Modelling of spatial-temporal changes of the geomagnetic field in Japan

Ji, Xiaoli; Utsugi, Mitsuru; Shirai, H.; Suzuki, Akira; He, Jingliang; Fujiwara, Satoshi; Fukuzaki, Yoshihiro

doi:10.1186/bf03351979

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…According to estimations based on the CHAOS main field model (Olsen et al 2006), the geomagnetic secular variations were identical for Kanoya and Kuchi-erabu-jima over this time period. The regional secular variation model by Ji et al (2006) also supports the similarity of the secular variations at the two sites.…”

Section: Analysis Of Volcanic Datasupporting

confidence: 60%

New procedures to decompose geomagnetic field variations and application to volcanic activitiy

Fujii

Kanda

2008

Geophysical Journal International

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SUMMARY We report the development of numerical procedures for extracting long‐term geomagnetic field variations caused by volcanic activity from an observed geomagnetic field by using statistical methods. The newly developed procedures are to estimate the trend from the observed data, as well as variations of non‐volcanic origin such as periodic components, components related to external geomagnetic variations and observational noise. We also aim at referring to data obtained at a remote standard geomagnetic observatory rather than using a temporarily installed reference site for reasons of data quality. Two different approaches—a Bayesian statistical method and a Kalman filter method—are applied to decompose the geomagnetic field data into four components for comparison. The number of filter coefficients and the degree of condition realizations are optimized on the basis of minimization of the information criteria. The two procedures were evaluated by using a synthetic data set. Generally, the results of both methods are equally sufficient. Subtle differences are seen at the first, several data points due to arbitrarily selected initial values in the case of the Kalman filter method and at the smaller residual for the Bayesian statistical method. The largest differences are in computation time and memory size. The Kalman filter method runs a thousand times faster on a testing workstation and requires less memory than the Bayesian method. The Kalman filter method was applied to the total intensity data at Kuchi‐erabu‐jima volcano. The result suggests that the procedure works reasonably well.

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Section: Analysis Of Volcanic Datasupporting

confidence: 60%

New procedures to decompose geomagnetic field variations and application to volcanic activitiy

Fujii

Kanda

2008

Geophysical Journal International

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“…Therefore, a new modeling method that can keep the quality with limited data is required. GSI developed new geomagnetic models (for example, Ji et al, 2006b;Ji et al, 2007) after release of the geomagnetic charts for the epoch 2000.0. Consequently, GSI created a new geomagnetic model in 2010, the "spatial-temporal model".…”

Section: Spatial-temporal Modelmentioning

confidence: 99%

Geomagnetic Surveys by the Geospatial Information Authority of Japan and the Contribution of the Kakioka Magnetic Observatory

et al. 2013

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The Geospatial Information Authority of Japan (GSI) has been conducting geomagnetic surveys in Japan since 1949 to clarify the geographical distribution of direction, intensity of the geomagnetic field, and their secular variations. Recently, we have carried out continuous observations at geodetic observatories and continuous geomagnetic stations and repetitive observations at several first-order geomagnetic stations. The results of the surveys, "geomagnetic charts", have been published every 10 years. In 2011, GSI released the newest geomagnetic charts for the epoch 2010.0 created by adopting a new spatial-temporal model. This model needs continuous data of good quality. In addition to the GSI geodetic observatories, the Kakioka Magnetic Observatory, which has been conducting high-quality and stable observations for 100 years, makes a large contribution.

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“…Spherical cap harmonic analysis was originally developed by G. V. Haines for mapping regional magnetic fields, and has been applied to create regional maps across the globe (e.g. Haines 1985aHaines , 1988Haines , 2007An et al 1998;De Santis et al 1997b;Feng et al 2015;Ji et al 2006;Kotze, 2014;Pavón-Carrasco et al 2008;Pothier et al 2015;Stening et al 2008;Tozzi et al 2013;Weimer 2013;Waters et al 2015). As a practical example, the Canadian Geomagnetic Reference Field (CGRF) is a regional magnetic field map that was produced every 5 years from 1985 to 2005 over Canada and adjacent regions (Haines and Newitt 1997).…”

Section: Introductionmentioning

confidence: 99%

Spherical Cap Harmonic Analysis Techniques for Mapping High-Latitude Ionospheric Plasma Flow—Application to the Swarm Satellite Mission

Fiori

2019

Ionospheric Multi-Spacecraft Analysis Tools

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This chapter describes spherical cap harmonic analysis (SCHA) for mapping ionospheric plasma flows measured by the Swarm satellites. In Sect. 9.1, SCHA is introduced as a tool for mapping a variety of one, two, and three-dimensional parameters. Section 9.2 provides a detailed summary of the theory pertaining to SCHA including a discussion of the spherical cap coordinate system, boundary conditions and basis functions, calculation of non-integer degree, and practical considerations. Section 9.3 provides a practical example of SCHA mapping of ionospheric plasma flow for a ground-based data set, and Sect. 9.4 focuses on two-dimensional SCHA mapping of Swarm ion drift measurements both independently and in conjunction with measurements from other instruments.

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Modelling of spatial-temporal changes of the geomagnetic field in Japan

Cited by 6 publications

References 6 publications

New procedures to decompose geomagnetic field variations and application to volcanic activitiy

New procedures to decompose geomagnetic field variations and application to volcanic activitiy

Geomagnetic Surveys by the Geospatial Information Authority of Japan and the Contribution of the Kakioka Magnetic Observatory

Spherical Cap Harmonic Analysis Techniques for Mapping High-Latitude Ionospheric Plasma Flow—Application to the Swarm Satellite Mission

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