Data gaps exist in the measured spectral reflectance and atmospheric data from the Radiometric Calibration Network (RadCalNet) due to instrument malfunctions or weather-related interferences, which severely impedes the application of the data. Therefore, developing a method to fill these missing RadCalNet data is a pressing issue. This study focuses on four RadCalNet sites with distinct surface types and proposes a high-precision Bottom-of-Atmosphere (BOA) spectral reflectance model. With on-site atmospheric data from RadCalNet, the predicted results achieve a Root Mean Square Error (RMSE) of no more than 1.26%. In scenarios where in-situ atmospheric conditions are completely missing, the ERA5 dataset is used as a substitute and validated with Landsat 8 surface reflectance products; the absolute errors for all sites did not exceed 4.58%, validating the proposed method’s effectiveness. Additionally, the importance of input parameters and the impact of their uncertainties on prediction accuracy are discussed.

The Medium Resolution Spectral Imager-III (MERSI-III), the third generation of the MERSI series, began observations from the Feng Yun-3F (FY-3F) in a sun-synchronous morning orbit on August 3, 2023. MERSI-III collects data from 25 spectral bands, including 19 reflective solar bands (RSBs) and 6 thermal emissive bands with wavelengths ranging from 0.4 to 2.15 μm and 3.7 to 12.5 μm, respectively. Compared with its predecessors, MERSI-III features an enhanced on-orbit calibration capability for RSBs thanks to the incorporation of a newly designed visible on-board calibrator (VOC). This VOC is a solar diffuser (SD)-based on-board calibration system consisting of an SD panel, a solar attenuation plate positioned in front of the SD panel, and an on-board SD degradation monitor. We provide an overview of the MERSI-III instrument, its VOC functions, and the corresponding on-orbit calibration methodologies. The performance of the on-orbit calibration is also assessed using a wide dynamic-integrated vicarious calibration (VC) technique, which combines multiple VC methods, including inter-comparison using invariant pixels, absolute calibration with pseudo-invariant calibration sites, and Rayleigh scattering calibration. Based on three months of validation results, the on-orbit calibration demonstrates strong performance in both absolute accuracy and radiometric stability. Among the 14 validated RSBs, 13 bands meet the basic calibration accuracy requirement of a calibration bias of less than 5%, while 7 bands meet the desired requirement of a calibration bias of less than 3%.

The Chinese early-morning-orbiting Fengyun-3E (FY-3E) satellite fills the 6-h initial observation window for data assimilation in numerical weather prediction (NWP). The low-light band (LLB) on the medium-resolution spectral imager low light (MERSI-LL) of FY-3E can detect extremely low radiances at night, significantly enhancing nighttime observation capabilities as well as elevating data assimilation quality by improving the nighttime cloud mask algorithm. However, severe and nonlinear stray light contamination affects most nocturnal FY-3E/MERSI-LL LLB images, particularly those from the Southern Hemisphere, hindering further visualization applications. The analysis concluded that the stray light is closely associated with the refraction and reflection of sunlight entering the MERSI-LL, solar zenith angle (SZA), and detector number. To obtain clear and enhanced images, this study designed a fully automated and adaptive stray light correction and enhancement algorithm for the nocturnal low-light images of FY-3E/MERSI-LL. Three typical stray-light-contaminated scenarios were categorized for all nighttime images. The restored results showed that after processing, the “fog” stray light and stripes were essentially removed, and the details became richer and more prominent, significantly improving the visual effect and usability of the images. This algorithm is simple, efficient, and highly applicable, and will be integrated into the processing system of the FY-3E satellite to support near real-time applications of LLB images. However, some strong or unusual stray light still affects the local continuity of the images. Future low-light imagers of FY-3 satellites will feature more sophisticated instruments to reduce incident stray light in their optical system.

