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Convective and Volcanic Clouds (CVC)
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Convective and Volcanic Clouds (CVC)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 20743

Special Issue Editors

Dr. Riccardo Biondi

E-Mail Website
Guest Editor
Dipartimento di Geoscienze, Università degli Studi di Padova, 35122 Padova, Italy
Interests: remote sensing; volcanic clouds; convection; tropical cyclones; GNSS radio occultation
Special Issues, Collections and Topics in MDPI journals
Dr. Stefano Corradini

E-Mail
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Interests: remote sensing; volcanic cloud monitoring; ash and SO2 volcanic cloud retrievals; thermal infrared measurements

Special Issue Information

Dear Colleagues,

Extreme convective events cause many deaths and injuries and much damage to property every year, and account for major economic damages related to natural disasters in several countries. The tropical cyclone Harvey in 2017 was the strongest landfalling hurricane and the costliest on record. Due to global warming, Atlantic tropical cyclones have increasingly become extratropical cyclones, which also affect northern Europe.

In recent years, some volcanic eruptions have focused the scientists’ attention on the detection and monitoring of volcanic ash clouds, as their impact on the air traffic control system has been unprecedented. In 2010, Eyjafjallajökull eruption forced the disruption of the airspace of several countries generating the largest air traffic shutdown since World War II.

Convective and Volcanic Clouds (CVC) are very dangerous for aviation operations, as they can affect aircraft safety and economic, political, and cultural activities. The detection, nowcasting, and monitoring of CVC is vital for organizing efficient early warning systems. Convection and volcanic eruptions can reach the upper troposphere and lower stratosphere and impact atmospheric variability and climate change.

The proposed Special Issue aims to incorporate contributions from different fields such as

  • Forecasting tools to support air traffic management, thus improving the limits of the present science and new products/tools and providing better services to the end-users;
  • Extreme clouds remote sensing with novel techniques and new sensors;
  • Novel techniques to detect overshooting and their impact on climate; 
  • A special focus on the recent Anak Krakatau eruption (December 2018), with an extensive discussion of the interaction between volcanic cloud and surrounding convection.

Kind regards,

Dr. Riccardo Biondi
Dr. Stefano Corradini
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • convection
  • overshooting
  • tropical cyclone
  • volcanic eruption
  • volcanic cloud
  • cloud
  • volcanic monitoring
  • cloud remote sensing
  • cloud modeling

Published Papers (6 papers)

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Editorial

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3 pages, 171 KiB  
Editorial
Editorial for Special Issue “Convective and Volcanic Clouds (CVC)”
by Riccardo Biondi and Stefano Corradini
Remote Sens. 2020, 12(13), 2080; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12132080 - 29 Jun 2020
Cited by 1 | Viewed by 1704
Abstract
In recent years, some volcanic eruptions have focused scientists’ attention on the detection and monitoring of volcanic clouds, as their impact on the air traffic control system has been unprecedented. In 2010, the Eyjafjallajökull eruption forced the disruption of the airspace of several [...] Read more.
In recent years, some volcanic eruptions have focused scientists’ attention on the detection and monitoring of volcanic clouds, as their impact on the air traffic control system has been unprecedented. In 2010, the Eyjafjallajökull eruption forced the disruption of the airspace of several countries, generating one of the largest air traffic shutdowns ever. Extreme convective events cause many deaths and injuries, and much damage to property every year, accounting for major economic damages related to natural disasters in several countries. Due to global warming, Atlantic tropical cyclones have increased their maximum intensity, hurricanes have more often become extratropical cyclones affecting northern Europe, and southeastern Europe is characterized by increasing annual stormy days. Convective and Volcanic Clouds (CVC) are very dangerous for aviation operations, as they can affect aircraft safety and economic, political, and cultural activities. The detection, nowcasting, and monitoring of CVC is therefore vital for organizing efficient early warning systems. Full article
(This article belongs to the Special Issue Convective and Volcanic Clouds (CVC))

