Climate observations and their applications require measurements with high stability and low uncertainty in order to detect and assess climate variability and trends. The difficulty with space-based observations is that it is generally not possible to trace them to standard calibration references when in orbit. In order to overcome this problem, it has been proposed to deploy space-based radiometric reference systems which intercalibrate measurements from multiple satellite platforms. Such reference systems have been strongly recommended by international expert teams. This paper describes the Chinese Space-based Radiometric Benchmark (CSRB) project which has been under development since 2014. The goal of CSRB is to launch a reference-type satellite named LIBRA in around 2025. We present the roadmap for CSRB as well as requirements and specifications for LIBRA. Key technologies of the system include miniature phase-change cells providing fixed-temperature points, a cryogenic absolute radiometer, and a spontaneous parametric down-conversion detector. LIBRA will offer measurements with SI traceability for the outgoing radiation from the Earth and the incoming radiation from the Sun with high spectral resolution. The system will be realized with four payloads, i.e., the Infrared Spectrometer (IRS), the Earth-Moon Imaging Spectrometer (EMIS), the Total Solar Irradiance (TSI), and the Solar spectral Irradiance Traceable to Quantum benchmark (SITQ). An on-orbit mode for radiometric calibration traceability and a balloon-based demonstration system for LIBRA are introduced as well in the last part of this paper. As a complementary project to the Climate Absolute Radiance and Refractivity Observatory (CLARREO) and the Traceable Radiometry Underpinning Terrestrial- and Helio- Studies (TRUTHS), LIBRA is expected to join the Earth observation satellite constellation and intends to contribute to space-based climate studies via publicly available data.

The design and processing algorithm of oceanic LIDAR requires an effective lidar simulator. Currently, most simulation methods for lidar signal propagation in seawater use elastic scattering. In this study, a new semi-analytical Monte Carlo (MC) model for oceanic lidar inelastic signals is developed to investigate chlorophyll fluorescence and Raman scattering in seawater. We also used this model to simulate the echo signal of high spectral resolution lidar (HSRL) in the particulate and water molecular channels. Using this model, the effects of chlorophyll concentration, multiple scattering, receiving field of view (FOV), scattering phase function (SPF), receiver full width at half maximum (FWHM) and inhomogeneous seawater were investigated. The feasibility and effectiveness of the model were verified by the lidar equation under small and large FOVs. The results showed that chlorophyll concentration and vertical structure and multiple scattering have considerable and integrated effects on echo signals, which could provide a reference for the design of oceanic fluorescence and HSRL lidar systems and contribute to the development of processing algorithms.

Monitoring global greenhouse gas concentration information via satellite remote sensing has become a critical area of research to support the further understanding of global carbon emissions. The Greenhouse-gases Absorption Spectrometer-2 (GAS-2) is being developed as the primary payload of the Fengyun-3H (FY-3H), which will be launched in 2024. Achieving high-precision mesurements of greenhouse gases requires precise spectral calibration. However, currently, there is no method for assessing the detection accuracy of GAS-2 using spectral calibration light sources, and quantitative studies are lacking. In this study, the influence model of calibration light sources on spectral calibration accuracy is established, and the spectral radiance acquired via GAS-2 is simulated using the line-by-line radiative transfer model (LBLRTM). We investigated the impact of different linewidths and wavelength stabilities of the calibration light source on its accuracy in four wavelength bands. This study is the first to examine the effects of the linewidth and wavelength stability of a calibration light source on the spectral radiance acquired via GAS-2. The initial results demonstrate that if the linewidth of the calibration light source is approximately 100 MHz and the wavelength stability is in the order of subpicometers, the radiance error obtained by GAS-2 is less than 10%. Among the four bands, the 2.06 $\mathsf{\mu }$m (strong-$C{O}_2$) band is more affected by the calibration light source than the other three bands. In addition, the wavelength stability of the light source has a greater influence on the error than the linewidth of the light source under the same error condition. The research findings can be used to guide and reference the selection of light sources in the laboratory spectral calibration of GAS-2, ultimately contributing to the instrument’s quantitative development level.