The MEdium Resolution Spectral Imager (MERSI) onboard the Fengyun-3 (FY-3) series satellites can provide the long-term series data with favorable spectral and spatial resolution on the global scale since 2008. Such datasets are valuable for the studies of climate change. However, due to the lack of stable and reliable onboard calibration equipment and inconsistent in-orbit calibration methods, the MRESI historical data have poor long-term stability and unreliable accuracy, which affects the quantitative application of the data. This study reveals the overall status of the FY-3A/B/C MERSI-I historical data and proposes the recalibration methods for the reflective solar bands (RSBs) and thermal emission bands (TEBs). For the RSBs, by using FY-3A as the radiative transfer reference, an integrated transfer calibration method is developed for the calibration of FY-3B, which is then used to recalibrate FY-3C. The degradation tracking model of FY-3 MERSI-I is established first in the recalibration process by integrating multiple calibration methods. Then, based on the overlapping observations over the Libyan Desert, the linear consistency transfer model of the reference and target satellites is established, and the consistent correction coefficient between them is obtained. For the TEBs, a retrospective transfer recalibration scheme is proposed to achieve the reevaluation of the in-orbit radiometric calibration parameters based on intercalibration and to conduct the recalibration of historical data without permanent dependence on reference instruments. All the historical data of FY-A/B/C MERSI-I (from February 2008 to March 2017) are reprocessed with the same calibration method. The reprocessed datasets show remarkable improvements in calibration accuracy and stability compared with the operational datasets. The overall radiometric biases are found to be small and highly stable during the entire mission cycle of the instrument. The calibration biases of reprocessed data are less than 3% and 0.5 K for the RSBs and TEBs, respectively, much better than those of the operational datasets. There are also substantial improvements in the seasonal fluctuations and deviation discontinuities. This reprocessed long-term MERSI data with high intersensor consistency can provide valuable insights into global climate monitoring and model assessment.

The payload MEdium Resolution Spectral Imager - low light (MERSI-LL) of Fengyun-3E (FY-3E) equipped with a low light band (LLB) first enabled the FY series satellite to detect low lights at night. Due to the early morning orbit of FY-3E, MERSI-LL/LLB only obtains nighttime observations in one hemisphere during the winter half-year, and nighttime observations are only found at high latitudes for the ascending orbit (at dusk) and globally covered for the descending orbit (at dawn). Using MERSI-LL/LLB data, we developed nighttime lights (FY-NTL) product for socioeconomic use. Publicly released FY-NTL data include monthly and annual products for both ascending and descending orbits, which are composited from multitemporal MERSI-LL/LLB data after quality control. At present, the quality control procedure consists of moonlit data identification, stray light removal, cloud screening, and natural illumination exclusion. The absolute radiometric accuracy of FY-NTL degraded in the stray light removal process, and the comparison results with VIIRS NTL suggested that FY-NTL may bear a negative bias. Nonetheless, FY-NTL first images global nighttime lights at dawn and provides us with an opportunity to study city lights in different periods of the night.

The quality of thermal infrared (TIR) radiances from the FY-4A advanced geostationary radiation imager (AGRI) and their derived products is very important for weather predictions. The demand for more accurate weather forecasting models is increasing, so it is necessary to evaluate and improve the calibration accuracy of AGRI. This study aims to evaluate the AGRI TIR radiometric calibration accuracy by comparing two well-calibrated hyperspectral radiometers, the cross-track infrared sounder (CrIS), and the infrared atmospheric sounding interferometer (IASI). Most of the AGRI TIR channels are calibrated with an absolute brightness temperature (Tb) bias less than 0.5 K currently. The Tb bias of AGRI and CrIS\IASI depends on the target temperature, and it is smaller and more stable for higher Tb and increases for lower Tb. CH_14 shows the largest Tb bias (−0.53 K) and standard deviation (0.64 K), CH_10 and CH_11 record slightly positive Tb biases, and the other four channels exhibit negative Tb biases. The diurnal mean Tb bias is very consistent except for CH_11, which varies greatly among different time bins. The Tb bias of CH_09 is very consistent after the calibration update in February 2018. CH_10 shows a gradual bias decrease with bias from 1.0 to 0.6 K. CH_11 shows a gradual bias decrease with bias from 0.4 to 0.1 K with large fluctuations. CH_14 shows a gradual bias decrease with large fluctuation and like CH_11. CH_12 and CH_13 exhibit seasonal variations where the Tb bias reaches its maximum around June and minimum around February. In general, the Tb bias shows different spatial patterns in different channels and CH_11 shows obvious spatial distribution characteristics that is monthly dependent.

