Journal of Atmospheric and Solar-Terrestrial Physics最新文献

The Galactic Cosmic Rays (GCR) flux can contribute to the formation of condensation nuclei (CN), radionuclides, and other particles, which in turn influence the formation of rain and extreme weather events. The aim of this analysis was to investigate the possible influence of GCR flux on the extreme rainfall events that occurred in Greece and Libya in September 2023. We used time series data for GCR, rainfall estimates from ERA5, and Sea Surface Temperature (SST) for the period between September 1, 2023, and September 11, 2023. The results revealed a negative correlation between GCR and SST of −0.807 (Greece) and −0.828 (Libya), and a positive correlation between precipitation and SST of +0.972 (Greece) and +0.998 (Libya). The GCR flux and SST accounted for approximately 60.52% and 34.53% of the extreme event in Greece, and 33.71% and 65.96% in Libya, respectively. These statistical results indicate that GCR flux contributed to the formation of the extreme precipitation event that caused significant destruction in Greece and Libya in September 2023.

The processes of ion formation in humid tropospheric air under the action of cosmic rays are considered. In this case, positive and negative cluster ions appear. For this analysis, a kinetic model was developed that includes 55 components and 161 reactions. The calculation was carried out using the KINET software package. It is shown that the ionization of air by cosmic rays at altitudes of 5–35 km leads to the formation of plasma consisting mainly of $N{H}_4^{+}\cdot N{H}_3\cdot H_{2}O$, $H^{+}\cdot {\left(H_{2}O\right)}_4$ and $O_2^{-}\cdot {\left(H_{2}O\right)}_2$ ions. The maximum concentrations of ions under conditions of minimum magnetic rigidity are observed at altitudes from 10 to 18 km. These results differ sharply from the calculation results obtained for the dry air model.

Tropospheric propagation channel modeling is gaining more attention in the scientific community, especially in the applications of the upcoming high-frequency satellite communication systems. Channel modeling is essential to predict link performance, for example, in the area of Bit-Error-Ratio (BER) in a single-user scenario and in a multi-user scenario, especially in the areas of throughput and latency. This study investigates the seasonal characteristics of rainfall rate and rain-induced attenuation in terms of exceedance and worst-month rain statistics over selected tropical locations in Nigeria. The coefficient of variation (CV) of rain rate has also been analyzed to examine the variability of rainfall rate due to the inhomogeneity nature of the chosen region. The GPM satellite 30-min rain rate data has been used for rain attenuation prediction through a 30-min to 1-min metric conversion model. Validation of rain attenuation was conducted through a two-year (2013–2014) beacon measurement of rain attenuation at 12.275 GHz at the Akure site. The ITU-R 618–13 (2017) rain attenuation model has been modified based on the rain attenuation beacon measurement. The modified ITU-R model has produced a least root mean square error (RMSE) of 6.4 when compared to the ITU-R model with 23.5 RMSE. The attenuation difference reduces as the frequency difference moves to the upper frequency bands. The ITU-R model overestimates the calculations from the GPM-derived results, which indicates the modification of the ITU-R model for the tropical location. Spatial variation of attenuation at 30 GHz revealed intensive and dry seasons exhibited the highest and lowest attenuation induced values, respectively. The results can be applied to power-enhanced satellite systems to achieve good signal availability in the study areas.

