Short‐Fractional Hop Whistler Rate Observed by the Low‐Altitude Satellite DEMETER at the End of the Solar Cycle 23

Parrot, M.; Pinçon, Jean-Louis; Shklyar, D. R.

doi:10.1029/2018ja026176

Cited by 6 publications

(5 citation statements)

References 50 publications

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“…Němec et al () indeed obtained higher median wave intensities during the months of high lightning activity. A more precise attempt to resolve the lightning contribution was done by Záhlava et al (), who used the data provided by the neural network for whistler detection onboard the DEMETER spacecraft (Elie et al, ; Parrot et al, ) to better distinguish various lightning activity levels at the measurement times. All these studies show that the lightning contribution is, especially during the night, nonnegligible.…”

Section: Introductionmentioning

confidence: 99%

Lightning Contribution to Overall Whistler Mode Wave Intensities in the Plasmasphere

Zãhlava

Němec

Santolı́k

et al. 2019

Geophysical Research Letters

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Electromagnetic waves generated by lightning propagate into the plasmasphere as dispersed whistlers. They can therefore influence the overall wave intensity in space, which, in turn, is important for dynamics of the Van Allen radiation belts. We analyze spacecraft measurements in low‐Earth orbit as well as in high‐altitude equatorial region, together with a ground‐based estimate of lightning activity. We accumulate wave intensities when the spacecraft are magnetically connected to thunderstorms and compare them with measurements obtained when thunderstorms are absent. We show that strong lightning activity substantially affects the wave intensity in a wide range of L‐shells and altitudes. The effect is observed mainly between 500 Hz and 4 kHz, but its frequency range strongly varies with L‐shell, extending up to 12 kHz for L lower than 3. The effect is stronger in the afternoon, evening, and night sectors, consistent with more lightning and easier wave propagation through the ionosphere.

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Section: Introductionmentioning

confidence: 99%

Lightning Contribution to Overall Whistler Mode Wave Intensities in the Plasmasphere

Zãhlava

Němec

Santolı́k

et al. 2019

Geophysical Research Letters

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“…The lightning activity is naturally function of many parameters as the location and the seasons. But a recent study has shown that a map of whistler activity is very different from a map of lightning activity [20]. The main point is that the whistlers with low dispersion are strongly attenuated close to the magnetic equator.…”

Section: The Whistlersmentioning

confidence: 94%

“…It is called a whistler. Onboard the low altitude satellite DEMETER, RNF is a dedicated experiment based on a neural network to count these whistlers and to classify them by dispersion with a time resolution of 0.1024 s. Details about the RNF experiment can be found in [18] [19], and [20]. Here we will consider the whistlers with low frequency dispersion, i.e., the whistlers which corresponds to waves emitted just below the satellite.…”

Section: The Whistlersmentioning

confidence: 99%

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Is There an Earthquake Weather?

Parrot¹,

Pinçon²

2020

OJER

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The aim of this study is to check if there is a relationship between the seismic activity and the whistlers observed by the micro-satellite DEMETER. Whistlers are the waves emitted by lightning strokes during thunderstorm activity. They use to propagate in the Earth-ionosphere waveguide but also in the ionosphere and the magnetosphere mainly along the magnetic field lines. Due to this reason we have checked the whistler occurrence not close to earthquake epicenters but close to the magnetically conjugate point of these epicenters at the satellite altitude. The number of whistlers is given by a neural network in operation onboard the satellite. It appears that the whistler amplitude is attenuated at the satellite altitude around the magnetic equator. It is why we have removed the earthquakes occurring at low geomagnetic latitudes in the statistic. The whistler rate is normalized with a background value to take into account the seasons and the epicenter locations. A superposed epoch method is used to display the results between −15 and +5 days around the earthquake day and up to 1000 km from the conjugate point of the epicenters. It is shown that the whistler rate is higher the day before the earthquake at a distance less than 200 km. It would be unrealistic to believe in the possibility to use this study for earthquake prediction because everyday thunderstorm activity reliably masks seismic effects. But it is further evidence that there is a lithosphere-atmosphere-ionosphere coupling at the time of the seismic activity.

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“…Zahlava et al [6] found that waves in the ionosphere were strongly related to frequency and geomagnetic latitude by analyzing the measurements from the detection of electro-magnetic emissions transmitted from spacecraft from earthquake regions. Parrot et al [7] found that for every 1 degree Celsius change in global temperature, the frequency of lightning varies by 5% to 6%. The electronic components of satellites are susceptible to damage due to the total dose effect and single-event effect of high-energy electrons.…”

Section: Introductionmentioning

confidence: 99%

Spaceborne Algorithm for Recognizing Lightning Whistler Recorded by an Electric Field Detector Onboard the CSES Satellite

Li,

Yuan,

Cao

et al. 2023

Atmosphere

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The electric field detector of the CSES satellite has captured a vast number of lightning whistler events. To recognize them effectively from the massive amount of electric field detector data, a recognition algorithm based on speech technology has attracted attention. However, this approach has failed to recognize the lightning whistler events which are contaminated by other low-frequency electromagnetic disturbances. To overcome this limitation, we apply the single-channel blind source separation method and audio recognition approach to develop a novel model, which consists of two stages. (1) The training stage: Firstly, we preprocess the electric field detector wave data into the audio fragment. Then, for each audio fragment, mel-frequency cepstral coefficients are extracted and input into the long short-term memory network for training the novel lightning whistler recognition model. (2) The inference stage: Firstly, we process each audio fragment with the single-channel blind source to generate two different sub-signals. Then, for each sub-signal, the mel-frequency cepstral coefficient features are extracted and input into the lightning whistler recognition model to recognize the lightning whistler. Finally, the two results above are processed by decision fusion to obtain the final recognition result. Experimental results based on the electric field detector data of the CSES satellite demonstrate the effectiveness of the algorithm. Compared with classical methods, the accuracy, recall, and F1-score of this algorithm can be increased by 17%, 62.2%, and 50%, respectively. However, the time cost only increases by 0.41 s.

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Short‐Fractional Hop Whistler Rate Observed by the Low‐Altitude Satellite DEMETER at the End of the Solar Cycle 23

Cited by 6 publications

References 50 publications

Lightning Contribution to Overall Whistler Mode Wave Intensities in the Plasmasphere

Lightning Contribution to Overall Whistler Mode Wave Intensities in the Plasmasphere

Is There an Earthquake Weather?

Spaceborne Algorithm for Recognizing Lightning Whistler Recorded by an Electric Field Detector Onboard the CSES Satellite

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