Relevant bibliographies by topics / Geomagnetic variation

Academic literature on the topic 'Geomagnetic variation'

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Published: 6 September 2023

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Journal articles on the topic "Geomagnetic variation"

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Sutcliffe, P. R. "The development of a regional geomagnetic daily variation model using neural networks." Annales Geophysicae 18, no. 1 (January 31, 2000): 120–28. http://dx.doi.org/10.1007/s00585-000-0120-0.

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Abstract. Global and regional geomagnetic field models give the components of the geomagnetic field as functions of position and epoch; most utilise a polynomial or Fourier series to map the input variables to the geomagnetic field values. The only temporal variation generally catered for in these models is the long term secular variation. However, there is an increasing need amongst certain users for models able to provide shorter term temporal variations, such as the geomagnetic daily variation. In this study, for the first time, artificial neural networks (ANNs) are utilised to develop a geomagnetic daily variation model. The model developed is for the southern African region; however, the method used could be applied to any other region or even globally. Besides local time and latitude, input variables considered in the daily variation model are season, sunspot number, and degree of geomagnetic activity. The ANN modelling of the geomagnetic daily variation is found to give results very similar to those obtained by the synthesis of harmonic coefficients which have been computed by the more traditional harmonic analysis of the daily variation.Key words. Geomagnetism and paleomagnetism (time variations; diurnal to secular) · Ionosphere (modelling and forecasting)
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Arifin, Lukman, and John Maspupu. "MODEL EMPIRIS HARI TENANG VARIASI MEDAN GEOMAGNET DI STASIUN GEOMAGNET TONDANO MANADO." JURNAL GEOLOGI KELAUTAN 12, no. 2 (February 16, 2016): 115. http://dx.doi.org/10.32693/jgk.12.2.2014.251.

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Penentuan model empiris hari tenang variasi medan geomagnet dikonstruksi berdasarkan data geomagnet dari stasiun geomagnet (SG) Badan Meteorologi Klimatologi dan Geofisika (BMKG) Tondano, Manado. Hari tenang variasi medan geomagnet dinyatakan sebagai fungsi dari keempat komponen atau variabel yang mempengaruhinya yaitu: aktivitas matahari SA (solar activity), hari dalam setahun DOY (date of year), usia bulan LA (lunar age) dan waktu lokal LT (local time). Dalam bentuk matematis ditulis sebagai, EMQD ( SA, DOY, LA, LT ) = f(SA). g(DOY). h(LA). m(LT). Model empiris yang didasarkan pada fungsi kecocokan ini terdiri dari 270 bentuk ekspresi matematik. Sedangkan bentuk-bentuk ekspresi matematik ini juga mencakup proses-proses non-linier yang tak dapat diabaikan dalam model empiris hari tenang variasi medan geomagnet tersebut. Model empiris ini dapat ditiru atau dikonstruksi kembali pada suatu selang waktu yang relatif panjang (misalnya satu siklus matahari), asalkan kondisi geomagnet selalu berada dalam keadaan tenang. Kontribusi dari model empiris hari tenang ini akan memberikan informasi tentang gangguan geomagnet yang ada di stasiun geomagnet Tondano (Nilai Gangguan geomagnet = Nilai variasi medan geomagnet yang terukur – Nilai model empiris hari tenang). Dengan demikian model ini akan memberikan informasi gangguan geomagnet untuk operasi survey geomagnet disekitar stasiun geomagnet Tondano, Manado. Kata kunci : Model empiris, Hari tenang, Variasi medan geomagnet. The determination an empirical model of the quiet daily geomagnetic field variation that is constructed based on geomagnetic data from Tondano, Manado station geomagnetic This quiet daily of geomagnetic field variation was described as a function of four variables that its influence, these are solar activity (SA), day of year (DOY), lunar age (LA) and local time (LT). In the mathematically writes: EMQD ( SA, DOY, LA, LT ) = f(SA). g(DOY). h(LA). m(LT). The empirical model based on this fitting function consist of 270 coefficients which included in expression form of mathematic. While, expression form of this mathematic also comprise nonlinear processes which can not minimized in the empirical model of the quiet daily geomagnetic field variation. This empirical model can be reconstructed on the time interval that is long relative (for example one solar cycle). Provided that, under geomagnetic quiet conditions. Contribution of this empirical model of the quiet daily variation is can give information about the existence of geomagnetic disturbance at Tondano (value of geomagnetic disturbance equal value of measurable geomagnetic field variation minus value of empirical model of the quiet daily variation). Thus, information about the existence of this geomagnetic disturbance very useful for necessity geomagnetic survey at Tondano, Manado geomagnetic station. Keywords: Empirical model, the quiet daily variation, geomagnetic field variation.
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Maspupu, John, and Setyanto C. D. Pranoto. "MODEL PARSIAL HARI TENANG VARIASI MEDAN GEOMAGNET SEBAGAI FUNGSI HARI DALAM SETAHUN, USIA BULAN DAN WAKTU LOKAL DI STASION GEOMAGNET TONDANO." JURNAL GEOLOGI KELAUTAN 12, no. 1 (February 16, 2016): 43. http://dx.doi.org/10.32693/jgk.12.1.2014.245.

