Polar Mesospheric Clouds (PMCs), as ice crystal clouds formed in the middle and upper atmosphere (approximately 83 km high), have a seasonal onset that serves as an important parameter for studying the coupling processes between thermodynamics and dynamics in the polar mesosphere. Based on multi-source observational data from 1979 to 2023, the long-term evolution characteristics of the onset of PMCs in both hemispheres are systematically analyzed, and their correlations with the reversal time of stratospheric zonal mean wind and solar activity are examined. Results show that there are significant differences in the onset of PMCs between the two hemispheres: the interannual variation (with a standard deviation of 22 d) in the southern hemisphere is about twice that in the northern hemisphere (11 d), which may be related to differences in thermal and dynamic processes such as inter-hemispheric circulation modes and the intensity of gravity wave activity. In the southern hemisphere, the onset of PMCs season exhibits a very strong positive correlation with the reversal time of the stratospheric zonal mean wind, while in the northern hemisphere, although a negative correlation is observed, the approximately 60-day difference does not directly indicate a causal relationship between the two. The regulation of the onset by solar activity (Lyman-α radiation) also shows hemispheric asymmetry. In the northern hemisphere, there was a certain negative correlation with solar activity before 2011 that later weakened due to changes in the stratospheric dynamic background, whereas the southern hemisphere exhibited only a weak response. This indicates that both solar radiation effects and dynamic processes may jointly contribute. In addition, the discrepancies among multi-source data suggest that differences in detection systems and data types can introduce uncertainties in studies of the long-term variation characteristics of PMCs.

This review systematically summarizes recent advances in filmwise and dropwise condensation under microgravity, elucidating two-phase heat transfer mechanisms and gravitational influence patterns. For condensing heat transfer in tubes, gravity-independent criterion numbers (Bond number, Froude number, etc.) are used to determine whether gravity affects heat transfer, and the effect of gravity can be attenuated by increasing the mass flow rate of the vapor and reducing the tube diameter. In microgravity environments, dropwise condensation can be achieved through vapor flow acceleration combined with functional surfaces and air-blowing techniques for condensate removal. Current experimental studies on microgravity condensation remain limited due to challenges in obtaining sustained microgravity conditions. The paper emphasizes the necessity of conducting long-term condensation experiments utilizing orbital platforms like the China Space Station and International Space Station to address data reproducibility issues, investigate gravity-dependent mechanisms, and provide theoretical foundations for space two-phase thermal management systems.

The Low-Energy Ion Analyzer (LEIA) and Low-Energy Electron Analyzer (LEEA), integral components of the Chang’E-7 lander’s lunar surface environment detection system, conduct in-situ measurements of low-energy charged particles (0.001～30 keV) to elucidate solar wind-regolith interaction mechanisms, investigate microstructure evolution in the lunar near-surface plasma environment, and support space-environment assessment for future lunar research stations. Employing identical hemispherical electrostatic analyzers with asymmetric electrostatic deflectors, both analyzers achieve wide-field detection (90°×360° FOV), broad energy coverage, and voltage-controlled variable geometric factors. Ground calibration using standard plasma beam sources confirmed compliance with mission requirements: energy resolution <15% (ΔE/E), dynamic flux range spanning seven orders of magnitude, and angular resolution <15°×22.5°, collectively enabling comprehensive characterization of lunar surface plasma phenomena.

The Kp index is a parameter designed to indicate the level of global geomagnetic disturbances originating from the interaction of the solar wind with the magnetosphere. The index is defined at 3-hour intervals and has 28 levels. Kp is a global version of the local K index, which was conceived by Bartels and is commonly used in scientific research of the solar-terrestrial relationship. The continuity of the index over 50 year makes it particularly valuable in studies of solar-cycle variations and other long-term effects on interplanetary and magnetospheric phenomena. For example, Kp has been used in studies of solar wind shock waves, the interplanetary magnetic field, plasma density variations in the magnetosphere, and magnetospheric ULF waves. In addition, the index is widely used as an input to magnetospheric/ionospheric models. For example, the plasmapause is modeled to move closer to the Earth with increasing Kp. The location of substorm injection is modeled to have a similar Kp dependence. The magnetic field model of Tsyganenko has an explicit Kp dependence, and the magnetotail becomes more stretched for higher Kp. These models are used both in scientific research and in monitoring and predicting space weather. In 2011, the National Space Science Center of the Chinese Academy of Sciences established the Chinese Academy of Sciences Space Environment Monitoring Network, which included Mohe, Beijing, Langfang, Sanya, and Fuke stations. A geomagnetic Kp_est index, which can effectively identify the day-to-day variation characteristics of the geomagnetic regular daily variation, reflect the seasonal and local time effects of geomagnetic disturbances, and is suitable for the distribution characteristics of China’s geomagnetic observatory network, has been developed through the integration and processing of the H-component monitoring data from fluxgate magnetometers at these five geomagnetic observatory stations. This dataset contains the geomagnetic Kp_est indices for the five geomagnetic observatory stations from 2022 to 2024. It addresses the current situation where the official Kp index is released with a two-week delay, failing to meet operational requirements, and can provide data support for space weather forecasting services.

