{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:57:46Z","timestamp":1760237866783,"version":"build-2065373602"},"reference-count":5,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2020,6,29]],"date-time":"2020-06-29T00:00:00Z","timestamp":1593388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent years, some volcanic eruptions have focused scientists\u2019 attention on the detection and monitoring of volcanic clouds, as their impact on the air traffic control system has been unprecedented. In 2010, the Eyjafjallaj\u00f6kull 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.<\/jats:p>","DOI":"10.3390\/rs12132080","type":"journal-article","created":{"date-parts":[[2020,6,29]],"date-time":"2020-06-29T11:17:17Z","timestamp":1593429437000},"page":"2080","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Editorial for Special Issue \u201cConvective and Volcanic Clouds (CVC)\u201d"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3062-0326","authenticated-orcid":false,"given":"Riccardo","family":"Biondi","sequence":"first","affiliation":[{"name":"Dipartimento di Geoscienze, Universit\u00e0 degli Studi di Padova, 35131 Padova, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefano","family":"Corradini","sequence":"additional","affiliation":[{"name":"Istituto Nazionale di Geofisica e Vulcanologia (INGV), ONT, 00143 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Cigala, V., Biondi, R., Prata, A.J., Steiner, A.K., Kirchengast, G., and Brenot, H. (2019). GNSS radio OccultationAdvances the monitoring of volcanic clouds: The case of the 2008 Kasatochi Eruption. Remote Sens., 11.","DOI":"10.3390\/rs11192199"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zhu, W., Zhu, L., Li, J., and Sun, H. (2020). Retrieving volcanic ash top height through combined polar orbit activeand geostationary passive remote sensing data. Remote Sens., 12.","DOI":"10.3390\/rs12060953"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Corradini, S., Guerrieri, L., Stelitano, D., Salerno, G., Scollo, S., Merucci, L., Prestifilippo, M., Musacchio, M., Silvestri, M., and Lombardo, V. (2020). Near real-time monitoring of the Christmas 2018 Etna eruption using SEVIRI and products validation. Remote Sens., 12.","DOI":"10.3390\/rs12081336"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Scollo, S., Prestifilippo, M., Bonadonna, C., Cioni, R., Corradini, S., Degruyter, W., Rossi, E., Silvestri, M., Biale, E., and Carparelli, G. (2019). Near-real-time tephra fallout assessment at Mt. Etna, Italy. Remote Sens., 11.","DOI":"10.3390\/rs11242987"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Guerova, G., Dimitrova, T., and Georgiev, S. (2019). Thunderstorm classification functions based on instability indicesand GNSS IWV for the Sofia Plain. Remote Sens., 11.","DOI":"10.3390\/rs11242988"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/13\/2080\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:44:14Z","timestamp":1760175854000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/13\/2080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,29]]},"references-count":5,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["rs12132080"],"URL":"https:\/\/doi.org\/10.3390\/rs12132080","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2020,6,29]]}}}