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Penentuan suatu model parsial hari tenang variasi medan geomagnet di stasion geomagnet Tondano merupakan fungsi Date of Year (DOY), Lunar Age (LA), dan Local Time (LT). Diperoleh tiga model parsial hari tenang variasi medan geomagnet yaitu = g(DOY), = h(LA), dan = m(LT). Kontribusi dari DOY terhadap hari tenang variasi medan geomagnet sangatlah kecil (sebesar 0,784.10-3 %). Kontribusi faktor fisis lainnya diduga berperan terhadap hari tenang variasi medan geomagnet . Informasi hasil analisis model parsial variasi hari tenang terhadap usia bulan menunjukkan adanya anomali di sekitar lokasi pengamatan. Model parsial hari tenang variasi medan geomagnet yang diperoleh akan membentuk model empiris dari hari tenang. Model empiris akan memberikan informasi gangguan geomagnet untuk kegiatan survei geofisika di perairan Sulawesi Utara. Kata kunci : Model parsial, hari tenang, variasi medan geomagnet, DOY, LA, LT, Tondano. Determination of partial model from quiet daily geomagnetic field variation ( ) at geomagnetic station in Tondano is a function of Day of Year (DOY), Lunar Age (LA) and Local Time (LT). It obtains three partial models of quiet daily geomagnetic field variation, those are = g(DOY), = h(LA), dan = m(LT). Contribution from DOY to the quiet daily geomagnetic field variation ( ) is very small (around 0,784.10-3 %). Another contribution of physical factor presumes to play role to quiet daily geomagnetic field ( ). Information of analysis result of quiet daily partial model to lunar age indicates anomaly occurrence around the observation location. Partial model of the obtained quite daily geomagnetic will form empirical model of quite day. This empirical model will provide any information about geomagnetic disturbance for geophysical survey in North Sulawesi Waters. Keywords: Partial model, the quiet daily variation, geomagnetic field variation, DOY, LA, LT, Tondano.
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KUZNETSOV, V. V., V. V. PLOTKIN, I. I. NESTEROVA, and N. I. IZRAILEVA. "Universal Geomagnetic Variation." Journal of geomagnetism and geoelectricity 44, no. 7 (1992): 481–94. http://dx.doi.org/10.5636/jgg.44.481.

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Le Mouël, J. L., E. Blanter, and M. Shnirman. "The six-month line in geomagnetic long series." Annales Geophysicae 22, no. 3 (March 19, 2004): 985–92. http://dx.doi.org/10.5194/angeo-22-985-2004.

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Abstract. Daily means of the horizontal components X (north) and Y (east) of the geomagnetic field are available in the form of long series (several tens of years). Nine observatories are used in the present study, whose series are among the longest. The amplitudes of the 6-month and 1-year periodic variations are estimated using a simple but original technique. A remarkably clear result emerges from the complexity of the geomagnetic data: the amplitude of the 6-month line presents, in all observatories, the same large variation (by a factor of 1.7) over the 1920–1990 time span, regular and quasi-sinusoidal. Nothing comparable comes out for the annual line. The 6-month line results from the modulation by an astronomical mechanism of a magnetospheric system of currents. As this latter mechanism is time invariant, the intensity of the system of currents itself must present the large variation observed on the 6-months variation amplitude. This variation presents some similarities with the one displayed by recent curves of reconstructed solar irradiance or the "Earth's temperature". Finally, the same analysis is applied to the aa magnetic index.Key words. Geomagnetism and paleomagnetism (time variations, diurnal to secular). Magnetospheric physics (current systems; polar cap phenomena)
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Lyatsky, W., and A. M. Hamza. "Seasonal and diurnal variations of geomagnetic activity and their role in Space Weather forecast." Canadian Journal of Physics 79, no. 6 (June 1, 2001): 907–20. http://dx.doi.org/10.1139/p01-049.

