retrieval parameters (aerosol optical depth, effective radius and ash mass), three different methods have been compared: the reliable and consolidated LUT p (Look Up Table) procedure, the very fast VPR (Volcanic Plume Retrieval) algorithm and a neural network based model.43 1 - PublicationOpen AccessSatellite detection of volcanic ash from Eyjafjallajökull and the threat to aviation(2010)
; ; ; ; ; ; ; ; ; ;Prata, F.; NILU, Norway ;Stohl, A.; NILU, Norway ;Tørseth, K.; NILU, Norway ;Clarisse, L.; ULB, Belgium ;Carn, S.; Michigan Technological University, USA ;Pavalonis, M.; CIMSS, University of Wisconsin, USA ;Corradini, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Merucci, L.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Piscini, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia; ; ; ; ; ; ; ; Earth orbiting satellites provide an excellent means for monitoring and measuring emissions from volcanic eruptions. The recent eruption of Eyjafjallajökull in Iceland on 14 April, 2010 and the subsequent movement of the ash clouds were tracked using a variety of satellite instruments as they moved over Europe. Data from the rapid sampling (every 15 minutes) SEVIRI on Meteosat Second Generation were especially useful during this event as the thermal channels between 10–12 micron could be used to detect the ash signal and perform quantitative ash retrievals of mass loadings, optical depths and effective particle size. Higher-spatial resolution ( 1 km2) information from the MODIS sensors on NASA’s Terra and Aqua platforms were also analysed to determine ash microphysics and also to provide ash cloud top height. High-spectral resolution data from the IASI and AIRS sensors showed that initially quantities of ice, potentially with ash cores, were present, and that multi-species retrievals could be performed by exploiting the spectral content of the data. Vertically resolved ash layers were detected using the Caliop lidar on board the Calipso platform. Ash was clearly detected over Europe using the infra-red sensors with mass loadings typically in the range 0.1–5 gm-2, which for layers of 500–1000 m thickness, suggests ash concentrations in the range 0.1–10 mg m-3, and therefore represent a potential hazard to aviation.Little SO2 was detected at the start of the eruption, although both OMI and AIRS detected upper-level SO2 on 15 April. By late April and early May, 0.1–0.3 Tg (SO2) could be detected using these sensors. The wealth of satellite data available, some in near real-time, and the ability of infrared and ultra-violet sensors to detect volcanic ash and SO2 are emphasised in this presentation. The ash/aviation problem can be addressed using remote sensing measurements, validated with ground-based and air-borne, and combined with dispersion modelling. The volcanic ash threat to aviation can be ameliorated by utilising these space-based resources.228 91 - PublicationOpen AccessSO2 AND ASH VOLCANIC PLUME RETRIEVALS FROM THE 24 NOVEMBER 2006 Mt. ETNA ERUPTION USING MSG-SEVIRI DATA: SO2 VALIDATION AND ASH CORRECTION PROCEDURE(2008-08)
; ; ; ; ; ; ; ; ; ;Corradini, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Merucci, L.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Prata, F.; Norwegian Institute for Air Research, Norway ;Spinetti, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Silvestri, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Musacchio, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Burton, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Caltabiano, T.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Buongiorno, M. F.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia; ; ; ; ; ; ; ; Estimation of the daily trend of sulfur dioxide and ash from the thermal infrared measurements of the Spin Enhanced Visible and Infrared Imager (SEVIRI), on board the Meteosat Second Generation (MSG) geosynchronous satellite, has been carried out. The SO2 retrieval is validated vicariously by using satellite sensors and with ground measurements. The 24 November 2006 tropospheric eruption of Etna volcano is used as a test case. MSG-SEVIRI is an optical imaging radiometer characterized by 12 spectral channels, a high temporal resolution (one image every 15 minutes), and a 10 km2 footprint. The instrument’s spectral range includes the 7.3 and 8.7 mm bands (channels 6 and 7) used for SO2 retrieval and the 10.8 and 12.0 mm (channels 9 and 10) split window bands used for ash detection and retrievals. The SO2 columnar abundance and ash are retrieved simultaneously by means of a Look-Up Table least squares fit procedure for SO2 and using a Brightness Temperature Difference algorithm for ash. The SO2 retrievals obtained using different satellite sensors such as AIRS and MODIS have been carried out and compared with SEVIRI estimations. The results were validated using the permanent mini-DOAS ground system network (FLAME) installed and operated by INGV on Mt. Etna. Results show that the simultaneous presence of SO2 and ash in a volcanic plume yields a significant error in the SO2 columnar abundance retrieval in multispectral Thermal Infrared (TIR) data. The ash plume particles with high effective radius (from 1 to 10 mm) reduce the top of atmosphere radiance in the entire TIR spectral range, including the channels used for the SO2 retrieval. The net effect is a significant SO2 overestimation. To take this effect into account a novel ash correction procedure is presented and applied to the retrieval.187 168