Bulgarian Geomagnetic Reference Field (BulGRF) for 2015.0 and secular variation prediction model up to 2020

Metodiev, Metodi; Trifonova, Petya

doi:10.5194/angeo-35-1085-2017

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…The establishment of the repeat stations network in Bulgaria started in 1934 with eight points which were checked, stabilized, and provided with permanent miras. Now it consists of 27 points uniformly distributed over the entire territory (Metodiev, 2014).…”

Section: Tc Geomagnetic Observationa Regional Model Of Declination Fo...mentioning

confidence: 99%

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Earth Observation Capacity of the National Geoinformation Center of Bulgaria as Part of the Tools for Geo- and Anthropogenic-Hazard Management in EPOS

Trifonova,

Miloshev,

Dimitrova

et al. 2023

IDRiM Journal

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Exploring the nature of the Earth system and its multi-scale architecture requires an integrated symbiotic approach not only to understand our planet but also to reveal the hazards and footprints of their events on human life. Following the conceptual model of the European Plate Observing System (EPOS) we integrate a variety of research to obtain a multilateral use of geoinformation for scientific and practical purposes. In 2018, we started building a Bulgarian distributed scientific infrastructure called the National Geoinformation Center, aiming to provide data, products, and expertise to predict and prevent natural and anthropogenic risks and disasters, as well as environmental changes. The present paper demonstrates the capabilities of seismological, Global Navigation Satellite System (GNSS), geomagnetic and multi-scale laboratories (MSL) in Bulgaria that participate to the respective thematic core services of EPOS. More than 40 seismological stations register and transmit data in real time through the operational center of the Bulgarian Seismological Network. Data from 18 GNSS stations, part of the National GNSS network, are officially registered in the EPOS GNSS Data Gateway. Data and products are available via the EPOS GNSS Product Portal for interested users. Panagjurishte geomagnetic observatory (PAG) provides real time variations and long-period data series for the Earth’s magnetic field. The Palaeomagnetic Laboratory at the National Institute of Geophysics, Geodesy and Geography (NIGGG) participates in MSL with its unique facilities for paleo-, archeo- and environmental magnetism studies. Four case studies are presented to illustrate best practices for utilizing the data collected. The analysis of seismicity in a region of a long-time exploited salt deposit is upgraded with GNSS　data to reveal the reason for crustal movements in the region. The results show that the majority of the seismic events took place in the upper part of the Earth’s crust at a depth of up to 5 km, where the salt body is buried. The observed significant local deformations of the Earth’s surface are very likely related to the technological process of deposit exploitation. A recent model of the geomagnetic declination over the Bulgarian territory is also presented. It tracks the variation of the regional magnetic field from 2015 to 2020 and adds short-wavelength signals from the secular network observations. Last but not least, the application of a mineral magnetic laboratory analysis along the depth of a Holocene soil profile is demonstrated. Results reveal the soil evolution in response to environmental changes adding a new magnetic proxy parameter for more precise identification and characterization of the soil formation processes.

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Section: Tc Geomagnetic Observationa Regional Model Of Declination Fo...mentioning

confidence: 99%

“…Using all available data, Metodiev and Trifonova (2017) generated the latest analytic model called BulGRF of the geomagnetic field over the Bulgarian territory. Results were obtained for the horizontal component, vertical component, magnetic declination, and total intensity values.…”

Section: Tc Geomagnetic Observationa Regional Model Of Declination Fo...mentioning

confidence: 99%

Earth Observation Capacity of the National Geoinformation Center of Bulgaria as Part of the Tools for Geo- and Anthropogenic-Hazard Management in EPOS

Trifonova,

Miloshev,

Dimitrova

et al. 2023

IDRiM Journal

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“…Santis et al (2003) on the Italian Geomagnetic Reference Field, andMetodiev and Trifonova (2017) on the Bulgarian Geomagnetic Reference Field.Pavón-Carrasco et al. (…”

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confidence: 99%

Investigation of Regional Geomagnetic Field Modelling in Indonesia

Setiawan¹

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<p>This thesis deals with the application of the Spherical Cap Harmonic Analysis (SCHA) modelling technique to obtain geomagnetic field models for Indonesia, which have better resolution and accuracy than the International Geomagnetic Reference Field (IGRF). B-splines basis function and autoregressive forecasting are applied to improve estimates of secular variation and its forecast over the Indonesian region. The modelling technique is applied to geomagnetic observation data compiled from 68 geomagnetic repeat stations in Indonesia covering the period 1985 - 2015 from BMKG (Badan Meteorologi Klimatologi dan Geofisika / Agency for Meteorology, Climatology, and Geophysics) Indonesia, definitive data from five BMKG geomagnetic observatories and 13 INTERMAGNET (The International Real-Time Magnetic Observatory Network) observatories. Synthetic cartesian X, Y, and Z components at sea level at 17 fixed locations, calculated from IGRF-13, are also used. The area covered by the models in this thesis is the Indonesian region with a spherical cap half-angle of 30° and with the coordinate of the spherical cap pole at 122°E and 3°S. From statistical analysis and comparison with the IGRF, the SCHA model with index k = 7 is considered as the best SCHA model, both in resolution and accuracy. Compared with the root mean square deviation (RMSD) of the IGRF model, the RMSD of the SCHA model with index k = 7 is lower by 28 nT, 11 nT, and 34 nT for X, Y, and Z components, respectively. A model from interpolation of the SCHA with index k = 7 using the B-splines basis function for the year 1985.5 – 2015.5 shows that the SCHA model gives better results than the IGRF. The forecasting calculation for the year 2015.5 – 2020.5 suggests that the autoregressive order 3 of the SCHA with index k = 7 gives better results than the forecasting of the IGRF model, especially in the X, Z, and F components. However, in the Y component, the IGRF is still better than the SCHA model. The RMSD of the forecasted SCHA model is 154.92 nT, 200.87 nT, 104.39 nT, and 135.81 nT for X, Y, Z, and F components, respectively, while the RMSD of the IGRF model is 172.62 nT, 95.52 nT, 117.55 nT, and 162.38 nT for X, Y, Z, and F components. Thus, the forecasted SCHA model is suitable for data reduction of geomagnetic surveys in the Indonesian region but not preferable for navigation.</p>

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