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A possible test for different models explaining the seasonal variation in geomagnetic activity is the diurnal variation. We computed diurnal variations both in the occurrence of large AE (auroral electrojet) indices and in the AO index. (AO is the auroral electrojet index that provides a measure of the equivalent zonal current.) Both methods show a similar diurnal variation in geomagnetic activity with a deep minimum around (3–7) UT (universal time) in winter and a shallower minimum near 5–9 UT in equinoctial months. The observed UT variation is consistent with the results of other scientists, but it is different from that expected from the Russell–McPherron mechanism proposed to explain the seasonal variation. It is suggested that the possible cause for the diurnal and seasonal variations may be variations in nightside ionospheric conductivity. Recent experimental results show an important role for ionospheric conductivity in particle acceleration and geomagnetic disturbance generation. They also show that low ionospheric conductivity is favorable to the generation of auroral and geomagnetic activity. The conductivity in conjugate nightside auroral zones (where substorm generation takes place) is minimum at equinoxes, when both auroral zones are in darkness. The low ionospheric conductivity at equinoxes may be a possible cause for the seasonal variation in the geomagnetic activity with maxima in equinoctial months. The diurnal variation in geomagnetic activity can be produced by the UT variation in the nightside ionospheric conductivity, which in winter and at equinoxes has a maximum around 4–5 UT that may lead to a minimum in geomagnetic activity at this time. We calculated the correlation patterns for the AE index versus solar-wind parameters inside and outside the (2–7) UT sector related to the minimum in geomagnetic activity. The correlation patterns appear different in these two sectors indeed, which is well consistent with the UT variation in geomagnetic activity. It also shows that it is possible to improve significantly the reliability of the Space Weather forecast by taking into account the dependence of geomagnetic activity not only on solar-wind parameters but also on UT and season. Our test shows that a simple account for the dependence of geomagnetic activity on UT can improve the reliability of the Space Weather forecast by at least 50% in the 2–7 UT sector in winter and equinoctial months. PACS No.: 91.25Le
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Trichtchenko, L., and D. H. Boteler. "Modelling of geomagnetic induction in pipelines." Annales Geophysicae 20, no. 7 (July 31, 2002): 1063–72. http://dx.doi.org/10.5194/angeo-20-1063-2002.

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Abstract. Geomagnetic field variations induce telluric currents in pipelines, which modify the electrochemical conditions at the pipe/soil interface, possibly contributing to corrosion of the pipeline steel. Modelling of geomagnetic induction in pipelines can be accomplished by combining several techniques. Starting with geomagnetic field data, the geoelectric fields in the absence of the pipeline were calculated using the surface impedance derived from a layered-Earth conductivity model. The influence of the pipeline on the electric fields was then examined using an infinitely long cylinder (ILC) model. Pipe-to-soil potentials produced by the electric field induced in the pipeline were calculated using a distributed source transmission line (DSTL) model. The geomagnetic induction process is frequency dependent; therefore, the calculations are best performed in the frequency domain, using a Fourier transform to go from the original time domain magnetic data, and an inverse Fourier transform at the end of the process, to obtain the pipe-to-soil potential variation in the time domain. Examples of the model calculations are presented and compared to observations made on a long pipeline in the auroral zone.Key words. Geomagnetism and paleomagnetism (geo-magnetic induction)
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Xiao, Sheng Hong, Zhi Wu Cai, Yan Min Xie, and Shao Feng Bian. "Navigation and Positioning by Using the Insufficient Geomagnetic Components." Advanced Materials Research 569 (September 2012): 707–11. http://dx.doi.org/10.4028/www.scientific.net/amr.569.707.

