Spatiotemporal Deep Learning Network for High-Latitude Ionospheric Phase Scintillation Forecasting

Liu, Yunxiang; Yang, Zhe; Morton,, Y. Jade; Li, Ruoyu

doi:10.33012/navi.615

Cited by 2 publications

(2 citation statements)

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“…While this general understanding of the drivers, sources, and processes that lead to the creation and evolution of high latitude ionospheric irregularities has helped to establish the climatology of ionospheric scintillation occurrence, there has not been a quantitative analysis of the time lags between the detection of the driver events and GNSS scintillation. The time lag distribution will not only provide further insights into the magnetosphere‐ionosphere coupling process, but also offer guidance in designing features for machine learning algorithms to forecast scintillation occurrences (Liu et al., 2023; McGranaghan et al., 2018). The objective of this paper is to quantify the time delay between the arrival of solar wind shock waves compressing the geomagnetic field and the resulting ionospheric irregularity impacts on ground‐based GNSS receivers, using GNSS scintillation monitoring receivers installed in northern high latitudes.…”

Section: Introductionmentioning

confidence: 99%

Time Lags Between Ionospheric Scintillation Detection at Northern Auroral Latitudes and Onset of Geomagnetic Storms

Yang,

Morton,

Liu

2023

JGR Space Physics

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Ionospheric responses to geomagnetic storms can cause irregular plasma structures and scintillation of Global Navigation Satellite System (GNSS) signals. In this paper, we investigate time lags between the detection of GNSS signal scintillation at northern hemisphere auroral latitudes and the onset of 15 geomagnetic storms that occurred in 2015–2017. The results show that the time lags between the detection of ground‐based GNSS scintillations and the observed sudden change in solar wind parameters are between tens of minutes and 15 hr. This time lag consists of two segments. The first segment is about 30–80 min, which is the lag between observed disturbances in the geomagnetic field and solar wind disturbances detected by orbiting spacecrafts around the L1 point. The second segment is between the observed GNSS signal scintillation and the storm sudden commencement (SSC). This second lag segment varies in the range of about 10–830 min and highly depends on the storm onset time and geomagnetic locations of GNSS signal propagation paths. Longer time lags over 450 min were observed with the signal ionospheric piercing point at 60–70° geomagnetic latitudes (MLAT) on the dayside, while shorter lags of 10∼450 min were observed with the signal IPPs at 68–81° MLAT and on the nightside at the time of SSC. The lag time variations can be explained by ionospheric irregularity production and transport processes associated with a variety of auroral and polar cap phenomena in response to solar wind coupling to the magnetosphere and ionosphere.

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Section: Introductionmentioning

confidence: 99%

Time Lags Between Ionospheric Scintillation Detection at Northern Auroral Latitudes and Onset of Geomagnetic Storms

Yang,

Morton,

Liu

2023

JGR Space Physics

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“…Coster and Yizengaw (2021) have classified the effects as follows: First, the presence of large gradients in ionospheric electron density can lead to significant errors in the range and bending of signals (Hoque & Jakowski, 2011;Sherif et al, 2023). Second, even minor irregularities at a small scale within the ionosphere can cause fluctuations in GNSS signals (also known as scintillation) or even result in the loss of the clock in GNSS signals (David et al, 2023;Liu et al, 2023). Lastly, solar radio bursts can noticeably impact GNSS signals by elevating the level of background noise (Cerruti et al, 2008;Sato et al, 2019).…”

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confidence: 99%

Forward‐Looking Study of Solar Maximum Impact in 2025: Effects of Satellite Navigation Failure on Aviation Network Operation in the Greater Bay Area, China

Xue,

Yang,

Liu

et al. 2023

Space Weather

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Satellite navigation based on the Global Navigation Satellite System can provide aircraft with more precise guidance and increase flight efficiency. However, severe space weather events can cause satellite navigation failure due to the dramatic increase in total electron content and irregularities in the ionosphere. Consequently, ground navigation has to be used to replace satellite navigation, increasing aircraft separation standards and reducing airspace capacity. As a result, numerous flights may be delayed or even canceled, incurring significant financial losses. The occurrence peak of space weather events generally coincides with the 11‐year‐cycle solar maximum, and 2025 is expected to be the upcoming solar maximum. The Greater Bay Area (GBA), located in the equatorial ionization anomaly region of China, is particularly vulnerable to space weather impacts. To explore the effects of satellite navigation failure on flight operation, we conduct this looking‐forward study and propose solution methods from the standpoint of Air Traffic Management, by simulating satellite navigation failure scenarios. Based on the projected flight volume in 2025 related to the GBA airports, simulation results show that the economic costs can be tens of millions of Euros, which is dependent on the duration of satellite navigation failure and the time interval of ground navigation‐based landing. We believe that this study can be a benchmark for evaluating the potential economic effects of forthcoming space weather on flight operations.

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Spatiotemporal Deep Learning Network for High-Latitude Ionospheric Phase Scintillation Forecasting

Cited by 2 publications

References 46 publications

Time Lags Between Ionospheric Scintillation Detection at Northern Auroral Latitudes and Onset of Geomagnetic Storms

Time Lags Between Ionospheric Scintillation Detection at Northern Auroral Latitudes and Onset of Geomagnetic Storms

Forward‐Looking Study of Solar Maximum Impact in 2025: Effects of Satellite Navigation Failure on Aviation Network Operation in the Greater Bay Area, China

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