Coherent backscatter radar observations made at the Jicamarca Radio Observatory (JRO) have contributed significantly to our understanding of equatorial F-region irregularities. Radar observations, however, have been made predominantly at the Very-High Frequency (VHF) band (50 MHz), which corresponds to measurements of 3-m field-aligned irregularities. The deployment of the 14-panel version of the Advanced Modular Incoherent Scatter Radar (AMISR-14) at Jicamarca provided an opportunity for observations of Ultra-High Frequency (UHF - 445 MHz) echoes which correspond to measurements of irregularities with 0.34 m scale sizes. Here, we present what we believe to be the first report describing the quiet-time climatology of sub-meter equatorial F-region irregularities derived from UHF radar measurements. The measurements were made between August 2021 and February 2023 using a 10-beam AMISR-14 mode that scanned the F-region in the magnetic equatorial plane. The results show how F-region sub-meter irregularities respond to variations in season and solar flux conditions. The results also confirm, experimentally, that the occurrence of UHF F-region echoes is controlled by the occurrence of equatorial spread F (ESF). Higher occurrence rates were observed during pre-midnight hours and during Equinox and December solstice. Reduced occurrence rates were observed during June solstice. The results show that an increase in solar flux was followed by an increase in the altitude where noticeable occurrence rates ($\gtrsim$ 10%) start and in the maximum altitude of these occurrence rates. The observations also show that occurrence rates lasted longer (in local time) during low solar flux conditions. Comparisons with collocated VHF radar observations showed that, despite differences in radar parameters, observation days, and the scale size (one order of magnitude) of the scattering irregularities, the two systems show similar climatological variations with only minor differences in the absolute occurrence rates. Finally, the analysis of the occurrence rates for different beams did not show substantial climatological variations over local (within a few 100s of km) zonal distances around JRO. We point out, however, that observations on a single day can show strong local variations in echo detection and intensity within the AMISR-14 field of view due to the intrinsic development and decay of ESF structures.

This study analyzes the predictability of the solar modulation potential using time series models. Recently, new data sets for the modulation potential have become available, at daily, monthly, and annual resolutions. At lower frequencies, the data show the well-known 11-22-year cycle. Both the periodicity and amplitude vary over time. At higher resolutions, the probability distribution has heavy tails, while the data show the intermittent outliers characteristic of multifractal processes. Forecasting experiments are run using regressions in levels and differences, frequency domain methods, models with sinusoidal terms and neural networks. For the daily data, all the models achieve high degrees of accuracy at proximate horizons. As the horizon extends, accuracy falls away rapidly. At 27 days, corresponding to one solar rotation, a transfer function in differences achieves a more accurate forecast than either regressions or neural nets, since it is able to replicate the range of the data. At the annual resolution, both the regression and neural net predict well at horizons of 1 year. Again, forecast accuracy deteriorates sharply as the forecast horizon extends. At the monthly resolution, forecasting is problematic. The resolution is not low enough to bring out the low frequency cycles, but there is so much short-term dependence that the data are completely dominated by serial correlation. Any model incorporating proximate lags will generate inertial forecasts. Any model using lower frequency cyclical terms will be unable to pick up on near-term patterns. The forecasting skill of time series models appears limited to short horizons. The recommendation for forecasting over longer intervals is some combination of physics and statistical models.

Atmospheric gravity wave (AGW) characteristics were examined using Rayleigh lidar data collected over a period spanning 11 years above Logan, UT (41.7°N, 111.8°W), over an altitude range of 45–90 km. Variations of the relative density perturbations obtained with 3-km vertical resolution and 10-min temporal resolution are used to identify the presence of monochromatic gravity wave features throughout the mesosphere. The measured vertical wavelengths ${\lambda }_z$ ranged over 6–19 km with 12–14 km the most prevalent and the measured wave period $\tau$ ranged over 2–8 h with 5–6 h the most prevalent. The values of ${\lambda }_z$, $\tau$ and mean wind velocity u were used to infer vertical phase velocities $c_z$, horizontal wavelengths ${\lambda }_x$, horizontal phase velocities $c_x$ and horizontal distances to the source region x. There appears to be a clear seasonal dependence in $c_z$, $\tau$, $c_x$, ${\lambda }_x$, and x but not in ${\lambda }_z$. The $c_z$ values maximize in summer, $\tau$ and x maximize in winter whereas $c_x$ and ${\lambda }_x$, maximize in winter and summer but minimize in spring and autumn. The values of x ranged over 1300–5000 km for waves at 60 km and ∼2000–7500 km for waves at 90 km. The source of these AGWs is, thus, far away. Furthermore, for one of these monochromatic waves to exist all night or appear to extend over 45–90 km, it has to originate from a very extended region and persist for a long time.