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Geomagnetic field information of the vehicle contains abundant positional information, so the positional information can be derived from the geomagnetic observational value. Firstly, base on the analysis of geomagnetic maps of southeast China, the least square algorithm is used for modeling the local geomagnetism on WMM2010(world magnetic model)database. Then, the optimal positional model can be derived. The simulation has been done, from the simulation results we can see that the mean- squared error of the model in latitude and longitude are about 0.7062 sea mile and 1.8735 sea mile respectively. At last, according to the shortcoming of geomagnetic course system such as costing more time and money in calibration error, the partial geomagnetic field model is applied on correcting the compass variation. The analysis of simulation result indicates that the accuracy has been significantly improved.
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Marques de Souza Franco, Adriane, Rajkumar Hajra, Ezequiel Echer, and Mauricio José Alves Bolzan. "Seasonal features of geomagnetic activity: a study on the solar activity dependence." Annales Geophysicae 39, no. 5 (October 18, 2021): 929–43. http://dx.doi.org/10.5194/angeo-39-929-2021.

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Abstract. Seasonal features of geomagnetic activity and their solar-wind–interplanetary drivers are studied using more than five solar cycles of geomagnetic activity and solar wind observations. This study involves a total of 1296 geomagnetic storms of varying intensity identified using the Dst index from January 1963 to December 2019, a total of 75 863 substorms identified from the SuperMAG AL/SML index from January 1976 to December 2019 and a total of 145 high-intensity long-duration continuous auroral electrojet (AE) activity (HILDCAA) events identified using the AE index from January 1975 to December 2017. The occurrence rates of the substorms and geomagnetic storms, including moderate (-50nT≥Dst>-100nT) and intense (-100nT≥Dst>-250nT) storms, exhibit a significant semi-annual variation (periodicity ∼6 months), while the super storms (Dst≤-250 nT) and HILDCAAs do not exhibit any clear seasonal feature. The geomagnetic activity indices Dst and ap exhibit a semi-annual variation, while AE exhibits an annual variation (periodicity ∼1 year). The annual and semi-annual variations are attributed to the annual variation of the solar wind speed Vsw and the semi-annual variation of the coupling function VBs (where V = Vsw, and Bs is the southward component of the interplanetary magnetic field), respectively. We present a detailed analysis of the annual and semi-annual variations and their dependencies on the solar activity cycles separated as the odd, even, weak and strong solar cycles.
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Mandrikova, Oksana, Anastasia Rodomanskay, and Alexander Zaitsev. "Analysis of geomagnetic disturbances dynamics during increased solar activity and magnetic storms (according to the measurements of INTERMAGNET station network)." E3S Web of Conferences 127 (2019): 02003. http://dx.doi.org/10.1051/e3sconf/201912702003.

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We present and describe an automated method for analysis of magnetic data and for detection of geomagnetic disturbances based on wavelet transformation. The parameters of the computational algorithms allow us to estimate the characteristics of non-uniformly scaled peculiar properties in the variations of geomagnetic field that arise during increasing geomagnetic activity. The analysis of geomagnetic data before and during magnetic storms was carried out on the basis of the method according to ground station network. Periods of increasing geomagnetic activity, which precede and accompany magnetic storms, are highlighted. The dynamic of geomagnetic field variation in the auroral zone is considered in detail.
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Dissertations / Theses on the topic "Geomagnetic variation"

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Bloxham, J. "Geomagnetic secular variation." Thesis, University of Cambridge, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.372644.

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Heller, Rainer. "The paleomagnetic field's long-term mean intensity and secular variation /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/6840.

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Pressling, Nicola Justine. "Pacific geomagnetic secular variation : the story from Hawaii." Thesis, University of Leeds, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.441187.

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Lean, Candida Mary Bevan. "Geomagnetic palaeosecular variation recorded in North and Central American speleothems." Thesis, University of Liverpool, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240751.

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McArdle, Nicholas John. "Long term variation in geomagnetic field intensity and terrestrial planet development." Thesis, University of Liverpool, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.569142.

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Knowledge of the intensity of the Earth's magnetic field throughout geological time can deliver a wealth of information regarding the development of the planet. The nature of the geomagnetic field is dependent on processes that occur deep in the Earth's core. By analysing long period changes in geomagnetic field intensity inferences can be made about conditions in the Earth's interior far back into Earth history. The microwave palaeointensity technique is a relatively recent addition to palaeomagnetic investigation. High-frequency microwaves, which are resonant with the constituent magnetic system of a rock, are used to isolate and progressively remove the magnetisation of samples acquired at the time of formation in a controlled manner. By exciting the magnetic system directly, thermal-type experiments can be conducted, whilst minimising the risk of chemical alteration, which is a major cause of experimental failure.
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Finlay, Christopher Charles. "Hydromagnetic waves in Earth's core and their influence on geomagnetic secular variation." Thesis, University of Leeds, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418244.