Satellite-based monitoring of atmospheric greenhouse gas (GHG) concentrations has emerged as a prominent and globally recognized field of research. With the imminent launch of the Greenhouse-Gases Absorption Spectrometer-2 (GAS-2) on the FengYun3-H (FY3-H) satellite in 2024, there is a promising prospect for substantial advancements in GHG detection capabilities. Crucially, the accurate acquisition of spectral information by GAS-2 is heavily reliant on its instrument parameters. However, the existing body of research predominantly emphasizes the examination of atmospheric parameters and their impact on GHG detection accuracy, thereby leaving a discernible gap in the comprehensive evaluation of instrument parameters specifically concerning the acquisition of atmospheric greenhouse gas concentration data by GAS-2. To address this knowledge gap, our study employs a radiation transfer model grounded in radiation transfer theory. This comprehensive investigation aims to quantitatively analyze the effects of various instrument parameters, encompassing crucial aspects such as spectral resolution, spectral sampling rate, signal-to-noise ratio, radiometric resolution, and spectral calibration accuracy (including instrument line shape function, central wavelength shift, and spectral resolution broadening). Based on our preliminary findings, it is evident that GAS-2 has the necessary spectral resolution, spectral sampling rate, and signal-to-noise ratio, slightly surpassing existing international instruments and enabling a significant detection accuracy level of 1 part per million (ppm). Moreover, it is essential to recognize the critical impact of instrument spectral calibration accuracy on overall detection precision. Among the five commonly used instrument line shape functions, the sinc function has the least impact on detection accuracy. Additionally, GAS-2’s radiance quantization depth is 14 bits, which is comparable to similar international payloads and maintains a root mean squared error below 0.1 ppm, thus ensuring a high level of precision. This study provides a comprehensive evaluation of the influence of GAS-2’s instrument parameters on detection accuracy, offering valuable insights for the future development of spectral calibration, the optimization of similar payload instrument parameters, and the overall improvement of instrument quantification capabilities.

The next-generation FengYun-3H satellite carrying a greenhouse gas absorption spectrometer (GAS) is planned for launch by 2024 with a strengthened ability to help researchers understand the global carbon cycle. However, assessments of the atmospheric CO₂-detection capabilities of GAS are still incomplete, mainly in the following aspects: previous studies on the spectral range of GAS instruments often used the weak absorption band of CO₂ molecules (1.61 μm); research on the measurement accuracies of different atmospheric environments above oceans is lacking; and most studies considered land surfaces as the bottom boundaries. Here, we simulated high spectral CO₂ absorption spectra in both the strong and weak bands (2.06 and 1.61 μm) while considering the effects of different instrumental (spectral resolution and sampling rate) and environmental (wind speed, visibility, and rough sea surface) parameters. This is the first atmospheric CO₂ absorption spectrum study to consider rough-sea-surface effects. The preliminary results show that the root mean squared error (RMSE) and mean absolute difference (MAD) values of the atmospheric CO₂ transmittance spectra of GAS are 0.031 and 0.011, respectively, in the 1.61 μm band and 0.05 and 0.033 in the 2.06 μm band, revealing that GAS is competitive among similar CO₂ instruments. This study provides a design reference for next-generation GAS instruments and contributes to spectral data CO₂ processing in the above-sea atmosphere.

InGaAs detection systems have been increasingly used in the aerospace field, and due to the high signal-to-noise ratio requirements of short-wave infrared quantitative payloads, there is an urgent need for methods for the rapid and precise evaluation and the optimal design of these systems. The rigid-flex printed circuit board (PCB) is a vital component of InGaAs detectors, as its grid ground plane design parameters impact parasitic capacitance and thus affect weak infrared analog signals. To address the time-intensive and costly nature of design optimization achieved with simulations and experimental measurements, we propose an innovative method based on a neural network to predict the scattering parameters of rigid-flex boards for InGaAs detection links. This is the first study in which the effects of rigid-flex boards on weak infrared detection signals have been considered. We first obtained sufficient samples with software simulation. A backpropagation (BP) neural network prediction model was trained on existing sample sets and then verified on a rigid-flex board used in a crucial aerospace short-wave infrared quantitative mission. The model efficiently and accurately predicted high-speed interconnect scattering parameters under various rigid-flex board grid plane parameter conditions. The prediction error was less than 1% compared with a 3D field solver, indicating an overcoming of the iterative optimization inefficiency and showing improved design quality for InGaAs detection circuits.