The radio-occultation technique can provide vertical profiles of planetary ionospheric and atmospheric parameters, which merit the planetary-climate and space-weather scientific research so far. The Tianwen-1 one-way single-frequency radio-occultation technique was developed to retrieve Mars ionospheric and atmospheric parameters. The first radio-occultation event observation experiment was conducted on 5 August 2021. The retrieved excess Doppler frequency, bending angle, refractivity, electron density, neutral mass density, pressure and temperature profiles are presented. The Mars ionosphere M1 (M2) layer peak height is at 140 km (105 km) with a peak density of about 3.7 × 10¹⁰ el/m³ (5.3 × 10¹⁰ el/m³) in the retrieved electron-density profile. A planetary boundary layer (−2.35 km~5 km), a troposphere (temperature decreases with height) and a stratosphere (24 km–40 km) clearly appear in the retrieved temperature profile below 50 km. Results show that Tianwen-1 radio occultation data are scientifically reliable and useful for further Mars climate and space-weather studies.

The stratospheric environmental responses to solar storms (SENSORs) campaign investigates the influence of solar storms on the stratosphere. This campaign employs a long-duration zero-pressure balloon as a platform to carry multiple types of payloads during a series of flight experiments in the mid-latitude stratosphere from 2019 to 2022. This article describes the development and testing of an acoustic anemometer for obtaining in situ wind measurements along the balloon trajectory. The anemometer is also equipped with temperature, pressure, and humidity sensors from a temperature–pressure–humidity measurement module (TPH module), inherited from a radiosonde developed for sounding balloons. The acoustic anemometer and other sensors were used in a flight experiment of the SENSOR campaign that took place in the Dachaidan District (95.37°E, 37.74°N) on September 4, 2019. 3-D wind speed observations, which were obtained during level flight at an altitude of around 25 km, are presented. A preliminary analysis of the measurements yielded by the anemometer is also discussed. To our knowledge, this is the first time that wind measurements were obtained by an acoustic anemometer during level flight of the high-altitude balloon and were used to analyze the Lagrangian spectrum in the inertial subrange over the Tibetan Plateau. In addition to wind speed measurements, temperature, pressure, and relative humidity measurements during ascent are compared to observations from a nearby radiosonde launched four hours earlier, and the results show very good agreement.

Stellar occultation instruments detect the transmission of stellar spectra through the planetary atmosphere to retrieve densities of various atmospheric components. This paper introduces an idea of using instruments with bandpass filters for stellar occultation detection. According to the characteristics of the occultation technique for oxygen density measurement, a full-link forward model is established, and the average transmission under a typical nocturnal atmosphere is calculated with the help of the HITRAN database, occultation simulation and a 3D ray-tracing program. The central wavelength and bandwidth suitable for 760 nm oxygen A-band absorption measurement are discussed. This paper also compares the results of the forward model with GOMOS spectrometer data under this band, calculates the observation signal-to-noise ratio corresponding to different instrument parameters, and target star magnitudes. The results of this paper provide a theoretical basis for the development of a stellar occultation technique with a bandpass filter and guidance on the instrument design.

The stellar occultation technique is capable of atmospheric trace gas detection using the molecule absorption characteristics of the stellar spectra. In this paper, the non-iterative and iterative retrieval methods for oxygen and air density detection by stellar occultation are investigated. For the single-band average transmission data in the oxygen 761 nm A-band, an onion-peeling algorithm is used to calculate the effective optical depth of each atmospheric layer, and then the optical depth is used to retrieve the oxygen number density. The iteration method introduces atmospheric hydrostatic equilibrium and the ideal gas equation of state, and it achieves a more accurate retrieval of the air density under the condition of a priori temperature deviation. Finally, this paper analyzes the double solution problem in the iteration process and the ideas to improve the problem. This paper provides a theoretical basis for the development of a new type of atmospheric density detection method.

As a critical trace gas and a sensitive indicator of climate change, water vapor (H₂O) plays a pivotal role in regulating the Earth’s radiative budget and middle-atmospheric chemical cycles. In this study, H₂O measurements from the Sounding of the Atmosphere using a Broadband Emission Radiometry (SABER) instrument on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite are analyzed to characterize the H₂O spatiotemporal distribution throughout the stratosphere–mesosphere–lower thermosphere (SMLT) region. Using eigen analysis, the bimonthly mean H₂O across different latitude bins between 2002 and 2025 is decomposed into four empirical orthogonal functions (EOFs). Results indicate that stratospheric water vapor remains relatively stable with weak latitudinal dependence, whereas H₂O in the mesosphere–lower thermosphere (MLT) at middle-to-high latitudes exhibits pronounced seasonal variations and distinct hemispheric antisymmetry. The first mode captures a global H₂O long-term increasing trend. Both EOF1 and EOF2 are associated with solar activity and the El Niño–Southern Oscillation (ENSO) to varying degrees, indicating that these dominant modes are driven by multiple concurrent forcing factors. EOF3 correlates with the Quasi-Biennial Oscillation (QBO), suggesting links to QBO-driven atmospheric dynamical processes, whereas EOF4 demonstrates no significant associations with natural activity indices, suggesting perturbations arising from alternative atmospheric mechanisms. By systematically applying EOF analysis to a 24-year dataset of H₂O observations in the SMLT region, this study characterizes the principal distribution patterns and evolutionary characteristics of SMLT H₂O. Through correlation analyses with natural forcing indices, the complex driving mechanisms governing its variability are elucidated. This work provides a comprehensive observational framework for SMLT water vapor variability, enhancing assessments of SMLT H₂O responses to long-term climate change and refining the understanding of the Earth–atmosphere system. Furthermore, these findings provide critical data support for the subsequent development and optimization of SMLT water vapor models.

Precise characterization of the thermospheric neutral wind is essential for comprehending the dynamic interactions within the ionosphere-thermosphere system, as evidenced by the development of models like HWM and the need for localized data. However, numerical models often suffer from biases due to uncertainties in external forcing and the scarcity of direct wind observations. This study examines the influence of incorporating actual neutral wind profiles from the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) on the Ionospheric Connection Explorer (ICON) satellite into the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE-GCM) via an ensemble-based data assimilation framework. To address the challenges of assimilating real observational data, a robust background check Quality Control (QC) scheme with dynamic thresholds based on ensemble spread was implemented. The assimilation performance was evaluated by comparing the analysis results against independent, unassimilated observations and a free-running model Control Run. The findings demonstrate a substantial improvement in the precision of the thermospheric wind field. This enhancement is reflected in a 45–50% reduction in Root Mean Square Error (RMSE) for both zonal and meridional components. For zonal winds, the system demonstrated effective bias removal and sustained forecast skill, indicating a strong model memory of the large-scale mean flow. In contrast, while the assimilation exceptionally corrected the meridional circulation by refining the spatial structures and reshaping cross-equatorial flows, the forecast skill for this component dissipated rapidly. This characteristic of “short memory” underscores the highly dynamic nature of thermospheric winds and emphasizes the need for high-frequency assimilation cycles. The system required a spin-up period of approximately 8 h to achieve statistical stability. These findings demonstrate that the assimilation of data from ICON/MIGHTI satellites not only diminishes numerical inaccuracies but also improves the representation of instantaneous thermospheric wind distributions. Providing a high-fidelity dataset is crucial for advancing the modeling and understanding of the complex interactions within the Earth’s ionosphere-thermosphere system.