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Mitsutake, Gen. "Natural variation in geomagnetic pulsations and preschool children's sleep disturbance and motor activity levels." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ62799.pdf.

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Allington, M. L., Catherine M. Batt, M. J. Hill, A. Nilsson, A. J. Biggin, and N. Card. "Obtaining archaeointensity data from British Neolithic pottery: A feasibility study." Elsevier, 2021. http://hdl.handle.net/10454/18426.

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Yes
There is a significant lack of geomagnetic field strength (archaeointensity) measurements for many archaeological time periods in the United Kingdom (UK). This not only makes past geomagnetic secular variation difficult to model but also limits the development of archaeointensity dating. This paper presents the first archaeointensity study on UK Neolithic material. In this study, twenty-five sherds of Neolithic Grooved Ware pottery from the Ness of Brodgar, Orkney, UK, some with direct radiocarbon dates, were subjected to a full archaeomagnetic investigation with the aim of increasing the amount of archaeointensity data for the UK. Both thermal Thellier and microwave palaeointensity experiments were used to determine which technique would be most suitable for British Neolithic pottery. Three successful archaeointensity results between 35 and 40μT were obtained using thermal Thellier method, which is consistent with the limited data available within a 15° radius and geomagnetic field model predictions from the same time. We separated the results into four different types with an intention of explaining the behaviours that determine the likelihood of achieving an acceptable archaeointensity estimate. The feasibility of obtaining geomagnetic field strength information during the UK Neolithic from ceramics has been demonstrated and the results provide a solid basis for improving our knowledge of geomagnetic secular variation during archaeological time in Britain.
The Andy Jagger Fund, University of Bradford, for supporting the stay at the University of Liverpool and Crafoord Grant, Sweden, No. 20160763. The radiocarbon dates were funded by AHRC NF/2017/2/7.
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Wardinski, Ingo. "Core surface flow models from decadal and subdecadal secular variation of the main geomagnetic field." Potsdam : Geoforschungszentrum, 2005. http://www.gfz-potsdam.de/bib/pub/str0507/0507.htm.

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Wardinski, Ingo. "Core surface flow models from decadal and subdecadal secular variation of the main geomagnetic field." [S.l.] : [s.n.], 2004. http://www.diss.fu-berlin.de/2005/70/index.html.

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Books on the topic "Geomagnetic variation"

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L, Parker R., and United States. National Aeronautics and Space Administration., eds. Statistics of the geomagnetic secular variation for the past 5Ma. [Washington, DC: National Aeronautics and Space Administration, 1986.

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Constable, Catherine. Final report on geomagnetic field models incorporating physical constraints on the secular variation. [Washington, DC: National Aeronautics and Space Administration, 1993.

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Xanthakis, John N. Geomagnetic field variation as inferred from archaeomagnetism in Greece and palaeomagnetism in British lake sediments since 7000 B.C. Athēnai: Grapheion Dēmosieumatōn tēs Akadēmias Athēnōn, 1991.

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Karl-Heinz, Glassmeier, Soffel H. Chr, and Negendank Jörg F. W, eds. Geomagnetic field variations. Berlin: Springer, 2009.

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Karl-Heinz, Glassmeier, Soffel H. Chr, and Negendank Jörg F. W, eds. Geomagnetic field variations. Berlin: Springer, 2009.

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Karl-Heinz, Glassmeier, Soffel H. Chr, and Negendank Jörg F. W, eds. Geomagnetic field variations. Berlin: Springer, 2009.

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Glaβmeier, Karl-Heinz, Heinrich Soffel, and Jörg F. W. Negendank. Geomagnetic Field Variations. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-76939-2.

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McLean, Susan. Bibliography of historical geomagnetic main field survey and secular variation reports at the World Data Center-A for Solid Earth Geophysics. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, National Geophysical Data Center, 1993.

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Dennis, Smith, World Data Center A for Solid Earth Geophysics., and National Geophysical Data Center, eds. Bibliography of historical geomagnetic main field survey and secular variation reports at the World Data Center-A for Solid Earth Geophysics. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, National Geophysical Data Center, 1993.

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1926-, Campbell Wallace H., ed. Quiet daily geomagnetic fields. Basel: Birkhäuser Verlag, 1989.