The spectral response function (SRF) is a crucial parameter in multispectral radiometers, and it influences the radiometric calibration accuracy and quantitative application capabilities. The in-flight SRF often has errors due to prelaunch contamination or postlaunch degradation. This study proposes an innovative new method to retrieve SRFs of multispectral radiometers based on intercomparisons with hyperspectral sounders via the functional data analysis (FDA) technique. Under the FDA framework, all variables, including the hyperspectral radiance and SRF, are regarded as functions rather than discrete data by expanding in the Fourier functional basis. The forward convolution equation is processed directly into a functional integration model rather than a normally pointwise summation; this ensures that the unknown quantities are transformed from numerous SRF samples to several function parameters, thus avoiding the ill-posed problem. The proposed algorithm is verified with both simulated and real data from multiple thermal infrared bands of the FY-3 IRAS and FY-4 AGRI using collocations with METOP-B IASI. All these results demonstrate our algorithm’s qualitative and quantitative effectiveness for infrared SRF retrieval. Although the demonstrations are particularly relevant to infrared spectra, the algorithm is universal and also applicable to other spectral bands.

The High Spectral Infrared Atmospheric Sounder (HIRAS) is the first Chinese Fourier Transform Michelson interferometer onboard the FengYun 3D (FY-3D) polar-orbiting meteorological satellite launched on November 15, 2017. The FY-3D HIRAS provides infrared (IR) radiance spectra measurements in three spectral bands: the long-wave IR (LWIR) band from 650 to 1135 cm-1, middle-wave IR (MWIR) band from 1210 to 1750 cm-1, and short-wave IR (SWIR) band from 2155 to 2550 cm-1. The ground system processes the interferogram measurements into calibrated radiance spectra. In each cross-track scan, there are 29 observations, each with a field-of-regard (FOR) comprising an array of 2×2 field of views. In a six-month intensive campaign period, the HIRAS system was tuned, characterized, and validated. For the operational Level 1 product, the radiance noise levels meet the specifications. The spectral frequency accuracy was improved by maximizing the spectral correlation between the measured and simulated spectra by tuning the instrument-line-shape parameters. The absolute spectral frequency biases are less than 3 part per million (ppm) for all the three bands, and spectral bias standard deviations are less than 3 ppm in the LWIR and MWIR bands, and are about 3-5 ppm in the SWIR band. The radiometric calibration uncertainties were assessed by the comparisons of the radiance spectra between HIRAS and other IR hyperspectral sensors on different satellites. The radiance differences of the cross-sensor comparisons are in general less than 0.3, 0.7, and 1.0 K in the LWIR, MWIR, and SWIR bands, respectively. The HIRAS spectra were also compared with the spectra simulated with a fast radiative transfer model. Some remaining issues for the FY-3D HIRAS are also discussed.

The High-Spectral Infrared Atmospheric Sounder (HIRAS) is a Fourier transform spectrometer onboard the fourth polar-orbiting FengYun 3D satellite (FY-3D). The FY-3D HIRAS provides interferogram measurements of Earth view radiance spectra in three infrared spectral bands at 29 cross-track positions, each with a 2 × 2 array of field of views (FOVs). The HIRAS level 1 radiance data cover the spectral bands from 650 to 1135 cm-1[long-wave (LW) band], 1210 to 1750 cm-1[mid-wave (MW) band], and 2155 to 2550 cm-1[short-wave (SW) band] with a spectral resolution of 0.625 cm-1. The radiometric calibration algorithm and the methods of refining the nonlinearity (NL) and the polarization correction coefficients on orbit are summarized in this article. The NL correction coefficients are derived by minimizing the spread of the responsivity functions derived from the measurements of the internal calibration target with varying temperatures. The polarization correction coefficients are derived from the cold space observations and the routine Earth scene measurements. The radiometric accuracy is assessed by comparing the HIRAS measurements to the collocated Cross-track Infrared Sounder (CrIS) observations and radiance simulations. The results show that, compared to CrIS, the radiometric differences are about 0.3 and 0.7 K for the LW and MW bands, respectively, and 0.5 K for the CO absorption and window regions in the SW band. The consistency of the radiometric calibration among the four FOVs is estimated to be within 0.2 K for most of the spectral domain. Some remaining issues for the FY-3D HIRAS are also discussed.