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Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021
This study reports the atmospheric electric field (AEF) anomalies associated with seismic-geological activity recorded by the monitoring network in the Sichuan–Yunnan region of China during the 15–30 days prior to the Yangbi earthquake in Yunnan Province, China, on 21 May 2021. Based on the real-tim...
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Published in: | Atmosphere 2023-10, Vol.14 (10), p.1579 |
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description | This study reports the atmospheric electric field (AEF) anomalies associated with seismic-geological activity recorded by the monitoring network in the Sichuan–Yunnan region of China during the 15–30 days prior to the Yangbi earthquake in Yunnan Province, China, on 21 May 2021. Based on the real-time AEF data from continuous observation, this study summarized the characteristics of the anomalous interference of different meteorological factors on the AEF, compared the simultaneous meteorological data of the AEF anomalies, and ruled out the influence of precipitation, wind, fog, and other weather factors on the AEF anomalies in Yangbi County prior to the Yangbi Ms 6.4 earthquake. The AEF anomalies were identified and extracted from the two-month data from 1 April to 1 June, which were from multiple days, stations, and rupture zones near the 100 km radius from the epicenter of the Yangbi Ms 6.4 main earthquake. Using time series and wavelet transform analysis methods, the obvious common features of the anomalies were summarized, and the homology of the anomalies was verified. The main outcome of the investigation in this study will be used to distinguish and characterize the AEF anomalies associated with pre-seismic geologic activity of non-meteorological elements in the near future. |
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Based on the real-time AEF data from continuous observation, this study summarized the characteristics of the anomalous interference of different meteorological factors on the AEF, compared the simultaneous meteorological data of the AEF anomalies, and ruled out the influence of precipitation, wind, fog, and other weather factors on the AEF anomalies in Yangbi County prior to the Yangbi Ms 6.4 earthquake. The AEF anomalies were identified and extracted from the two-month data from 1 April to 1 June, which were from multiple days, stations, and rupture zones near the 100 km radius from the epicenter of the Yangbi Ms 6.4 main earthquake. Using time series and wavelet transform analysis methods, the obvious common features of the anomalies were summarized, and the homology of the anomalies was verified. The main outcome of the investigation in this study will be used to distinguish and characterize the AEF anomalies associated with pre-seismic geologic activity of non-meteorological elements in the near future.</description><identifier>ISSN: 2073-4433</identifier><identifier>EISSN: 2073-4433</identifier><identifier>DOI: 10.3390/atmos14101579</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Aftershocks ; Anomalies ; Atmosphere ; atmospheric electric field (AEF) ; China ; Earthquake prediction ; Earthquakes ; Electric field ; Electric fields ; Environmental aspects ; Fog ; Geology ; Homology ; Humidity ; Meteorological data ; Precipitation ; Seismic activity ; Seismic waves ; Wavelet analysis ; Wavelet transforms ; Yangbi earthquake</subject><ispartof>Atmosphere, 2023-10, Vol.14 (10), p.1579</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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The main outcome of the investigation in this study will be used to distinguish and characterize the AEF anomalies associated with pre-seismic geologic activity of non-meteorological elements in the near future.