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Book chapters on the topic "Geomagnetic variation"

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McLeod, Malcolm G. "Geomagnetic Secular Variation." In Geomagnetism and Palaeomagnetism, 19–30. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-0905-2_2.

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Korte, Monika. "Geomagnetic Field, Secular Variation." In Encyclopedia of Solid Earth Geophysics, 1–2. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-10475-7_112-1.

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Korte, Monika. "Geomagnetic Field, Secular Variation." In Encyclopedia of Solid Earth Geophysics, 394. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-8702-7_112.

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Korte, Monika. "Geomagnetic Field, Secular Variation." In Encyclopedia of Solid Earth Geophysics, 514–15. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58631-7_112.

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Gubbins, David. "Historical Secular Variation and Geomagnetic Theory." In Geomagnetism and Palaeomagnetism, 31–43. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-0905-2_3.

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Rikitake, Tsuneji, and Yoshimori Honkura. "Secular Variation of the Geomagnetic Field." In Solid Earth Geomagnetism, 41–53. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4546-3_2.

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Gillet, N., V. Lesur, and N. Olsen. "Geomagnetic Core Field Secular Variation Models." In Terrestrial Magnetism, 129–45. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-7955-1_6.

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Svetlana, Riabova. "Geomagnetic Diurnal Variation at Mikhnevo Geophysical Observatory." In Processes in GeoMedia - Volume II, 389–98. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-53521-6_42.

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Rikitake, Tsuneji, and Yoshimori Honkura. "Geomagnetic Variation of External Origin and Electromagnetic Induction." In Solid Earth Geomagnetism, 193–204. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4546-3_8.

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Tarling, D. H. "Geomagnetic Secular Variation in Britain During the Last 2000 Years." In Geomagnetism and Palaeomagnetism, 55–62. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-0905-2_5.

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Conference papers on the topic "Geomagnetic variation"

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Buga, Arunas, Simona Einorytė, Romuald Obuchovski, Vytautas Puškorius, and Petras Petroškevicius. "Analysis of Secular Variations of Geomagnetic Field in Lithuania Based on the Survey in 2016." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.170.

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Lithuania is successfully integrated in the European geomagnetic field research activities. Six secular variation research stations were established in 1999 and precise geomagnetic field measurements were performed there in 1999, 2001, 2004, 2007 and 2016. Obtained diurnal magnetic field variations at measuring station and neighbouring observatories were analysed. All measurements are reduced to the mean of the year using data from geomagnetic observatory of Belsk. Based on the measured data the analysis of geomagnetic field parameter secular changes was performed. Results of the presented research are useful for updating the old geomagnetic data as well as for estimation of accuracy of declination model.
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Celik, C., E. Tolak-Ciftci, M. Zobu, H. Ozener, S. B. Tank, A. Kizmaz, and N. Sarikaya. "Sunspot-dependence of the Geomagnetic Daily Variation in Turkey." In 7th Congress of the Balkan Geophysical Society. Netherlands: EAGE Publications BV, 2013. http://dx.doi.org/10.3997/2214-4609.20131670.

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Jiang, Chufeng, Yong Dai, and Zhisheng Feng. "Earthquake Prediction Index of Geomagnetic Diurnal Variation Correlation Method." In 10th Academic Conference of Geology Resource Management and Sustainable Development 2022. Riverwood, NSW Australia: Aussino Academic Publishing House, 2022. http://dx.doi.org/10.52202/067798-0142.

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Asimopolos, Laurentiu, Natalia-Silvia Asimopolos, and Adrian-Aristide Asimopolos. "COMPARATIVE AND SPECTRAL STUDIES BETWEEN GEOMAGNETIC SERIES RECORDED IN INTERMAGNET OBSERVATORIES." In 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022/6.1/s28.36.

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The main objectives of this study are: analysis of the associated spectrum of the geomagnetic field, time of occurrence of geomagnetic storms and comparisons between recordings made at various geomagnetic observatories in the INTERMAGNET network, in terms of frequency intensity identified and correlations during geomagnetic disturbances. A geomagnetic storm is a temporary disturbance of the Earth's magnetosphere caused by ejections of solar corona mass, coronal holes or solar flares. The data used in this paper are recorded from the Surlari Observatory, and additional information for the characterization of the analyzed geomagnetic storms, we obtained from specialized sites such as www.intermagnet.org and www.noaa.gov. The information about the geomagnetic data from other observatories, as well as about the planetary physical parameters allowed us to make comparative studies between the data recorded in different observatories. We used and calculated filtered data, spectral analysis, wavelet algorithms with different mathematical functions at different levels, the variation of the correlation coefficients for the magnetic components recorded at different latitudes and longitudes.
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Martínez, Adrián, Carlos Lledó Ardila, Jordi Gutiérrez Cabello, and Pilar Gil Pons. "Further evidence of the long-term thermospheric density variation using 1U CubeSats." In Symposium on Space Educational Activities (SSAE). Universitat Politècnica de Catalunya, 2022. http://dx.doi.org/10.5821/conference-9788419184405.041.

