ВАК 1.6 Науки о Земле и окружающей среде
УДК 550.38 Земной магнетизм. Геомагнетизм
УДК 550.380 Техника геомагнитных исследований. Методы наблюдений и измерений. Методика. Оборудование
УДК 55 Геология. Геологические и геофизические науки
УДК 550.34 Сейсмология
УДК 550.383 Главное магнитное поле Земли
ГРНТИ 37.15 Геомагнетизм и высокие слои атмосферы
ГРНТИ 37.01 Общие вопросы геофизики
ГРНТИ 37.25 Океанология
ГРНТИ 37.31 Физика Земли
ГРНТИ 38.01 Общие вопросы геологии
ГРНТИ 36.00 ГЕОДЕЗИЯ. КАРТОГРАФИЯ
ГРНТИ 37.00 ГЕОФИЗИКА
ГРНТИ 38.00 ГЕОЛОГИЯ
ГРНТИ 39.00 ГЕОГРАФИЯ
ГРНТИ 52.00 ГОРНОЕ ДЕЛО
ОКСО 05.06.01 Науки о Земле
ББК 260 Земля в целом
ББК 26 Науки о Земле
ТБК 6324 Геоэлектричество. Геомагнетизм
ТБК 63 Науки о Земле. Экология
BISAC SCI019000 Earth Sciences / General
BISAC SCI SCIENCE
Various aspects of the measurements and processing of raw magnetic data obtained at observatories are considered. It is noteworthy that the processing can be executed through simple mathematical methods and algorithms at almost all stages. Nevertheless, there are a number of tasks, for example, related to the mass recognition of noise in raw data and the need to fill in gaps, for the effective solution of which it is necessary to involve more powerful mathematical technologies.
magnetic observatory, raw data, noise, modern mathematical methods
1. Gonsette A., Rasson J., Humbled F. In situ vector calibration of magnetic observatories // Geoscientific Instrumentation, Methods and Data Systems. — 2017. — Vol. 6, no. 2. — P. 361–366. — DOI:https://doi.org/10.5194/gi-6-361-2017.
2. INTERMAGNET Technical Reference Manual, Version 5.1.0 / ed. by B. V. St-Louis. — INTERMAGNET Operations Committee, Executive Council, 2020. — 146 p.
3. Jankowski J., Sucksdorff C. Guide for magnetic measurements and observatory practice. — Warshaw : International Association of Geomagnetism, Aeronomy, 1996. — 236 p.
4. Khomutov S. Y., Mandrikova O. V., Budilova E. A., et al. Noise in raw data from magnetic observatories // Geoscientific Instrumentation, Methods and Data Systems. — 2017. — Vol. 6, no. 2. — P. 329–343. — DOI:https://doi.org/10.5194/gi-6-329-2017.
5. McCuen B. A., Moldwin M. B., Steinmetz E. S., et al. Automated high-frequency geomagnetic disturbance classifier: A machine learning approach to identifying noise while retaining high-frequency components of the geomagnetic field // Journal of Geophysical Research: Space Physics. — 2023. — Vol. 128, no. 2. — P. 1–22. — DOI:https://doi.org/10.1029/2022JA030842.
6. Papsheva S. Y., Mandrikova O. V., Khomutov S. Y. Method of noise detection in magnetic data // Vestnik KRAUNC. Fizikomatematicheskie nauki. — 2019. — Vol. 29, no. 4. — P. 87–97. — DOI:https://doi.org/10.26117/2079-6641-2019-29-4-87-97. — (In Russian).
7. Sidorov R. V., Soloviev A. A., Bogoutdinov S. R. Application of the SP algorithm to the INTERMAGNET magnetograms of the disturbed geomagnetic field // Izvestiya, Physics of the Solid Earth. — 2012. — Vol. 48. — P. 410–414. — DOI:https://doi.org/10.1134/S1069351312040088.
8. Soloviev A. A., Bogoutdinov S. R., Agayan S. M., et al. Detection of hardware failures at INTERMAGNET observatories: application of artificial intelligence techniques to geomagnetic records study // Russian Journal of Earth Sciences. — 2009. — Vol. 11, no. 2. — ES2006. — DOI:https://doi.org/10.2205/2009ES000387.
9. Soloviev A. A., Chulliat A., Bogoutdinov S. R., et al. Automated recognition of spikes in 1 Hz data recorded at the Easter Island magnetic observatory // Earth, Planets and Space. — 2012. — Vol. 64. — P. 743–752. — DOI:https://doi.org/10.5047/eps.2012.03.004.
10. Soloviev A. A., Lesur V., Kudin D. V. On the feasibility of routine baseline improvement in processing of geomagnetic observatory data // Earth, Planets and Space. — 2018. — Vol. 70. — P. 1–14. — DOI:https://doi.org/10.1186/s40623-018-0786-8.
