The Fengyun-3G (FY-3G) satellite, launched on 16 April 2023, carries China’s first spaceborne dual-frequency Precipitation Measurement Radar (PMR). This study aims to evaluate the precipitation detection capabilities of the PMR by comparing its observations of rain cells with those from a Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) Core Observatory, thereby validating the performance of the new Chinese PMR against an internationally recognized standard. Using rain cell identification and minimum bounding rectangle fitting methods, we analyze the morphological and physical parameters of rain cells observed by both radars during the boreal summer (June–August) of 2024 over tropical (20°S–20°N), subtropical (20°–40°N), and mid-latitude (40°–52°N) regions. The results show good consistency between the two instruments in the distribution patterns of most geometric parameters, including length, width, horizontal shape index, and area. However, systematic differences are found in vertical structure and precipitation intensity: the PMR detects higher echo-top heights and a broader range of rain rates, particularly for convective precipitation, and exhibits larger standard deviations in both geometric and physical parameters due to its wider swath and potentially higher sensitivity. Geographically, both radars consistently reveal that tropical rain cells are predominantly convective, while mid-latitude rain cells are largely stratiform. Moreover, rain cells over land tend to be vertically elongated and horizontally narrow (lanky), whereas those over ocean are vertically compact and horizontally broad (squatty). The spatial distributions of the horizontal shape index and three-dimensional morphological index derived from the PMR and DPR show consistent geographical patterns, with a stronger linear correlation for the three-dimensional index. These findings demonstrate that the FY-3G PMR provides reliable and advanced precipitation observations comparable to the GPM DPR, confirming its capability to deliver high-quality data for global precipitation monitoring and research.

Limb sounding can provide fine vertical profiles of atmospheric constituents, while tangent height (TH) offsets are the primary source of uncertainty in limb sounding. Due to the absence of a star tracker, the Ozone Monitoring Suite-Limb (OMS-L) aboard the Fengyun-3F (FY-3F) satellite cannot provide direct geometric references for TH validation, making it difficult to quantify the TH offsets. In this paper, an in-orbit TH validation and correction algorithm is developed for OMS-L based on the vertical structure of ultraviolet limb-scattered radiance (LSR) profiles. The knee of the LSR profile at 305 nm is employed as an equivalent TH reference, enabling rapid determination and correction of TH offsets. Sensitivity analysis indicates that the algorithm accuracy is within ±300 m, and the impact of algorithm uncertainty on the 320-nm LSR simulations and the ozone profile retrievals is within ±4% and ±8%, respectively. The above algorithm is applied to OMS-L TH data from November 2024 to March 2025. The results show that OMS-L TH offsets generally remain within ±1 km. After TH correction, the LSR simulations show better agreement with the measurements, with a correlation coefficient of 0.973.

