Special issue “Characterization of the geomagnetic field and its dynamic environment using data from space-based magnetometers”

Stolle, Claudia; Olsen, Nils; Anderson, B. J.; Doornbos, Eelco; Kuvshinov, Alexey

doi:10.1186/s40623-021-01409-0

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…Almost immediately afterward, in May 2018, another pair of spacecraft named the GRACE Follow-On (GRACE-FO; GRACE-C and GRACE-D) was launched to inherit the duty of GRACE. The GRACE-FO altitudes are similar to those of GRACE (∼500 km) at the launch as shown in Figure 1a: see also Landerer et al (2020), Stolle, Olsen, et al (2021), andStolle, Michaelis, et al (2021). GRACE and GRACE-FO spacecraft carry similar accelerometers manufactured by the same institute (Christophe et al, 2015).…”

Section: Spacecraft and Instruments: Grace And Grace-fomentioning

confidence: 67%

“…Upper-thermospheric GWs can lose half of their momentum flux when they propagate upward by several tens of kilometers (≈atmospheric scale height): for example, by 30 km under low solar activity (Vadas, 2007, Section 4). The CHAMP altitude under low solar activity (2006)(2007)(2008)(2009)(2010) was ∼350 km (Xu et al, 2021, Figure 1b;Stolle, Olsen, et al, 2021;Stolle, Michaelis, et al, 2021, Figure 1), which is roughly 5 scale heights below 500 km (500-350 km = 150 km = 5 × 30 km). Then, the momentum flux of GWs at 500 km would be only 2 −5 ≈ 1/32 ≈ 3% of that at CHAMP heights (i.e., attenuation by ∼97%) under low solar activity.…”

Section: Room For Further Improvements Over Previous Studies On Upper...mentioning

confidence: 99%

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Dayside Upper‐Thermospheric Density Fluctuations as Observed by GRACE and GRACE‐FO at ∼500 km Height

2023

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We statistically investigate fluctuation amplitudes (normalized to the background values) of dayside low‐/mid‐latitude upper‐thermospheric mass density as observed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE‐Follow‐On (GRACE‐FO) spacecraft at ∼500 km altitude between 2002 and 2022. There are three new findings in our results. First, the climatology closely replicates previous studies on stratospheric and upper‐thermospheric gravity waves (GWs) below the GRACE(‐FO) altitudes. For example, in low‐latitude regions, the fluctuations are stronger above continents than in the oceanic area. Mid‐latitude fluctuations prefer the local winter hemisphere to the summer, and the South American/Atlantic region in June solstice hosts stronger fluctuations than in any other low‐/mid‐latitude locations or seasons. Fluctuations are more intense under lower solar activity. The above‐mentioned consistency of the GRACE(‐FO) results with previous lower‐altitude GW studies confirms that GWs can penetrate up to 500 km. Second, the anti‐correlation of upper‐thermospheric GW with solar activity, which has been earlier reported for multi‐year time scales, can also be identified on the scale of the solar rotation period (∼27 days). Third, we demonstrate asymmetry between pre‐noon and post‐noon GWs. The former exhibits stronger GW activity, which may result from the colder thermosphere being more favorable for intense mass density fluctuations via secondary/tertiary GW generation.

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Section: Spacecraft and Instruments: Grace And Grace-fomentioning

confidence: 67%

Section: Room For Further Improvements Over Previous Studies On Upper...mentioning

confidence: 99%

Dayside Upper‐Thermospheric Density Fluctuations as Observed by GRACE and GRACE‐FO at ∼500 km Height

2023

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“…Section 2 provides a brief overview of the geomagnetic field. Subsequent work has shown the analytical potential of these additional data (e.g., Stolle, Olsen, et al (2021); Xiong et al (2021); Park et al (2020)).…”

Section: Introductionmentioning

confidence: 99%

“…They enlarge the spatiotem-68 poral distribution, e.g., providing enhanced coverage of the altitudes or local times of mea-69 sured phenomena mainly of magnetospheric or ionospheric origin. Subsequent work has 70 shown the analytical potential of these additional data (e.g.,Stolle, Olsen, et al (2021);71 Xiong et al (2021); Park et al (2020)). 72 In earlier works, we demonstrated the effectiveness of Machine Learning-based meth-73 ods for the calibration of platform magnetometers (Styp-Rekowski et al, 2021, 2022b; 74 Bader et al, 2022).…”

mentioning

confidence: 99%

Physics-informed Neural Networks for the Improvement of Platform Magnetometer Measurements

Styp-Rekowski,

Michaelis,

Korte

et al. 2024

Preprint

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Space-based measurements of the Earth’s magnetic field with a good spatiotemporal coverage are needed to understand the complex system of our surrounding geomagnetic field. High-precision magnetic field satellite missions form the backbone for sophisticated research, but they are limited in their coverage. Many satellites carry so-called platform magnetometers that are part of their attitude and orbit control systems. These can be re-calibrated by considering different behaviors of the satellite system, hence reducing their relatively high initial noise originating from their rough calibration. These platform magnetometer data obtained from non-dedicated satellite missions complement the high-precision data by additional coverage in space, time, and magnetic local times. In this work, we present an extension to our previous Machine Learning approach for the automatic in-situ calibration of platform magnetometers. We introduce a new physics-informed layer incorporating the Biot-Savart formula for dipoles that can efficiently correct artificial disturbances due to electric current-induced magnetic fields evoked by the satellite itself. We demonstrate how magnetic dipoles can be co-estimated in a neural network for the calibration of platform magnetometers and thus enhance the Machine Learning-based approach to follow known physical principles. Here we describe the derivation and assessment of re-calibrated datasets for two satellite missions, GOCE and GRACE-FO, which are made publicly available. We achieved a mean residual of about 7 nT and 4 nT for low- and mid-latitudes, respectively.

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Physics-informed neural networks for the improvement of platform magnetometer measurements

Styp-Rekowski,

Michaelis,

Korte

et al. 2025

Physics of the Earth and Planetary Interiors

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Special issue “Characterization of the geomagnetic field and its dynamic environment using data from space-based magnetometers”

Cited by 6 publications

References 11 publications

Dayside Upper‐Thermospheric Density Fluctuations as Observed by GRACE and GRACE‐FO at ∼500 km Height

Dayside Upper‐Thermospheric Density Fluctuations as Observed by GRACE and GRACE‐FO at ∼500 km Height

Physics-informed Neural Networks for the Improvement of Platform Magnetometer Measurements

Physics-informed neural networks for the improvement of platform magnetometer measurements

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