Due to the inherent limitations of current remote sensing techniques, the actual occurrence and accurate abundance of water ice in lunar regolith cannot be directly identified, making in-situ verification urgently necessary. The Chang’E-7 mission of China’s Lunar Exploration Program plans to conduct water ice detection at the lunar south pole, where an in-situ micro-sampling device mounted on the rover will perform quantitative collection of lunar regolith for the volatiles in-situ measurement instrument. However, the uncertainty of lunar surface conditions leads to considerable dispersion in sampling mass. Moreover, water ice sublimation loss caused by tool-soil temperature difference and mechanical interactions during sampling will further reduce the detection accuracy. To ensure the reliability of detection data from the volatiles measurement instrument, this paper proposes calibration methods for sampling mass and water ice loss. Icy lunar regolith simulant is prepared via vapor deposition during sampling, and sampling mass calibration experiments are carried out using a self-developed calibration device. Preliminary results show that sampling mass varies significantly with regolith particle size distribution. Further research will be conducted on the physical mechanism of icy lunar regolith sampling under multi-factor coupling conditions. This study aims to provide a high-confidence physical response parameter spectrum for accurate interpretation and scientific analysis of Chang’E-7 in-orbit data.

The Chang’E-7 spacecraft is scheduled to be landed in the Aitken Basin region of the lunar south pole to conduct comprehensive exploration and research on the lunar surface environment. As one of the main detectors onboard the Chang’E-7 spacecraft, a lunar dust detector is developed for in-situ measurements of naturally suspended dust in the polar region, key parameters such as the particle size, velocity, and cumulative mass flux will be obtained. To achieve high-precision scientific detection, systematic ground calibration experiments were conducted. For particle size calibration, a single-particle free-fall method combined with an equivalent test scheme using neutral density filters was employed, achieving coverage of the particle size range from 1 µm to 5000 µm. Experimental results demonstrate that the particle size retrieval error does not exceed 17%. Velocity calibration was performed by measuring the time-of-flight of free-falling particles from different heights, yielding a velocity measurement error within 13%. For mass flux calibration, the solution titration method was used to obtain the sensitivity of the Quartz Crystal Microbalances, with sensitivities in three orthogonal directions all on the order of 10^–9 g·Hz^–1·cm^–2 and exhibiting good linearity. Furthermore, temperature-frequency correction curves were established to support the normalization of in-orbit data. The calibration results indicate that the performance indicators of the dust detector meet the requirements for detection in the extreme environment of the lunar south pole. The established calibration methods and retrieval models provide a reliable foundation for the interpretation of subsequent in-orbit scientific data.

In response to the performance impact of long cable signal transmission between the search coil and the preamplifier circuit, this paper establishes for the first time a circuit equivalent model of Search Coil-Cable-Preamplifier Circuit. Through simulation analysis and experimental verification, the influence of cable length on the frequency distribution of sensor noise is revealed. Theoretical analysis indicates that cable length has limited impact on sensor sensitivity, but significantly increases the noise level in the high-frequency band (>1 kHz). Based on a prototype search coil magnetometer with a target specification of 10～1000 Hz bandwidth and 30 fT·Hz^1/2 (1 kHz) noise, the variation law of noise with cable length is validated. Experimental results show that as the cable length increases from 3 m to 39 m, the noise corner frequency shifts forward from 7.5 kHz to 2 kHz, while the high-frequency noise at 10 kHz increases by a factor of six. The study finds that an increase in cable length has a significant impact on the noise of inductive magnetometers, specifically manifested as a slight improvement in low-frequency noise and a sharp deterioration in high-frequency noise. Although cable length has a notable effect on inductive magnetometers, its influence can be predicted and mitigated through theoretical modeling incorporating cable parameters. This research provides critical parameter basis for the engineering implementation of search coil magnetometers in space exploration scenarios requiring long-cable applications.