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Faculty members, undergraduate and graduate students of the School of Communication and Aerospace Engineering (Polytechnical University of Catalonia) are participating in a series of studies to determine the thermospheric density. These studies involve planning a space mission, designing and constructing small satellites, and performing related data analysis. This article presents a method for determining the thermospheric density and summarises the academic context in which we develop our work. Several studies have reported the existence of a downtrend in thermospheric density, with relative values ranging from –2% to –7% per decade. Although it is well known that solar and geomagnetic activity are the main drivers of the variations of the thermospheric density, this downtrend was reported to be caused by the rise of greenhouse gases. We present an update of this progression, considering the last solar cycle (2009-2021) and using Two-Line Elements sets (TLE) of 1U CubeSats and the spherical satellites ANDE-2. TLEs were used to propagate the orbits numerically using SGP4 (Simplified General Perturbations), and then compute the average density between two consecutive TLEs by integrating the appropriate differential equation. Then, using the NRLMSISE-00 (Picone 2002) and JB2008 (Bowman 2008) atmospheric models, we calculated an average density deviation per year. We built a comprehensive time series of the thermospheric density values, ranging from 1967 to the present. We merged Emmert (2015) thermospheric density data and our results computed both with NRLMSISE-00 and with JB2008. A linear regression on the combined dataset yields a decreasing trend of –5.1% per decade. We also studied the geomagnetic and solar activity to isolate the possible greenhouse gasses effect during the considered period. Our results show a strong correlation between geomagnetic activity and density deviation near the solar minima, and we propose that the cause of the previously reported long-term density deviation could be a poor adjustment of the effects of geomagnetic activity. Finally, we proved that orbital information from small satellites could be efficiently used to assess the evolution of thermospheric density variations. Additional data obtained from future missions (as the one proposed by our group) will eventually allow a better characterisation of the atmospheric density and help disentangle the possible greenhouse gasses effects on its variations
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Matamba, Tshimangadzo M., and Donald W. Danskin. "Variation of TEC Over South Africa During a Geomagnetic Storm." In 2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC). IEEE, 2022. http://dx.doi.org/10.23919/at-ap-rasc54737.2022.9814299.

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Syafitri, Nia, Angga Yolanda Putra, Erlansyah, Muzirwan, Hadi Rasidi, Singgih Anggi Purnama, Helmi Suryaputra, et al. "Analysis of H-Component of Geomagnetic Variation in Indonesian Region." In IC3INA 2022: The 2022 International Conference on Computer, Control, Informatics and Its Applications. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3575882.3575948.

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R. Sutcliffe, Peter. "Progress Toward A Regional Geomagnetic Field Model Embracing The Sq Variation." In 5th SAGA Biennial Conference and Exhibition. European Association of Geoscientists & Engineers, 1997. http://dx.doi.org/10.3997/2214-4609-pdb.223.032.

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Asimopolos, Laurențiu, Natalia-Silvia Asimopoli, and drian-Aristide Asimopolos. "ANALYSES OF GEOMAGNETIC DATA SETS FROM OBSERVATORIES AND CORRELATION BETWEEN THEM." In GEOLINKS International Conference. SAIMA Consult Ltd, 2020. http://dx.doi.org/10.32008/geolinks2020/b1/v2/01.

