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.

The parameterization of raindrop size distribution (DSD) is critical for the satellite precipitation retrieval algorithms. Utilizing the multiple ground-based two-dimensional video (2DVD) and Particle Size and Velocity (Parsivel) disdrometers data from the Precipitation Validation Network (Guangdong) of the Fengyun satellites during April–September 2024, this study evaluates the uncertainty of DSD parameterization on a dual-frequency (DF) precipitation retrieval algorithm over South China. It is shown that the composite raindrop spectra generally conform to the gamma distribution, with the shape parameter μ on average of 4.5–4.8, which is higher than the fixed μ = 3 used in the Global Precipitation Measurement mission (GPM) Dual-Frequency Precipitation Radar (DPR) algorithms. By varying the μ value in the DSD gamma model, the effects on the retrieved mass-weighted mean diameter (D_m), normalized intercept parameter (N_w), and rain rate are examined. As μ increases from 1 to 6, the underestimation of D_m shifts to overestimation, while for lgN_w and rain rate, it is the opposite. The overestimation of rainfall, especially at the range of 8–32 mm h⁻¹, mainly comes from underestimated D_m and overestimated lgN_w. On the contrary, overestimation of D_m and underestimation of lgN_w mainly lead to underestimated rainfall, especially when rain rate is above 64 mm h⁻¹. Comprehensive analysis shows that the DSD gamma distribution with μ in the range of 4–5 may be more suitable for South China. These results provide valuable reference for optimizing the DSD module of the precipitation retrieval algorithm for the Fengyun-3G (FY-3G) satellite.

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).

By combining the bright band model used in the GPM retrieval algorithm and Mie scattering calculation, the lookup table of scattering functions is generated for three types of precipitation, i.e., solid precipitation, liquid precipitation and mixed phase precipitation. The accuracy of the lookup table is verified by comparing with the measured data of GPM. The result shows that the maximum deviation of scattering calculation is less than 0.5 dB. Based on the lookup table, the frequency correction from spaceborne Ku band radar to S-band radar is completed. The analysis of the scattering function shows that the frequency correction from Ku band to S band depends on the phase and spectral parameter $D_{\mathrm{m}}$. Among them, the frequency correction of liquid precipitation is mainly negative, and the maximum is not more than −3 dB. The frequency correction of mixed phase precipitation varies significantly with the height of the 0℃ bright band. The frequency correction of solid precipitation is positive without a 0℃ bright band. When there is a 0℃ bright band, it changes significantly with temperature. The method proposed in this paper can be used to realize the frequency correction between satellite and ground radars in different bands, and provide effective support for consistency inspection of detection accuracy of spaceborne radar.