After the Chang’E-7 lunar microwave imaging radar in the fourth phase of the Lunar Exploration Project is put into on-orbit operation in the future, calibration devices will not be deployed on the lunar surface, making on-orbit External calibration impossible. To ensure the acquisition of high-precision lunar surface image data, a ground calibration method is proposed. This method combines the internal calibration of the radar system with the performance calibration in the inner field. During ground testing, the internal calibration accuracy and the consistency of internal calibration channels are obtained by measuring the temperature characteristics of the internal calibration network under a full-temperature environment. The internal calibration constants are acquired in an anechoic chamber. By constructing a wireless transceiver environment in the inner field with the help of the anechoic chamber, the absolute transceiver gains and the stability of the transceiver channels of the system are accurately calibrated. The basic data obtained through ground calibration can be used for the calibration of indicators such as on-orbit internal calibration constants, absolute and relative radiation accuracy, and polarization channel consistency, providing guarantee for high-resolution lunar surface exploration.

As a key indicator of global climate change and an essential freshwater resource, the accurate acquisition of multiple physical parameters of glaciers holds significant importance for global climate change research, ecological conservation, and water resource planning. In China, glaciers are predominantly mountain glaciers distributed in high-altitude regions. Constrained by harsh environments and complex terrain, traditional in-situ detection methods fail to achieve large-scale continuous monitoring of internal glacier parameters. Satellite-borne glacier remote sensing, meanwhile, faces limitations in resolution and interference from complex ground clutter in mountainous glacier regions, and thus has yet to be operationalized. Airborne radar, with its superior spatial resolution and flexible detection capabilities, has become a critical technical tool for glacier monitoring and research. However, airborne detection of mountain glaciers still confronts challenges posed by undulating ice surfaces and complex subglacial topography: scattering clutter from the uneven ice surface interferes with radar signal interpretation and precise inversion of key parameters, while the intricate subglacial structure and scattering losses caused by ice surface topography interact with dielectric losses within the ice, impeding accurate inversion of glacier dielectric constants. To address these challenges, this study integrates airborne ultra-wideband radar detection data from mountain glaciers with the Pseudo-Spectral Time Domain (PSTD) numerical simulation method. A coupled model of ice surface-subglacial dual interface topography and dielectric parameters is established. Through two-dimensional PSTD electromagnetic simulations, the interaction mechanism between topographic scattering and ice dielectric loss is elucidated. Furthermore, an inversion method for the imaginary part of the ice layer dielectric constant in measured regions is proposed based on dynamic range analysis. For the measured data from Laohugou Glacier No. 12, iterative optimization converges the estimated imaginary part value to 6.0×10^–4. The relative error between the estimated imaginary part and the theoretical mean is 21%. Cross-validation between simulation results and theoretical models demonstrates that this method effectively improves the inversion accuracy of glacier dielectric parameters in complex terrain by decoupling the synergistic interference between topographic relief and dielectric parameters, thereby offering a viable solution for studying internal dielectric properties of glaciers.

The Chang’E-7 mission carries a Lunar Penetrating Radar (LPR) for investigating lunar shallow subsurface structures. To ensure the validity of the acquired data and improve the accuracy and consistency of its interpretation, this study presents a comprehensive calibration framework suitable for space-grade penetrating radar systems, incorporating full-system gain calibration and system transfer function calibration, among others. Applying this methodology, the lunar radar system was rigorously calibrated, clarifying the optimal parameter configuration for its in-orbit operation. Under this parameter setting, all performance metrics of the radar system meet the design requirements: the system gains of the Low-Frequency (LF) and High-Frequency (HF) channels are 171.02 dB and 169.70 dB, respectively, fulfilling the detection depth requirements of 400 m and 40 m. The acquired Time-Varying Gain (TVG) curve and system transfer function, validated through simulated lunar regolith experiments, can provide effective calibration baselines for scientific data obtained during lunar surface exploration. This calibration scheme can serve as a technical reference for the calibration of radar systems in future deep-space exploration missions.