Tornado rises rotating air columns extending from the bottom of cumulonimbus clouds to the ground, often accompanied by strong convection with thunderstorms, hail, and short-term heavy precipitation, which seriously threaten people's lives and property safety. Studying the characteristics of thunderstorm activity during a tornado is crucial for comprehending the atmospheric electrical mechanisms involved in its generation process and developing cooperative methods for tornado warning and forecasting. Based on the VLF/LF total lightning location system and radar echo data, this paper analyzes the spatial-temporal evolution, frequency, polarity, and height of total lightning during a strong tornado (EF3) in the Pearl River Delta region on June 3, 2014. The lightning activity lasted for about 3.5 h, with a total of 41,117 total lightning flashes, of which intra-cloud (IC) flashes accounted for 74.7%, cloud-to-ground (CG) flashes accounted for 21.6%, and narrow bipolar events (NBEs) accounted for 3.7%. Connected-Component Labeling (CCL) algorithm was used to divide the thunderstorm into four stages: initiation, development, maturation, and dissipation, and it was observed that the occurrence of tornadoes was closely related to total lightning activities. The observed characteristics of lightning activity in the tornado are summarized through comparison with other studies.

Earth observations through Global Navigation Satellite System (GNSS) and Remote Sensing (RS) technologies play a significant role in natural hazard surveillance, particularly in the context of earthquake prediction and detection. This study introduces a distinctive Deep Learning (DL) based approach to identify ionospheric and atmospheric precursors, utilizing data from multiple satellite sources and provides a comprehensive analysis of spatiotemporally varying precursors, contributing to the understanding and monitoring of seismic activity in earthquake-prone regions. In our investigation of the Morocco earthquake on September 08, 2023 (Mw 6.8), we analyzed various precursors including Total Electron Content (TEC), Air Pressure (AP), Relative Humidity (RH), Outgoing Longwave Radiation (OLR), and Air Temperature (AT). Our study aims to identify a synchronized anomalous window of potential earthquake precursors using Standard Deviation (STDEV), Continuous Wavelet Transform (CWT), and Long Short-Term Memory Inputs (LSTM) network. Both statistical and deep learning methods revealed abnormal fluctuations as precursors occurring within 8–9 days before the earthquake near the epicenter. Additionally, we detected geomagnetic anomalies in the ionosphere 6 days prior to and 4 days after the earthquake, coinciding with active geomagnetic storm days. This research underlined the importance of combining multiple earthquake precursors using statistical and deep learning approaches to support the understanding of the Lithosphere-Atmosphere-Ionosphere-Coupling (LAIC) phenomena.

This paper mainly examines the diurnal variation of the Total Electron Content (TEC) and critical frequency of the F2-layer (foF2) and their correlation with the height of the peak electron density (hmF2). This is carried out employing the observations (co-located Global Positioning System (GPS) and digisonde) and empirical models (International Reference Ionosphere, IRI, 2016 and IRI-extended to the Plasmasphere, IRI-Plas, 2017) in the low-to-high latitudes during relatively similar intense level geomagnetic storms that occurred during the high solar activity (February 19, 2014) and low solar activity (September 08, 2017). The GPS-derived TEC and digisonde-derived TEC, hmF2 and foF2 variabilities show large fluctuations on most of the stations when compared to the IRI 2016 and IRI-Plas 2017 variations. Moreover, the highest GPS-derived TEC values are observed when the hmF2 values reach in the ranges of about 270–309 km (low latitude), 203–266 km (mid latitude) and 259–311 km (high latitude) regions. The highest digisonde-derived TEC values are also depicted at the height ranges of about 256–451 km (low latitude), 250–326 km (mid latitude) and 309–388 km (high latitude) regions. In addition, the highest digisonde-derived foF2 values are observed when the hmF2 values reach about 253–384, 217–311 and 259–281 km in the low, mid and high latitudes, respectively. The model-derived TEC and foF2 variations also reveal that the highest values are generally observed at relatively similar height ranges with the observations. Moreover, the highest TEC and foF2 values are observed relatively at lower altitudes in the mid latitudes when compared to the low and high latitudes. The highest values also tend to move to the lower altitudes in shifting from the high to the low solar activity during similar intense level geomagnetic storms.