Nowadays, the possibility that medium-large earthquakes could produce some electromagnetic ionospheric disturbances during their preparatory phase is controversial in the scientific community. Some previous works using satellite data from DEMETER, Swarm and, recently, CSES provided several pieces of evidence supporting the existence of such precursory phenomena in terms of single case studies and statical analyses. In this work, we applied a Worldwide Statistical Correlation approach to M5.5+ shallow earthquakes using the first 8 years of Swarm(i.e., from November 2013 to November 2021) magnetic field and electron density signals in order to improve the significance of previous statistical studies and provide some new results on how earthquake features could influence ionospheric electromagnetic disturbances. We implemented new methodologies based on the hypothesis that the anticipation time of anomalies of larger earthquakes is usually longer than that of anomalies of smaller magnitude. We also considered the signal’s frequency to introduce a new identification criterion for the anomalies. We find that taking into account the frequency can improve the statistical significance (up to 25% for magnetic data and up to 100% for electron density). Furthermore, we noted that the frequency of the Swarm magnetic field signal of possible precursor anomalies seems to slightly increase as the earthquake is approaching. Finally, we checked a possible relationship between the frequency of the detected anomalies and earthquake features. The earthquake focal mechanism seems to have a low or null influence on the frequency of the detected anomalies, while the epicenter location appears to play an important role. In fact, land earthquakes are more likely to be preceded by slower (lower frequency) magnetic field signals, whereas sea seismic events show a higher probability of being preceded by faster (higher frequency) magnetic field signals.

On 19 September 2021, La Palma Cumbre Vieja Volcano started an eruption classified as Volcanic Explosive Index (VEI) 3. In this study, at least the six months prior to such an event have been investigated to search for possible lithosphere–atmosphere–ionosphere bottom-up interactions. The lithosphere has been analysed in terms of seismicity getting advantages from the high-density local seismic network. Possible atmospheric alterations related to the volcano emissions or release of gases due to the uplift of the magmatic chamber have been searched in SO2, aerosol, dimethyl sulphide, and CO. The magnetic field on Earth’s surface has been studied by ground geomagnetic observatories. The status of the ionosphere has been investigated with two satellite missions: China Seismo Electromagnetic Satellite (CSES) and European Space Agency Swarm constellation, with Total Electron Content (TEC) retrieved from global maps. We identified a temporal migration of the seismicity from November 2020 at a depth of 40 km that seems associable to magma migration, firstly to a deep chamber at about 15 km depth and in the last 10 days in a shallow magma chamber at less than 5 km depth. The atmospheric composition, ground geomagnetic field, and ionosphere showed anomalies from more than three months before the eruption, suggesting a possible influence from the bottom geo-layers to the upper ones. CSES-01 detected an increase of electron density, confirmed by TEC data, and alterations of vertical magnetic field on ground Guimar observatory that are temporal compatible with some volcanic low seismic activity (very likely due to the magma uplift), suggesting an eventual electromagnetic disturbance from the lithosphere to the ionosphere. A final increase of carbon monoxide 1.5 months before the eruption with unusually high values of TEC suggests the last uplifting of the magma before the eruption, confirmed by a very high shallow seismicity that preceded the eruption by ten days. This work underlines the importance of integrating several observation platforms from ground and overall space to understand geophysics better, and, in particular, the natural hazard affecting our planet.

We theoretically investigate the high-order harmonic generation (HHG) of helium atom driven by bichromatic counter-rotating circularly polarized laser fields. By changing the intensity ratio of the two driving laser fields, the spectral chirality of the HHG can be controlled. As the intensity ratio increases, the spectral chirality will change from positive- to negative-value around a large intensity ratio of the two driving fields when the total laser intensity keeps unchanged. However, the sign of the spectral chirality can be changed from positive to negative around a small intensity ratio of the two driving fields when the total laser intensity changes. At this time, we can effectively control the helicity of the harmonic spectrum and the polarization of the resulting attosecond pulses by adjusting the intensity ratio of the two driving laser fields. As the intensity ratio and the total intensity of the driving laser fields increase, the relative intensity of either the left-circularly or right-circularly polarized harmonic can be enhanced. The attosecond pulses can evolve from being elliptical to near linear correspondingly.

Infrared and visible image fusion can obtain combined images with salient hidden objectives and abundant visible details simultaneously. In this paper, we propose a novel method for infrared and visible image fusion with a deep learning framework based on a generative adversarial network (GAN) and a residual network (ResNet). The fusion is accomplished with an adversarial game and directed by the unique loss functions. The generator with residual blocks and skip connections can extract deep features of source image pairs and generate an elementary fused image with infrared thermal radiation information and visible texture information, and more details in visible images are added to the final images through the discriminator. It is unnecessary to design the activity level measurements and fusion rules manually, which are now implemented automatically. Also, there are no complicated multi-scale transforms in this method, so the computational cost and complexity can be reduced. Experiment results demonstrate that the proposed method eventually gets desirable images, achieving better performance in objective assessment and visual quality compared with nine representative infrared and visible image fusion methods.

Several possible lithosphere–atmosphere–ionosphere coupling mechanisms before earthquake occurrence are presented in the literature. They are described by several models with different interaction channels (e.g., electromagnetic, mechanics, chemical, thermal), sometimes in conflict with each other. In this paper, we search for anomalies six months before the Lushan (China) 2013 earthquake in the three geo-layers looking for a possible view of the couplings and testing if one or another is more reliable to describe the observations. The Lushan earthquake occurred in China’s Sichuan province on 20 April 2013, with a magnitude of Mw = 6.7. Despite the moderate magnitude of the event, it caused concern because its source was localized on the southwest side of the same fault that produced the catastrophic Wenchuan event in 2008. This paper applies a geophysical multi-layer approach to search for possible pre-earthquake anomalies in the lithosphere, atmosphere, and ionosphere. In detail, six main increases in the accumulated seismic stress were depicted. Anomalous geomagnetic pulsations were recorded in the Chengdu observatory, sometimes following the increased stress. Atmosphere status and composition were found to be anomalous in several periods before the earthquake, and, spatially, the anomalies seem to appear firstly far from the upcoming earthquakes and later approaching the Longmenshan fault where the Lushan earthquakes nucleated. The Formosat-3 data identified interesting anomalies in the altitude or electron content of the ionospheric F2 peak in correspondence with seismic and atmospheric anomalies 130 days before the earthquake. In addition, the total electron content showed high anomalous values from 12 to 6 days before the earthquake. We compared the anomalies and tried to explain their correspondences in different geo-layers by the lithosphere–atmosphere–ionosphere coupling models. In particular, we identified three possible couplings with different mechanisms: a first, about 130 days before the earthquake, with a fast (order of one day) propagation delay; a second, about 40 days before the earthquake occurrence, with a propagation delay of few days and a third from 2.5 weeks until one week before the event. Such evidence suggests that the geo-layers could interact with different channels (pure electromagnetic or a chain of physical-chemical processes) with specific propagation delays. Such results support the understanding of the preparation for medium and large earthquakes globally, which is necessary (although not sufficient) knowledge in order to mitigate their impact on human life.