We introduce a novel Rayleigh Doppler lidar (RDLD) system that utilizes a high-power single-frequency laser with over 60 W average output power, achieved through fiber solid-state cascade amplification. This lidar represents a significant advancement by addressing common challenges such as mode hopping and multi-longitudinal mode issues. Designed for atmospheric wind and temperature profiling, the system operates effectively between altitudes of 30 km and 70 km. Key performance metrics include wind speed and temperature measurement errors below 7 m/s and 3 K, respectively, at 60 km, based on 30 min temporal and 1 km spatial resolutions. Observation data align closely with ECMWF reanalysis data, showing high correlation coefficients of 0.98, 0.91, and 0.94 for zonal wind, meridional wind, and temperature, respectively. Continuous observations also reveal detailed wind field variations caused by gravity waves, demonstrating the system’s high resolution and reliability. These results highlight the RDLD system’s potential for advancing meteorological monitoring, atmospheric dynamics studies, and environmental safety applications.

Nonrecurrent geomagnetic storms caused by Coronal Mass Ejection (CME) can induce serious impacts on space‐ and ground‐based equipment. However, these nonrecurrent geomagnetic storms are hard to predict since CMEs are not periodic. Previous studies have shown that the variations of Cosmic Ray Intensity (CRI) before nonrecurrent storms may forebode the coming geomagnetic storm. But it is difficult to extract the variations since the cosmic ray flux is a complex signal. In order to identify the precursory signal in CRI variations triggered by CME, an ensemble self‐adaptive time‐frequency analysis method was proposed and applied to 65 nonrecurrent geomagnetic storms occurred between 1998 and 2019. The results indicate that the precursory signals are successfully identified in 43 of 45 storms, after excluding 20 storms accompanied by ground level enhancement. In addition, it is also found that the spectral density of the precursory signal could reflect the active level of geomagnetic condition, which is lower during geomagnetic quiet period.

Predicting non‐recurrent geomagnetic storms caused by Coronal Mass Ejection (CME) is important and necessary for space weather forecasting. Previous studies have shown that it is feasible to predict non‐recurrent geomagnetic storms by reconstructing precursors from cosmic ray intensity (CRI) in the frequency domain. However, the difficulty lies in predicting the minor storms, the moderate storms, and the storms accompanying ground level enhancement (GLE). This study proposes a new method that includes the spectral whitening method and CEEMDAN‐CWT for predicting non‐recurrent geomagnetic storms. The method was applied to 229 CME‐driven events, including 166 events with Kp ≥ 5 and 63 events with Kp < 5, during the solar cycles 23 and 24. This study analyzed 166 geomagnetic storm events and found that 129 of them were accurately predicted, resulting in a recall rate of 77.7%. Additionally, the study found that as the Kp index increased, the amplitude of the precursor detected by this method also increased, while the time interval between the onset of CME and the maximum amplitude of the precursor decreased.

In the solar wind, the fluctuation of heavy ion abundance serves as a crucial physical metric. This not only mirrors the attributes of the solar wind’s originating solar region but also signifies its influence on Earth’s magnetosphere. Utilizing data from the Advanced Composition Explorer satellite, this investigation scrutinizes heavy ion variations in stream interaction region (SIR)- and interplanetary coronal mass ejection (ICME)-driven shocks. We further delineate the disparities in heavy ion fluctuations between these two types of interplanetary shocks across diverse solar activity cycles. Our findings reveal that ICME-driven shocks typically manifest elevated shock velocities and magnetic field strengths relative to their SIR-driven counterparts. Additionally, heavy ion abundance ratios, such as C⁶⁺/O⁴⁺, O⁷⁺/O⁶⁺, He/O, Si/O, and Fe/O, are consistently higher in ICME-driven shocks than in SIR-driven shocks. During varying solar activity cycles, these ratios surge postarrival of ICME-driven shocks. At solar maximum, these elevated ratios persist, whereas they revert to baseline levels swiftly during solar minimum. For SIR-driven shocks, the alteration in heavy ion abundance ratios is comparatively subdued, yet a noteworthy correlation with the solar activity cycle is evident.

During geomagnetic storms, which are the primary periods for heavy ions from the solar wind to enter Earth’s magnetospheric space, the charge state of solar wind heavy ions during these storms has significant implications for studying the distribution and effects of heavy ions in the magnetosphere. We analyzed the states and variations of heavy ions during 158 interplanetary coronal mass ejection (ICME)–driven geomagnetic storm events using data from the Advanced Composition Explorer satellite and examined four of these events in detail. We found that the increase in the average charge state of heavy ions such as O, Mg, Si, and Fe is positively correlated with the intensity of the geomagnetic storm. Regarding the abundance ratio of heavy ions such as Ne, Mg, Si, and Fe relative to oxygen ions, the rate and magnitude of increase in abundance ratios during extreme geomagnetic storms (Kp = 9) triggered by ICME events are significantly higher than those during other levels of geomagnetic storms. Additionally, we observed that although the average charge states of heavy ions such as O and Fe are correlated with the geomagnetic storm intensity induced by ICMEs, there are significant individual differences in the charge state variations of heavy ions.

Atmospheric gravity waves are one of the important dynamic processes in near space and are widely present in the atmosphere. They play a crucial role in the transfer of energy and momentum between different regions of the atmosphere. The Sun, as the ultimate source of gravity wave energy, significantly influences the intensity of gravity wave disturbances through its activity variations. This paper utilizes data from the Global Navigation Satellite System Occultation Sounder (GNOS) onboard the Fengyun-3C (FY-3C) satellite to invert global stratospheric gravity wave disturbances. It provides the global stratospheric gravity wave distribution from 2015 to 2023, nearly covering one solar activity cycle, and focuses on analyzing the response of gravity waves at different latitudes, altitudes, and wavelengths to the solar activity cycle. We found that short-wavelength gravity waves respond more noticeably to solar activity compared to long-wavelength gravity waves. Through analyzing the intensity of stratospheric gravity wave disturbances across different latitude bands, we found that in high-latitude regions, stratospheric gravity wave disturbances are most sensitive and respond most quickly to variations in solar activity. Furthermore, the Southern Hemisphere exhibits a stronger response to the current year’s solar activity changes compared to the Northern Hemisphere. In the mid-latitude and equatorial regions, the response to changes in solar activity intensity is delayed. The correlation gradually strengthens with this lag, reaching a very strong level after a 2-year lag. Additionally, the correlation between the Southern Hemisphere and solar activity is generally higher than that of the Northern Hemisphere.