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Data-mining reconstruction of extreme magnetic storms: Going before the L1 era. / Stephens, Grant K.; Sitnov, Mikhail I.; Tsyganenko, Nikolai A.

2023. Реферат от 2023 AGU Fall Meeting, San Francisco, Калифорния, Соединенные Штаты Америки.

Результаты исследований: Материалы конференцийтезисы

Harvard

Stephens, GK, Sitnov, MI & Tsyganenko, NA 2023, 'Data-mining reconstruction of extreme magnetic storms: Going before the L1 era', 2023 AGU Fall Meeting, San Francisco, Соединенные Штаты Америки, 11/12/23 - 16/12/23. <https://agu.confex.com/agu/fm23/meetingapp.cgi/Paper/1420486>

APA

Stephens, G. K., Sitnov, M. I., & Tsyganenko, N. A. (2023). Data-mining reconstruction of extreme magnetic storms: Going before the L1 era. Реферат от 2023 AGU Fall Meeting, San Francisco, Калифорния, Соединенные Штаты Америки. https://agu.confex.com/agu/fm23/meetingapp.cgi/Paper/1420486

Vancouver

Stephens GK, Sitnov MI, Tsyganenko NA. Data-mining reconstruction of extreme magnetic storms: Going before the L1 era. 2023. Реферат от 2023 AGU Fall Meeting, San Francisco, Калифорния, Соединенные Штаты Америки.

Author

Stephens, Grant K. ; Sitnov, Mikhail I. ; Tsyganenko, Nikolai A. / Data-mining reconstruction of extreme magnetic storms: Going before the L1 era. Реферат от 2023 AGU Fall Meeting, San Francisco, Калифорния, Соединенные Штаты Америки.

BibTeX

@conference{5f7788479af045f38d25fe7002b3eeef,
title = "Data-mining reconstruction of extreme magnetic storms: Going before the L1 era",
abstract = "The geomagnetic field, electric currents and storm-time plasma pressure are reconstructed for the strongest storms before 1995, the July 1982 superstorm and the March 1989 Hydro-Qu{\'e}bec grid collapse event, using an improved data-mining algorithm, where gaps in the L1 electric field parameter were filled using a recently published machine learning algorithm. The data mining is renormalized using available statistics of the nearest neighbor bins to reduce the bias toward weaker activity events. The description of storm and substorms is combined using a concurrent reconstruction method: Storm and substorm features are first reconstructed independently with the focus on the inner and outer magnetospheric regions. Then the data fitting is reiterated using both the original historical records and the synthetic data generated after the first round of reconstructions. Data fitting is further optimized to improve the resolution of the field-aligned currents, which are weakly constrained by low-altitude observations. Testing the new mining algorithm with the November 2003 and 1982 superstorms shows a significant improvement of validation results for in-situ observations and the substantial increase of the peak ring current. The ring current becomes so strong that is results on the formation of an X-line crescent or even ring within geosynchronous orbit, which effectively reduces the ring current pressure.",
author = "Stephens, {Grant K.} and Sitnov, {Mikhail I.} and Tsyganenko, {Nikolai A.}",
year = "2023",
month = dec,
day = "16",
language = "English",
note = "2023 Fall Meeting of the American Geophysical Union, 2023 AGU Fall Meeting ; Conference date: 11-12-2023 Through 16-12-2023",

}

RIS

TY - CONF

T1 - Data-mining reconstruction of extreme magnetic storms: Going before the L1 era

AU - Stephens, Grant K.

AU - Sitnov, Mikhail I.

AU - Tsyganenko, Nikolai A.

PY - 2023/12/16

Y1 - 2023/12/16

N2 - The geomagnetic field, electric currents and storm-time plasma pressure are reconstructed for the strongest storms before 1995, the July 1982 superstorm and the March 1989 Hydro-Québec grid collapse event, using an improved data-mining algorithm, where gaps in the L1 electric field parameter were filled using a recently published machine learning algorithm. The data mining is renormalized using available statistics of the nearest neighbor bins to reduce the bias toward weaker activity events. The description of storm and substorms is combined using a concurrent reconstruction method: Storm and substorm features are first reconstructed independently with the focus on the inner and outer magnetospheric regions. Then the data fitting is reiterated using both the original historical records and the synthetic data generated after the first round of reconstructions. Data fitting is further optimized to improve the resolution of the field-aligned currents, which are weakly constrained by low-altitude observations. Testing the new mining algorithm with the November 2003 and 1982 superstorms shows a significant improvement of validation results for in-situ observations and the substantial increase of the peak ring current. The ring current becomes so strong that is results on the formation of an X-line crescent or even ring within geosynchronous orbit, which effectively reduces the ring current pressure.

AB - The geomagnetic field, electric currents and storm-time plasma pressure are reconstructed for the strongest storms before 1995, the July 1982 superstorm and the March 1989 Hydro-Québec grid collapse event, using an improved data-mining algorithm, where gaps in the L1 electric field parameter were filled using a recently published machine learning algorithm. The data mining is renormalized using available statistics of the nearest neighbor bins to reduce the bias toward weaker activity events. The description of storm and substorms is combined using a concurrent reconstruction method: Storm and substorm features are first reconstructed independently with the focus on the inner and outer magnetospheric regions. Then the data fitting is reiterated using both the original historical records and the synthetic data generated after the first round of reconstructions. Data fitting is further optimized to improve the resolution of the field-aligned currents, which are weakly constrained by low-altitude observations. Testing the new mining algorithm with the November 2003 and 1982 superstorms shows a significant improvement of validation results for in-situ observations and the substantial increase of the peak ring current. The ring current becomes so strong that is results on the formation of an X-line crescent or even ring within geosynchronous orbit, which effectively reduces the ring current pressure.

M3 - Abstract

T2 - 2023 Fall Meeting of the American Geophysical Union

Y2 - 11 December 2023 through 16 December 2023

ER -

ID: 115583350