Research

Jump to: Editorial

20 pages, 8235 KiB  
Article
Near Real-Time Monitoring of the Christmas 2018 Etna Eruption Using SEVIRI and Products Validation
by Stefano Corradini, Lorenzo Guerrieri, Dario Stelitano, Giuseppe Salerno, Simona Scollo, Luca Merucci, Michele Prestifilippo, Massimo Musacchio, Malvina Silvestri, Valerio Lombardo and Tommaso Caltabiano
Remote Sens. 2020, 12(8), 1336; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12081336 - 23 Apr 2020
Cited by 28 | Viewed by 3705
Abstract
On the morning of 24 December 2018, an eruptive event occurred at Etna, which was followed the next day by a strong sequence of shallow earthquakes. The eruptive episode lasted until 30 December, ranging from moderate strombolian to lava fountain activity coupled with [...] Read more.
On the morning of 24 December 2018, an eruptive event occurred at Etna, which was followed the next day by a strong sequence of shallow earthquakes. The eruptive episode lasted until 30 December, ranging from moderate strombolian to lava fountain activity coupled with vigorous ash/gas emissions and a lava flow effusion toward the eastern volcano flank of Valle del Bove. In this work, the data collected from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instruments on board the Meteosat Second Generation (MSG) geostationary satellite are used to characterize the Etna activity by estimating the proximal and distal eruption parameters in near real time. The inversion of data indicates the onset of eruption on 24 December at 11:15 UTC, a maximum Time Average Discharge Rate (TADR) of 8.3 m3/s, a cumulative lava volume emitted of 0.5 Mm3, and a Volcanic Plume Top Height (VPTH) that reached a maximum altitude of 8 km above sea level (asl). The volcanic cloud ash and SO2 result totally collocated, with an ash amount generally lower than SO2 except on 24 December during the climax phase. A total amount of about 100 and 35 kt of SO2 and ash respectively was emitted during the entire eruptive period, while the SO2 fluxes reached peaks of more than 600 kg/s, with a mean value of about 185 kg/s. The SEVIRI VPTH, ash/SO2 masses, and flux time series have been compared with the results obtained from the ground-based visible (VIS) cameras and FLux Automatic MEasurements (FLAME) networks, and the satellite images collected by the MODerate resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua- polar satellites. The analysis indicates good agreement between SEVIRI, VIS camera, and MODIS retrievals with VPTH, ash, and SO2 estimations all within measurement errors. The SEVIRI and FLAME SO2 flux retrievals show significant discrepancies due to the presence of volcanic ash and a gap of data on the FLAME network. The results obtained in this study show the ability of geostationary satellite systems to characterize eruptive events from the source to the atmosphere in near real time during the day and night, thus offering a powerful tool to mitigate volcanic risk on both local population and airspace and to give insight on volcanic processes. Full article
(This article belongs to the Special Issue Convective and Volcanic Clouds (CVC))
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21 pages, 5398 KiB  
Article
Retrieving Volcanic Ash Top Height through Combined Polar Orbit Active and Geostationary Passive Remote Sensing Data
by Weiren Zhu, Lin Zhu, Jun Li and Hongfu Sun
Remote Sens. 2020, 12(6), 953; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12060953 - 16 Mar 2020
Cited by 6 | Viewed by 3048
Abstract
Taking advantage of both the polar orbit active remote sensing data (from the Cloud-Aerosol Lidar with Orthogonal Polarization—CALIOP) and vertical information and the geostationary passive remote sensing measurements (from the Spinning Enhanced Visible and Infrared Imager) with large coverage, a methodology is developed [...] Read more.
Taking advantage of both the polar orbit active remote sensing data (from the Cloud-Aerosol Lidar with Orthogonal Polarization—CALIOP) and vertical information and the geostationary passive remote sensing measurements (from the Spinning Enhanced Visible and Infrared Imager) with large coverage, a methodology is developed for retrieving the volcanic ash cloud top height (VTH) from combined CALIOP and Spinning Enhanced Visible and Infrared Imager (SEVIRI) data. This methodology is a deep-learning-based algorithm through hybrid use of Stacked Denoising AutoEncoder (SDA), the Genetic Algorithm (GA), and the Least Squares Support Vector Regression (LSSVR). A series of eruptions over Iceland’s Eyjafjallajökull volcano from April to May 2010 and the Puyehue-Cordón Caulle volcanic complex eruptions in Chilean Andes in June 2011 were selected as typical cases for independent validation of the VTH retrievals under various meteorological backgrounds. It is demonstrated that using the hybrid deep learning algorithm, the nonlinear relationship between satellite-based infrared (IR) radiance measurements and the VTH can be well established. The hybrid deep learning algorithm not only performs well under a relatively simple meteorological background but also is robust under more complex meteorological conditions. Adding atmospheric temperature vertical profile as additional information further improves the accuracy of VTH retrievals. The methodology and approaches can be applied to the measurements from the advanced imagers onboard the new generation of international geostationary (GEO) weather satellites for retrieving the VTH science product. Full article
(This article belongs to the Special Issue Convective and Volcanic Clouds (CVC))
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17 pages, 3314 KiB  
Article
Thunderstorm Classification Functions Based on Instability Indices and GNSS IWV for the Sofia Plain
by Guergana Guerova, Tsvetelina Dimitrova and Stefan Georgiev
Remote Sens. 2019, 11(24), 2988; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11242988 - 12 Dec 2019
Cited by 24 | Viewed by 3619
Abstract
Bulgaria is a country with a high frequency of hail and thunderstorms from May to September. For the May–September 2010–2015 period, statistical regression analysis was applied to identify predictors/classification functions that contribute skills to thunderstorm forecasting in the Sofia plain. The functions are [...] Read more.
