{"id":"https://openalex.org/W4403079535","doi":"https://doi.org/10.1029/2024jh000151","title":"LiveWire: Horizontal Geoelectric Field Prediction With 1\u2010hr Lead\u2010Time Using Multi\u2010Fidelity Boosted Neural Networks","display_name":"LiveWire: Horizontal Geoelectric Field Prediction With 1\u2010hr Lead\u2010Time Using Multi\u2010Fidelity Boosted Neural Networks","publication_year":2024,"publication_date":"2024-10-02","ids":{"openalex":"https://openalex.org/W4403079535","doi":"https://doi.org/10.1029/2024jh000151"},"language":"en","primary_location":{"id":"doi:10.1029/2024jh000151","is_oa":true,"landing_page_url":"https://doi.org/10.1029/2024jh000151","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2024JH000151","source":{"id":"https://openalex.org/S4393248858","display_name":"Journal of Geophysical Research Machine Learning and Computation","issn_l":"2993-5210","issn":["2993-5210"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Geophysical Research: Machine Learning and Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2024JH000151","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082554131","display_name":"Andong Hu","orcid":"https://orcid.org/0000-0002-6929-2158"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"A. Hu","raw_affiliation_strings":["SWx TREC University of Colorado  Boulder CO USA"],"raw_orcid":"https://orcid.org/0000-0002-6929-2158","affiliations":[{"raw_affiliation_string":"SWx TREC University of Colorado  Boulder CO USA","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054362485","display_name":"Enrico Camporeale","orcid":"https://orcid.org/0000-0002-7862-6383"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]},{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"E. Camporeale","raw_affiliation_strings":["Department of Physics and Astronomy Queen Mary University of London  London UK","SWx TREC University of Colorado  Boulder CO USA"],"raw_orcid":"https://orcid.org/0000-0002-7862-6383","affiliations":[{"raw_affiliation_string":"Department of Physics and Astronomy Queen Mary University of London  London UK","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"SWx TREC University of Colorado  Boulder CO USA","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037394360","display_name":"Greg Lucas","orcid":"https://orcid.org/0000-0003-1331-1863"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]},{"id":"https://openalex.org/I4210114008","display_name":"Laboratory for Atmospheric and Space Physics","ror":"https://ror.org/01fcjzv38","country_code":"US","type":"facility","lineage":["https://openalex.org/I188538660","https://openalex.org/I4210114008"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Lucas","raw_affiliation_strings":["LASP University of Colorado  Boulder CO USA","SWx TREC University of Colorado  Boulder CO USA"],"raw_orcid":"https://orcid.org/0000-0003-1331-1863","affiliations":[{"raw_affiliation_string":"LASP University of Colorado  Boulder CO USA","institution_ids":["https://openalex.org/I188538660","https://openalex.org/I4210114008"]},{"raw_affiliation_string":"SWx TREC University of Colorado  Boulder CO USA","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057582273","display_name":"Thomas Berger","orcid":"https://orcid.org/0000-0002-4989-475X"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T. Berger","raw_affiliation_strings":["SWx TREC University of Colorado  Boulder CO USA"],"raw_orcid":"https://orcid.org/0000-0002-4989-475X","affiliations":[{"raw_affiliation_string":"SWx TREC University of Colorado  Boulder CO USA","institution_ids":["https://openalex.org/I188538660"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5082554131"],"corresponding_institution_ids":["https://openalex.org/I188538660"],"apc_list":null,"apc_paid":null,"fwci":0.3365,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5319052,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"1","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12424","display_name":"Earthquake Detection and Analysis","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6411610841751099},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.6327955722808838},{"id":"https://openalex.org/keywords/lead","display_name":"Lead (geology)","score":0.5990043878555298},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5978699922561646},{"id":"https://openalex.org/keywords/lead-time","display_name":"Lead time","score":0.5262091755867004},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5044234991073608},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.36888471245765686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32166847586631775},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19798284769058228},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09776568412780762},{"id":"https://openalex.org/keywords/geomorphology","display_name":"Geomorphology","score":0.07276618480682373},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06983321905136108}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6411610841751099},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6327955722808838},{"id":"https://openalex.org/C2777093003","wikidata":"https://www.wikidata.org/wiki/Q6508345","display_name":"Lead (geology)","level":2,"score":0.5990043878555298},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5978699922561646},{"id":"https://openalex.org/C2781468064","wikidata":"https://www.wikidata.org/wiki/Q1267117","display_name":"Lead time","level":2,"score":0.5262091755867004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5044234991073608},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.36888471245765686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32166847586631775},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19798284769058228},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09776568412780762},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.07276618480682373},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06983321905136108},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1029/2024jh000151","is_oa":true,"landing_page_url":"https://doi.org/10.1029/2024jh000151","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2024JH000151","source":{"id":"https://openalex.org/S4393248858","display_name":"Journal