Swarm SCARF Dedicated Ionospheric Field Inversion chain

Chulliat, Arnaud; Vigneron, P.; Thébault, Erwan; Sirol, Olivier; Hulot, Gauthier

doi:10.5047/eps.2013.08.006

Cited by 28 publications

(23 citation statements)

References 17 publications

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“…This regular variation depends on the local time, latitude, season, and solar cycle, and it is known as the solar quiet (Sq) geomagnetic field daily variation [e.g., Chapman and Bartels 1940;Matsushita 1960;Matsushita and Campbell 1967;Cloutier and Haymes 1968;Richmond et al 1976;Campbell 1982Campbell , 1997Schlapp and Butcher 1995;Takeda 2002;Torta et al 2010;Hawary et al 2012;Yamazaki and Yumoto 2012;Chulliat et al 2013]. The Sq variation is mainly produced by ionospheric currents flowing in the E region of the ionosphere around 105 km.…”

Section: Introductionmentioning

confidence: 99%

Long-term variation in the upper atmosphere as seen in the geomagnetic solar quiet daily variation

et al. 2014

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Characteristics of long-term variation in the amplitude of solar quiet (Sq) geomagnetic field daily variation have been investigated using 1-h geomagnetic field data obtained from 69 geomagnetic observation stations within the period of 1947 to 2013. The Sq amplitude observed at these geomagnetic stations showed a clear dependence on the 10-to 12-year solar activity cycle and tended to be enhanced during each solar maximum phase. The Sq amplitude was the smallest around the minimum of solar cycle 23/24 in 2008 to 2009. The relationship between the solar F10.7 index and Sq amplitude was approximately linear but about 53% of geomagnetic stations showed a weak nonlinear relation to the solar F10.7 index. In order to remove the effect of solar activity seen in the long-term variation of the Sq amplitude, we calculated a linear or second-order fitting curve between the solar F10.7 index and Sq amplitude during 1947 to 2013 and examined the residual Sq amplitude, which is defined as the deviation from the fitting curve. As a result, the majority of trends in the residual Sq amplitude that passed through a trend test showed negative values over a wide region. This tendency was relatively strong in Europe, India, the eastern part of Canada, and New Zealand. The relationship between the magnetic field intensity at 100-km altitude and residual Sq amplitude showed an anti-correlation for about 71% of the geomagnetic stations. Furthermore, the residual Sq amplitude at the equatorial station (Addis Ababa) was anti-correlated with the absolute value of the magnetic field inclination. This implies movement of the equatorial electrojet due to the secular variation of the ambient magnetic field.

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Section: Introductionmentioning

confidence: 99%

Long-term variation in the upper atmosphere as seen in the geomagnetic solar quiet daily variation

et al. 2014

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“…The general satellite data preprocessing workflow is described in Chulliat et al (2013). The first step, data selection, aims at extracting quiet-time data from the initial dataset.…”

Section: Data Preprocessingmentioning

confidence: 99%

“…The model parameterization was presented in depth in Chulliat et al (2013). Here we summarize the most important aspects for the purpose of presenting and discussing the modeling results in "Results" section and specify the parameters and auxiliary data used.…”

Section: Model Parameterizationmentioning

confidence: 99%

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First results from the Swarm Dedicated Ionospheric Field Inversion chain

2016

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Data-based modeling of the magnetic field originating in the Earth's ionosphere is challenging due to the multiple timescales involved and the small spatial scales of some of the current systems, especially the equatorial electrojet (EEJ) that flows along the magnetic dip equator. The Dedicated Ionospheric Field Inversion (DIFI) algorithm inverts a combination of Swarm satellite and ground observatory data at mid-to low latitudes and provides models of the solar-quiet (Sq) and EEJ magnetic fields on the ground and at satellite altitude. The basis functions of these models are spherical harmonics in quasi-dipole coordinates and Fourier series describing the 24-, 12-, 8-and 6-h periodicities, as well as the annual and semiannual variations. A 1-D conductivity model of the Earth and a 2-D conductivity model of the oceans and continents are used to separate the primary ionospheric field from its induced counterpart. First results from the DIFI algorithm confirm several well-known features of the seasonal variability and westward drift speed of the Sq current systems. They also reveal a peculiar seasonal variability of the Sq field in the Southern hemisphere and a longitudinal variability reminiscent of the EEJ wave-4 structure in the same hemisphere. These observations suggest that the Sq and EEJ currents might be electrically coupled, but only for some seasons and longitudes and more so in the Southern hemisphere than in the Northern hemisphere.

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“…These input models are provided by the other Swarm processing chains (see . Note that the data are not corrected for the ionospheric field, which is assumed minimum at night-times (see Chulliat et al, 2013). The second family of correction is based on more empirical processes, performed either at the global scale, or along the satellite orbits (process 4).…”

Section: Data Correction For the Main And External Fieldsmentioning

confidence: 99%

Swarm SCARF Dedicated Lithospheric Field Inversion chain

Thébault

Vigneron

Maus³

et al. 2013

Earth Planet Sp

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The forthcoming Swarm satellite mission is a constellation of three satellites dedicated to the study of the geomagnetic field. The orbital characteristics of the mission, which includes a pair of satellites flying side by side, has prompted new efforts in data processing and modeling. A consortium of several research institutions has been selected by the European Space Agency (ESA) to provide a number of Level-2 data products which will be made available to the scientific community. Within this framework, specific tools have been tailor-made to better recover the lithospheric magnetic field contribution. These tools take advantage of gradient properties measured by the lower pair of Swarm satellites and rely on a regional modeling scheme designed to better detect signatures of small spatial scales. We report on a processing chain specifically designed for the Swarm mission. Using an End-to-End simulation, we show that the tools developed are operational. The chain generates a model that meets the primary scientific objectives of the Swarm mission. We also discuss refinements that could also be implemented during the Swarm operational phase to further improve lithospheric field models and reach unprecedented spatial resolution.

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Swarm SCARF Dedicated Ionospheric Field Inversion chain

Cited by 28 publications

References 17 publications

Long-term variation in the upper atmosphere as seen in the geomagnetic solar quiet daily variation

Long-term variation in the upper atmosphere as seen in the geomagnetic solar quiet daily variation

First results from the Swarm Dedicated Ionospheric Field Inversion chain

Swarm SCARF Dedicated Lithospheric Field Inversion chain

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