</description><subject>Aftershocks</subject><subject>Anomalies</subject><subject>Atmosphere</subject><subject>atmospheric electric field (AEF)</subject><subject>China</subject><subject>Earthquake prediction</subject><subject>Earthquakes</subject><subject>Electric field</subject><subject>Electric fields</subject><subject>Environmental aspects</subject><subject>Fog</subject><subject>Geology</subject><subject>Homology</subject><subject>Humidity</subject><subject>Meteorological data</subject><subject>Precipitation</subject><subject>Seismic activity</subject><subject>Seismic waves</subject><subject>Wavelet analysis</subject><subject>Wavelet transforms</subject><subject>Yangbi earthquake</subject><issn>2073-4433</issn><issn>2073-4433</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpVkT1vGzEMhg9BAzRIMnYX0Plcfd3pNBqB0xqI0SHtkOnAkyhbzvnkSPLgvT88cq8oWnEQQfJ9SJBV9YnRhRCafoF8CIlJRlmj9FV1w6kStZRCfPjH_1jdp7Sn5UktuJA31a-1xSl75w1kHyYCkyXLCcZz8okERzanMfv6Oc_Z5aXJcYfRG7Ia0eSL8-hxvIjCAUaPiQzoQkSSd0heYNoOnmwSaReSrCDm3dsJXpEUFmdkA2fCKWd31bWDMeH9n_-2-vm4-vHwrX76_nX9sHyqjaQ614o6K9oOFXCAQStuKUq0AzYgVSOsci1qx0A2g3aDFsp1nWlVYztjtWKduK3WM9cG2PfH6A8Qz30A3_8OhLjty4jejNhTxxsAMKLrrBRGae5aELwZhGQKGltYn2fWMYa3E6bc78Mpls2lnncd521pSEvVYq7aQoH6yYUcwRSzePAmTOh8iS-VYprxRvIiqGeBiSGliO7vmIz2l0P3_x1avAP7K5qF</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Nie, Lei</creator><creator>Zhang, Xuemin</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>SOI</scope><scope>DOA</scope><orcidid>https://orcid.org/0009-0009-2623-7421</orcidid><orcidid>https://orcid.org/0000-0001-7462-4463</orcidid></search><sort><creationdate>20231001</creationdate><title>Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021</title><author>Nie, Lei ; Zhang, Xuemin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c409t-70fd368e7a2aab972d0e4edbe5a4753d7f6e9f1a45b9fb937f88c675d8cd97183</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aftershocks</topic><topic>Anomalies</topic><topic>Atmosphere</topic><topic>atmospheric electric field (AEF)</topic><topic>China</topic><topic>Earthquake prediction</topic><topic>Earthquakes</topic><topic>Electric field</topic><topic>Electric fields</topic><topic>Environmental aspects</topic><topic>Fog</topic><topic>Geology</topic><topic>Homology</topic><topic>Humidity</topic><topic>Meteorological data</topic><topic>Precipitation</topic><topic>Seismic activity</topic><topic>Seismic waves</topic><topic>Wavelet analysis</topic><topic>Wavelet transforms</topic><topic>Yangbi earthquake</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nie, Lei</creatorcontrib><creatorcontrib>Zhang, Xuemin</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environment Abstracts</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Atmosphere</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nie, Lei</au><au>Zhang, Xuemin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021</atitle><jtitle>Atmosphere</jtitle><date>2023-10-01</date><risdate>2023</risdate><volume>14</volume><issue>10</issue><spage>1579</spage><pages>1579-</pages><issn>2073-4433</issn><eissn>2073-4433</eissn><abstract>This study reports the atmospheric electric field (AEF) anomalies associated with seismic-geological activity recorded by the monitoring network in the Sichuan–Yunnan region of China during the 15–30 days prior to the Yangbi earthquake in Yunnan Province, China, on 21 May 2021. Based on the real-time AEF data from continuous observation, this study summarized the characteristics of the anomalous interference of different meteorological factors on the AEF, compared the simultaneous meteorological data of the AEF anomalies, and ruled out the influence of precipitation, wind, fog, and other weather factors on the AEF anomalies in Yangbi County prior to the Yangbi Ms 6.4 earthquake. The AEF anomalies were identified and extracted from the two-month data from 1 April to 1 June, which were from multiple days, stations, and rupture zones near the 100 km radius from the epicenter of the Yangbi Ms 6.4 main earthquake. Using time series and wavelet transform analysis methods, the obvious common features of the anomalies were summarized, and the homology of the anomalies was verified. 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subjects | Aftershocks Anomalies Atmosphere atmospheric electric field (AEF) China Earthquake prediction Earthquakes Electric field Electric fields Environmental aspects Fog Geology Homology Humidity Meteorological data Precipitation Seismic activity Seismic waves Wavelet analysis Wavelet transforms Yangbi earthquake |
title | Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021 |
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