Bulgaria is a country with a high frequency of hail and thunderstorms from May to September. For the May–September 2010–2015 period, statistical regression analysis was applied to identify predictors/classification functions that contribute skills to thunderstorm forecasting in the Sofia plain. The functions are based on (1) instability indices computed from radiosonde data from Sofia station F1, and (2) combination of instability indices and Integrated Water Vapor (IWV), derived from the Global Navigation Satellite System (GNSS) station Sofia-Plana, F2. Analysis of the probability of detection and the false alarm ratio scores showed the superiority of the F2 classification function, with the best performance in May, followed by June and September. F1 and F2 scores were computed for independent data samples in the period 2017–2018 and confirmed the findings for the 2010–2015 period. Analysis of IWV and lightning flash rates for a multicell and supercell thunderstorm in June and July 2014 showed that the monthly IWV thresholds are reached 14.5 and 3.5 hours before the thunderstorm, respectively. The supercell IWV peak registered 40 min before the thunderstorm, followed by a local IWV minimum corresponding to a peak in the flash rate. In both cases, an increase of IWV during severe hail was registered, which is likely related to the hydrometeor contribution to GNSS path delay. The results of this study will be integrated into the Bulgarian Integrated NowCAsting tool for thunderstorm forecasting in the warm/convective season. Full article
(This article belongs to the Special Issue Convective and Volcanic Clouds (CVC))
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18 pages, 7217 KiB  
Article
Near-Real-Time Tephra Fallout Assessment at Mt. Etna, Italy
by Simona Scollo, Michele Prestifilippo, Costanza Bonadonna, Raffaello Cioni, Stefano Corradini, Wim Degruyter, Eduardo Rossi, Malvina Silvestri, Emilio Biale, Giuseppe Carparelli, Carmelo Cassisi, Luca Merucci, Massimo Musacchio and Emilio Pecora
Remote Sens. 2019, 11(24), 2987; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11242987 - 12 Dec 2019
Cited by 37 | Viewed by 4626
Abstract
During explosive eruptions, emergency responders and government agencies need to make fast decisions that should be based on an accurate forecast of tephra dispersal and assessment of the expected impact. Here, we propose a new operational tephra fallout monitoring and forecasting system based [...] Read more.
During explosive eruptions, emergency responders and government agencies need to make fast decisions that should be based on an accurate forecast of tephra dispersal and assessment of the expected impact. Here, we propose a new operational tephra fallout monitoring and forecasting system based on quantitative volcanological observations and modelling. The new system runs at the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV-OE) and is able to provide a reliable hazard assessment to the National Department of Civil Protection (DPC) during explosive eruptions. The new operational system combines data from low-cost calibrated visible cameras and satellite images to estimate the variation of column height with time and model volcanic plume and fallout in near-real-time (NRT). The new system has three main objectives: (i) to determine column height in NRT using multiple sensors (calibrated cameras and satellite images); (ii) to compute isomass and isopleth maps of tephra deposits in NRT; (iii) to help the DPC to best select the eruption scenarios run daily by INGV-OE every three hours. A particular novel feature of the new system is the computation of an isopleth map, which helps to identify the region of sedimentation of large clasts (≥5 cm) that could cause injuries to tourists, hikers, guides, and scientists, as well as damage buildings in the proximity of the summit craters. The proposed system could be easily adapted to other volcano observatories worldwide. Full article
(This article belongs to the Special Issue Convective and Volcanic Clouds (CVC))
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13 pages, 2843 KiB  
Article
GNSS Radio Occultation Advances the Monitoring of Volcanic Clouds: The Case of the 2008 Kasatochi Eruption
by Valeria Cigala, Riccardo Biondi, Alfredo J. Prata, Andrea K. Steiner, Gottfried Kirchengast and Hugues Brenot
Remote Sens. 2019, 11(19), 2199; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11192199 - 20 Sep 2019
Cited by 9 | Viewed by 3453
Abstract
The products of explosive volcanic eruptions, in particular, volcanic ash, can pose a severe hazard to, for example, international aviation. Detecting volcanic clouds and monitoring their dispersal is hence, the subject of intensive current research. However, the discrepancies between the different available methods [...] Read more.
The products of explosive volcanic eruptions, in particular, volcanic ash, can pose a severe hazard to, for example, international aviation. Detecting volcanic clouds and monitoring their dispersal is hence, the subject of intensive current research. However, the discrepancies between the different available methods lead to detected cloud altitude with significant uncertainties. Here we show the results of an algorithm developed explicitly for high vertical resolution detection of volcanic cloud altitude by using the Global Navigation Satellite System radio occultation (RO) observations. Analyzing the energetic Kasatochi eruption of August 2008 in a case study, we find the volcanic cloud altitudes detected with RO in good agreement (within ~1 km) with cloud altitude estimations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar backscatter images in the 4 h range between RO and CALIOP acquisitions. The tracking by combined RO and imaging of the volcanic cloud evolution during the weeks after the eruption indicates a promising potential for operational global cloud altitude monitoring. Full article
(This article belongs to the Special Issue Convective and Volcanic Clouds (CVC))
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