Since the launch of China’s Fengyun-3 (FY-3) satellite series in 2008, the on-board Microwave Temperature Sounders (MWTS) have provided critical atmospheric sounding data for numerical weather prediction and extreme weather monitoring. However, their application in climate research remains limited. To establish long-term Fundamental Climate Data Records (FCDRs) for FY-3 satellites—the core foundation of climate research—a comprehensive assessment of data consistency between China’s FY-3 satellites and the U.S. NOAA satellites is essential. This study systematically evaluates the inter-satellite consistency between FY-3 MWTS observations and three datasets of NOAA FCDRs, focusing on comparison of brightness temperatures and their anomalies over the extended period of 2009–2024. In accordance with the Global Climate Observing System (GCOS) Essential Climate Variables (ECVs) requirements (GCOS-245), the accuracy and stability of both operational and recalibrated FY-3 brightness temperatures are quantified on a global grid scale, using multiple statistical metrics including root mean square error (RMSE), standard deviation (SD), bias, and linear trend. The key findings are as follows. (1) FY-3 MWTS observations can effectively capture the characteristic seasonal cycles and vertical atmospheric structures of brightness temperatures, confirming their basic reliability in climate-related analyses. (2) Significant discontinuities in brightness temperatures are observed in the upper troposphere and lower stratosphere for earlier FY-3 satellites (FY-3A/3B/3C), indicating limitations in their long-term climate consistency, while newer satellites (FY-3D/3E/3F) show substantially improved consistency with NOAA FCDRs. (3) The recalibrated data of FY-3D exhibit a marked quality improvement, with RMSE reduced by 60% compared to FY-3D operational observations, and this recalibrated FY-3D dataset is recommended as the preferred choice for climate applications. (4) Even the operational (non-recalibrated) brightness temperature data of FY-3D achieves remarkable consistency with global benchmarks, boasting a global mean accuracy of 0.270 ± 0.039 K, which fully meets the accuracy thresholds specified by GCOS for ECVs. (5) For specific MWTS channels, the global mean brightness temperatures of Channel 4 (over oceans), Channel 6, and Channel 9 generally meet the stability requirements for climate monitoring, further supporting their utility in long-term climate studies. (6) Larger RMSEs of FY-3D operational data are identified in two key regions: the stratosphere over high latitudes and the mid troposphere over topographically complex areas (e.g., the Qinghai–Xizang Plateau, the Andes Mountains, and parts of Africa). These discrepancies are attributed to two technical factors: non-linearity in the MWTS calibration process and orbital drift of the FY-3 satellites. This study validates the climate monitoring capabilities of FY-3 MWTS observations, clarifies key directions for data quality improvement, and lays an important foundation for the transformation of this data from product generation to climate applications.

The Visible and Infrared Radiometer (VIRR) onboard China’s Fengyun-3A/B/C (FY-3A/B/C) satellites has delivered essential global Earth observations for over 15 years, enabling critical applications in cloud dynamics research, vegetation assessment, and environmental monitoring. However, VIRR lacks onboard calibration systems for its visible/near-infrared channels, which results in progressive radiometric degradation due to cumulative space radiation and detector aging, challenging the generation of stable long-term climate datasets [e.g., the fundamental climate data record (FCDR)]. By integrating simultaneous nadir overpass (SNO) cross-calibration technique with references from Aqua’s Moderate Resolution Imaging Spectroradiometer (MODIS), we identified pronounced seasonal fluctuations in long-term recalibration coefficients, particularly for the 0.86 μm. To isolate these effects, singular spectrum analysis (SSA) was used to decompose the coefficient series into three components: trend, seasonal fluctuations, and residuals. A hybrid calibration model was then formulated by integrating the isolated trend and seasonal features. Validation across globally distributed pseudo-invariant sites confirmed enhanced radiometric stability. The work highlights the necessity of accounting for seasonally modulated calibration artifacts, which were previously unaddressed in operational protocols, to ensure the stability and accuracy of climate data records (CDRs).

Microwave radiance data assimilation (DA) enhances initial conditions for numerical weather prediction (NWP) and shows great potential for improving forecasts in tropical regions like East Africa, where observational data scarcity and complex tropical dynamics present significant challenges. Effectiveness of radiance assimilation is a function of variations in channel sensitivity to local atmospheric conditions and region-specific bias characteristics. However, microwave radiance assimilation in Limited-Area Models (LAMs) over East Africa remains largely unexplored. This study investigates the impact of assimilating microwave radiance channels with weighting functions peaking in the troposphere and lower stratosphere on rainfall forecasts over East Africa from a five-satellite constellation: the Microwave Temperature Sounder-2 (MWTS-2) onboard Fengyun-3D (FY-3D), the Advanced Technology Microwave Sounder (ATMS) onboard JPSS, and the Advanced Microwave Sounding Unit-A (AMSU-A) onboard NOAA-15/18/19 satellites. The 6-h cycling DA experiments over a convectively active 15-day period show that assimilation of ATMS and AMSU-A radiances enhances representation of initial conditions, thereby reducing analysis and forecast errors. Assimilation of MWTS-2 radiances improves the analysis and forecasts further, especially for the tropospheric thermodynamic fields. The joint multi-microwave assimilation fills critical observation gaps over East Africa, allowing realistic simulations of diurnal precipitation trends, and capturing rainfall intensities exceeding 50 mm in 24 h, especially for T+12-h to T+24-h lead times. These findings are validated by a high-intensity rainfall case over Mandera, where spatio–temporal consistency is observed in instability and convection triggering. Forecast evaluation metrics have confirmed enhanced rainfall forecast skill for deep and rapidly developing convective systems. The study provides valuable insights into the gains of assimilating microwave radiance data over tropical regions, particularly in East Africa.