of Geophysical Research Machine Learning and Computation","issn_l":"2993-5210","issn":["2993-5210"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Geophysical Research: Machine Learning and Computation","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7666f3d289454010a67d80a47a0a9b47","is_oa":true,"landing_page_url":"https://doaj.org/article/7666f3d289454010a67d80a47a0a9b47","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Geophysical Research: Machine Learning and Computation, Vol 1, Iss 4, Pp n/a-n/a (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1029/2024jh000151","is_oa":true,"landing_page_url":"https://doi.org/10.1029/2024jh000151","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2024JH000151","source":{"id":"https://openalex.org/S4393248858","display_name":"Journal of Geophysical Research Machine Learning and Computation","issn_l":"2993-5210","issn":["2993-5210"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Geophysical Research: Machine Learning and Computation","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G3177685836","display_name":null,"funder_award_id":"80NSSC20K1275","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G718453068","display_name":null,"funder_award_id":"80NSSC20K1580","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"}],"funders":[{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"},{"id":"https://openalex.org/F4320322037","display_name":"Nuclear Safety and Security Commission","ror":"https://ror.org/05qk3ge34"},{"id":"https://openalex.org/F4320332183","display_name":"U.S. Geological Survey","ror":"https://ror.org/035a68863"},{"id":"https://openalex.org/F4320332538","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4403079535.pdf"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W941293174","https://openalex.org/W1924770834","https://openalex.org/W1992107289","https://openalex.org/W2002801528","https://openalex.org/W2007972759","https://openalex.org/W2078441523","https://openalex.org/W2091539461","https://openalex.org/W2098322460","https://openalex.org/W2163932252","https://openalex.org/W2166187720","https://openalex.org/W2564808782","https://openalex.org/W2622246362","https://openalex.org/W2752465967","https://openalex.org/W2767126550","https://openalex.org/W2789758093","https://openalex.org/W2794933829","https://openalex.org/W2811189959","https://openalex.org/W2902809560","https://openalex.org/W2973837607","https://openalex.org/W2994453307","https://openalex.org/W2996770550","https://openalex.org/W3010522705","https://openalex.org/W3092371715","https://openalex.org/W3092896378","https://openalex.org/W3101963837","https://openalex.org/W3129338160","https://openalex.org/W4220866683","https://openalex.org/W4221159243","https://openalex.org/W4307893952","https://openalex.org/W4361249933","https://openalex.org/W6902145280","https://openalex.org/W6958584605","https://openalex.org/W6969429625"],"related_works":["https://openalex.org/W2381850946","https://openalex.org/W4380449851","https://openalex.org/W4255463199","https://openalex.org/W4281691423","https://openalex.org/W2411039299","https://openalex.org/W1856410221","https://openalex.org/W3108315613","https://openalex.org/W4291265047","https://openalex.org/W4286841477","https://openalex.org/W3153279542"],"abstract_inverted_index":{"Abstract":[0],"Geomagnetically":[1],"Induced":[2],"Currents":[3],"(GICs)":[4],"are":[5],"electrical":[6],"currents":[7],"generated":[8],"by":[9,32,58,194],"rapid":[10],"changes":[11],"in":[12,59,147,203],"the":[13,35,39,46,86,114,148,154,167,187,214],"geomagnetic":[14,40,174],"field":[15,49,117,171,205],"during":[16,173],"space":[17,220],"weather":[18],"events,":[19],"posing":[20],"risks":[21],"to":[22,45,75,219],"power":[23,72],"grids":[24],"and":[25,103,133,163,186,198],"pipelines.":[26],"Traditional":[27],"approaches":[28],"predict":[29],"GICs":[30],"indirectly":[31],"forecasting":[33,206],",":[34],"temporal":[36],"variation":[37],"of":[38,85,99,216],"field,":[41,88],"which":[42,89],"is":[43],"proportional":[44],"induced":[47],"electric":[48],"via":[50],"Faraday's":[51],"law.":[52],"However,":[53],"current":[54],"physics\u2010based":[55],"models":[56],"driven":[57],"situ":[60],"solar":[61,134],"wind":[62,135],"measurements":[63],"offer":[64],"only":[65],"10\u201330":[66],"min":[67],"lead":[68,121],"times,":[69],"insufficient":[70],"for":[71],"grid":[73,80],"operators":[74,81],"take":[76],"mitigating":[77],"actions.":[78],"Additionally,":[79],"prefer":[82],"direct":[83],"forecasts":[84,113],"geoelectric":[87,116,170,204],"directly":[90,112],"influences":[91],"GICs,":[92],"rather":[93],"than":[94],"relying":[95],"on":[96,166],"intermediate":[97],"predictions":[98],"that":[100,111,179],"require":[101],"complex":[102],"time\u2010consuming":[104],"calculations.":[105],"We":[106],"present":[107],"a":[108,119,138,183],"novel":[109],"approach":[110],"horizontal":[115],"with":[118],"one\u2010hour":[120],"time,":[122],"bypassing":[123],"predictions.":[124],"Our":[125,176],"method":[126],"combines":[127],"magnetometer":[128],"data,":[129,132],"magnetotelluric":[130],"survey":[131],"inputs":[136],"into":[137],"new":[139],"probabilistic":[140],"multi\u2010fidelity":[141],"machine":[142],"learning":[143],"technique,":[144],"ProBoost,":[145],"resulting":[146],"LiveWire":[149,165,180],"model.":[150],"Using":[151],"data":[152],"from":[153],"Boulder":[155],"Geomagnetic":[156],"Observatory":[157],"(BOU)":[158],"since":[159],"2002,":[160],"we":[161],"trained":[162],"validated":[164],"top":[168],"50":[169],"events":[172],"storms.":[175],"results":[177],"show":[178],"outperforms":[181],"both":[182],"persistence":[184],"forecast":[185],"operational":[188],"Space":[189],"Weather":[190],"Modeling":[191],"Framework":[192],"(SWMF)":[193],"at":[195],"least":[196],"31%":[197],"23%,":[199],"respectively.":[200],"This":[201],"advancement":[202],"promises":[207],"more":[208],"accurate":[209],"GIC":[210],"predictions,":[211],"helping":[212],"enhance":[213],"resilience":[215],"critical":[217],"infrastructure":[218],"weather.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
