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Understanding Strong Neutral Vertical Winds and Ionospheric Responses to the 2015 St. Patrick's Day Storm Using TIEGCM Driven by Data-Assimilated Aurora and Electric Fields

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dc.contributor.authorLu, Xianen
dc.contributor.authorWu, Haonanen
dc.contributor.authorKaeppler, Stephenen
dc.contributor.authorMeriwether, Johnen
dc.contributor.authorNishimura, Yukitoshien
dc.contributor.authorWang, Wenbinen
dc.contributor.authorLi, Jintaien
dc.contributor.authorShi, Xuelingen
dc.date.accessioned2023-03-27T17:05:51Zen
dc.date.available2023-03-27T17:05:51Zen
dc.date.issued2023-02en
dc.description.abstractAs one of the strongest geomagnetic storms in Solar Cycle 24, the 2015 St. Patrick's Day storm has attracted significant attention. We revisit this event by taking advantage of simultaneous observations of high-latitude forcings (aurora and electric fields) and ionosphere-thermosphere (I-T) responses. The forcing terms are assimilated to drive the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) using a newly adopted Lattice Kriging method (Wu & Lu, 2022, https://doi. org/10.1029/2021SW002880; Wu et al., 2022, https://doi.org/10.1029/2022SW003146). Compared to the default run, the TIEGCM simulation with assimilation captures: (a) secondary E-region electron density peak due to aurora intensification; (b) strongly elevated ion temperatures (up to similar to 3000 K) accompanied by a strong northward electric field (similar to 80 mV/m) and associated ion frictional heating; (c) elevation of electron temperatures; and (d) substantially enhanced neutral vertical winds (order of 50 m/s). Root-mean-square errors decrease by 30%-50%. The strong neutral upwelling is caused by large Joule heating down to similar to 120 km resulting from enhanced aurora and electric field. Data assimilation increases the height-integrated Joule heating at Poker Flat to a level of 50-100 mW/m2 while globally, its maximum value is comparable with the default run: the location of energy deposition becomes guided by data. Traveling atmospheric disturbances in the assimilation run show stronger magnitudes and larger extension leading to an increase of vertical wind variability by a factor of similar to 1.5-3. Our work demonstrates that data assimilation of model drivers helps produce realistic storm-time I-T responses, which show richer dynamic range, scales, and variability than what has been simulated before.en
dc.description.notesWe are grateful of the valuable discussion with Qiong Zhang, Whitney Huang, and Xiyan Tan at Clemson University concerning the data assimilation. We thank Donald Hampton and Mark Conde at University of Alaska Fairbanks for providing the FPI data. Xian Lu and Haonan Wu's work is supported by NASA Grants 80NSSC22K0018, NNX17AG10G, 80NSSC22K1010, 80NSSCK19K0810, and NSF Grants AGS-2149695, AGS-2012994, CAREER-1753214. Yukitoshi Nishimura's work is supported by NASA Grant 80NSSC18K0657, 80NSSC20K0604, 80NSSC20K0725, 80NSSC21K1321, and 80NSSC19K0546, NSF Grant AGS-1907698 and AGS-2100975, and AFOSR grant FA9559-16-1-0364. Wenbin Wang's work is supported in part by NASA Grants 80NSSC19K0080, 80NSSC20K0356, 80NSSC19K0835, 80NSSC20K0601 and NSF Grant AGS-2033843.en
dc.description.sponsorshipNASA [80NSSC22K0018, NNX17AG10G, 80NSSC22K1010, 80NSSCK19K0810, 80NSSC21K1321, 80NSSC19K0546, 80NSSC19K0080, 80NSSC20K0356, 80NSSC19K0835, CAREER-1753214, AGS-1907698, AGS-2100975, AGS-2033843]; NSF [80NSSC18K0657, 80NSSC20K0604, 80NSSC20K0725, 80NSSC20K0601, AGS-2149695, FA9559-16-1-0364]; AFOSR [AGS-2012994]en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1029/2022SW003308en
dc.identifier.eissn1542-7390en
dc.identifier.issue2en
dc.identifier.urihttp://hdl.handle.net/10919/114186en
dc.identifier.volume21en
dc.language.isoenen
dc.publisherAmerican Geophysical Unionen
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectspace weather modelingen
dc.subjectdata assimilationen
dc.subjectaurora and electric fieldsen
dc.subjectTIEGCMen
dc.subjectPFISR and SuperDARNen
dc.subjectTHEMIS ASIsen
dc.titleUnderstanding Strong Neutral Vertical Winds and Ionospheric Responses to the 2015 St. Patrick's Day Storm Using TIEGCM Driven by Data-Assimilated Aurora and Electric Fieldsen
dc.title.serialSpace Weather-The International Journal of Research and Applicationsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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