Meteorological observation technology serves as a foundational pillar of contemporary atmospheric science, which has propelled the development of atmospheric science and the advancement of related services. During the initial formation period of modern meteorological science in China in the 1920s, the older generation of meteorologists proposed that the purpose of the Meteorological Society is "to seek the progress of meteorological science and the development of meteorological observation undertakings". The meteorological observation system has experienced a leap-forward development from rudimentary inception to automated operations and from surface to space. A relatively complete diversified observation system has been formed, covering surface observations, upper-air soundings, satellite remote sensing, and other aspects. The progress of science and technology has driven a continuous development of meteorological observation, significantly improving the accuracy and timeliness of weather forecasting. This article provides an overview of the development history, current status, and future development trends of the meteorological observation system from eight aspects, including surface observations, upper-air soundings, marine observations, space weather observations, weather radars, meteorological satellites, and ground- and air-based remote sensing systems. As an important innovative driving force for the development of meteorological observation technology and the research of atmospheric sounding methods as well as the construction of observing equipment systems, meteorological observation field experiments have played an important leading and technical supporting role in the upgrade of observation systems. Therefore, this article also briefly introduces the situation of multi-source comprehensive observation and large-scale field experiments in China. The meteorological observation systems are not only an application of current engineering technologies, but also a scientific discipline itself that is full of unknown scientific problems, technical challenges, and development in application fields. With advances in observation technology and application of high-precision sensors and more advanced remote sensing equipments, the existing observation equipment needs to be continuously upgraded to stay at the forefront of technology and ensure the accuracy of data. The meteorological observation systems are developing in the direction of greater intelligence, three-dimensionality, and global integration, while frontier technologies such as big data, artificial intelligence, and quantum technology will play important roles in the future development of meteorological observation systems.

Atmospheric inversion layer will hinder the development of vertical movement. Traditionally, only ground-based radiosonde data are used for monitoring and analyzing the atmospheric inversion layer. Spaceborne hyperspectral infrared atmospheric sounding can retrieve atmospheric temperature and humidity profiles in clear sky condition, which provides a possible technique for monitoring the atmospheric inversion layer. In order to explore the method of monitoring inversion layer using domestic satellite data, the RTTOV fast radiative transfer model is used to simulate the FY-3D/HIRAS observation spectrum, including the effects of different inversion strength and height of the inversion layer top on the brightness temperature observed by HIRAS. The results show that the channels corresponding to the fine spectral lines in the window region of 780—1000 cm⁻¹ are most sensitive to the inversion layer, and the brightness temperature difference between the observed channel and the reference channel (926.875 cm⁻¹) can be used to identify the atmospheric inversion layer. The sensitivity index of inversion strength and the sensitivity index of the height of the inversion layer top are defined in this study. Simulation results show that the sensitivity indices of inversion strength at strong absorption (784.375 cm⁻¹, 798.750 cm⁻¹), medium absorption (803.125 cm⁻¹, 852.500 cm⁻¹) and weak absorption (840.000 cm⁻¹, 871.250 cm⁻¹) channels are 0.49, 0.48 and 0.30, and the sensitivity indices of the height of the inversion layer top are 0.045, 0.036 and 0.018, respectively. Based on the brightness temperature of the strong absorption channels, the inversion strength and the height of the inversion layer top can be retrieved, and the correlation of the channel brightness temperature with inversion strength is higher than that with the height of the inversion layer top. The results verify the applicability of using infrared hyperspectral channel brightness temperature data to study the inversion layer structure, and provide a basis and reference for subsequent retrievals of the inversion characteristics.