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The purpose of this study was to analyze the associated spectrum of geomagnetic field, frequencies intensity and the time of occurrence. We calculated the variation of the correlation coefficients, with mobile windows of various sizes, for the recorded magnetic components at different latitudes and latitudes. We included in our study the observatories: Surlari (USA), Honolulu (HON), Scott Base (SBA), Kakioka (KAK), Tihany (THY), Uppsala (UPS), Wingst (WNG) and Yellowknife (YKC). We used the data of these observatories from INTERMAGNET for the bigest geomagnetic storm from the last two Solar Cycles. We have used for this purpose a series of filtering algorithms, spectral analysis and wavelet with different mother functions at different levels. In the paper, we show the Fourier and wavelet analysis of geomagnetic data recorded at different observatories regarding geomagnetic storms. Fourier analysis highlight predominant frequencies of magnetic field components. Wavelet analysis provides information about the frequency ranges of magnetic fields, which contain long time intervals for medium frequency information and short time intervals for highlight frequencies, details of the analyzed signals. Also, the wavelet analysis allows us to decompose geomagnetic signals in different waves. The analyzes presented are significant for the studied of the geomagnetic storm. The data for the next days after the storm showed a mitigation of the perturbations and a transition to a quiet day of the geomagnetic field. In both, the Fourier Transformation and the Wavelet Transformation, transformation evaluation involves the calculation of a scalar product between the analyzed signal and a set of signals that form a particular base in the vector space of the finite energy signals. Fourier representation use and orthogonal vectors base, whereas in the case of wavelet there is the possibility to use also bases consisting of independent linear non-orthogonal vectors. Unlike the Fourier transform, which depends only on a single parameter, wavelet transform type depends on two parameters, a and b. As a result, the graphical representation of the spectrum is different, wavelet analysis bringing more information about geomagnetic pattern of each observatory with that own specific conditions
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Mishra, Sujeet Kumar, and D. P. Tiwari. "Study of solar wind plasma structure and their association with geomagnetic field variation." In 2008 IEEE 35th International Conference on Plasma Science (ICOPS). IEEE, 2008. http://dx.doi.org/10.1109/plasma.2008.4590649.

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Reports on the topic "Geomagnetic variation"

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Crooker, N. U., E. W. Cliver, and B. T. Tsurutani. The Semiannual Variation of Great Geomagnetic Storms and the Postshock Russell-McPherron Effect Preceding Coronal Mass Ejecta. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada254955.

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Onovughe, Elvis. Usage of RC index as a Good Representation for Characterising Rapid Variation Signals in Geomagnetic Field Studiess. Balkan, Black sea and Caspian sea Regional Network for Space Weather Studies, April 2018. http://dx.doi.org/10.31401/sungeo.2018.01.11.

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BARKHATOV, NIKOLAY, and SERGEY REVUNOV. A software-computational neural network tool for predicting the electromagnetic state of the polar magnetosphere, taking into account the process that simulates its slow loading by the kinetic energy of the solar wind. SIB-Expertise, December 2021. http://dx.doi.org/10.12731/er0519.07122021.

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The auroral activity indices AU, AL, AE, introduced into geophysics at the beginning of the space era, although they have certain drawbacks, are still widely used to monitor geomagnetic activity at high latitudes. The AU index reflects the intensity of the eastern electric jet, while the AL index is determined by the intensity of the western electric jet. There are many regression relationships linking the indices of magnetic activity with a wide range of phenomena observed in the Earth's magnetosphere and atmosphere. These relationships determine the importance of monitoring and predicting geomagnetic activity for research in various areas of solar-terrestrial physics. The most dramatic phenomena in the magnetosphere and high-latitude ionosphere occur during periods of magnetospheric substorms, a sensitive indicator of which is the time variation and value of the AL index. Currently, AL index forecasting is carried out by various methods using both dynamic systems and artificial intelligence. Forecasting is based on the close relationship between the state of the magnetosphere and the parameters of the solar wind and the interplanetary magnetic field (IMF). This application proposes an algorithm for describing the process of substorm formation using an instrument in the form of an Elman-type ANN by reconstructing the AL index using the dynamics of the new integral parameter we introduced. The use of an integral parameter at the input of the ANN makes it possible to simulate the structure and intellectual properties of the biological nervous system, since in this way an additional realization of the memory of the prehistory of the modeled process is provided.
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Nikitina, L., and L. Trichtchenko. Extreme values statistical assessment for geomagnetic and geoelectric field variations for Alberta. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2015. http://dx.doi.org/10.4095/296956.

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Kleimenova, Natalia G., A. Odzimek, S. Michnowski, and M. Kubicki. Geomagnetic Storms and Substorms as Space Weather I nfluence on Atmospheric Electric Field Variations. Balkan, Black Sea and Caspian Sea Regional Network on Space Weather Studies, November 2018. http://dx.doi.org/10.31401/sungeo.2018.01.14.

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