The Aerosol and Carbon Detection Lidar (ACDL) on board the Atmospheric Environment Monitoring Satellite (DQ-1) has been successfully operationalized, and it possesses the capability of detecting carbon dioxide, aerosols, and clouds around the world. However, in contrast to other spaceborne lidars currently/previously in operation (e.g., the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation-CALIPSO, the Ice, Cloud, and land Elevation Satellite-2 mission-ICESat-2 and so on), the ACDL does not incorporate a background signal monitor. Consequently, it is crucial to develop background signal acquisition algorithm for ACDL and to analyze the background characterization. In this paper, a three-segmented background signal acquisition algorithm is designed for ACDL to ensure that the acquired background signals match the instrument characteristics. Additionally, the multi-channel background signals measured by ACDL during daytime and nighttime are characterized in detail, including the features in single profile, along the orbit, on a monthly, semi-annually basis, and particular regions. The quantitative analysis of the data reveals a decrease in background signal intensity along latitudinal lines during nocturnal periods (<0.0005 V). Concurrently, elevated signal values are observed within specific regions of South Atlantic Anomaly (SAA). Additionally, the daytime background signal exhibits a high degree of sensitivity to the characteristics of the feature, and it is influenced by the relative positions of the Sun and the Earth. These findings corroborate the stability of the background signal and its consistency with the behavior of the background signal collected by CALIPSO. And the background removed signals collected by ACDL showed good agreement (difference less than 0.026 V) in the region of consistent diurnal aerosol loads (18-22 km) under clear-air conditions. The background acquisition algorithm and characterization analysis proposed in this paper provide accurate data and theoretical support for subsequent calibration and product inversion. Additionally, it offers a solution for background signal extraction in the case of spaceborne lidars that are not equipped with a background signal monitor.

The Ice, Cloud and land elevation Satellite-2 (ICESat-2) carries the new generation photon-counting lidar payload, the Advanced Topographic Laser Altimeter System (ATLAS). After after-pulse correction, the water column profile acquired by ATLAS can be used to derive vertical profiles of ocean optical parameters. However, the stability and robustness of the correction method across different sea areas could be improved. This study analyzes the broadening effect of sea surface signals caused by varying sea states. It employs land signals with broadening characteristics similar to those of the sea surface as the system impulse response function (SIRF) to perform after-pulse correction on water column profiles. By matching pulse widths, the proposed algorithm reduces the impact of sea surface broadening on after-pulse correction results. Internal consistency validation among ATLAS three strong beams is conducted and achieve the correlation coefficient exceeding 0.8 in the Black Sea, Atlantic Ocean, and Pacific Ocean. Meanwhile, the ocean optical parameter inversions are compared and validated with MODIS and BGC-Argo data. The mean relative errors of inversion results in the three sea areas are approximately 20%, representing a reduction of over 30% compared to traditional algorithm. Finally, a sensitivity analysis of the broadening matching algorithm and cumulative length confirms the algorithm’s robustness. The ocean optical parameters inversion algorithm based on pulse broadening matching lays the foundation for high-precision inversion of parameters such as chlorophyll concentration and provides a reference for future data processing in related systems.

Lidar can provide three-dimensional detection of the subsurface layer of the global ocean and represents the future direction of ocean remote sensing. One equation and two unknowns in elastic scattering lidar greatly affect the inversion accuracy. Based on airborne oceanographic lidar and in-situ measurements, an error analysis of widely used profile parameter inversion methods was performed, and a high-precision inversion method was developed. After careful data preprocessing, error analysis was performed on bio-optical parameters obtained from inversion methods including Collis Slope method, Klett backscatter iteration method, Churnside perturbation retrieval method and empirical models. In response to the inversion accuracy problems, a parameters optimization method has been proposed that does not require the assumption of a lidar ratio or a constant of lidar attenuation coefficient. Inversion results from the airborne lidar under the conditions of Case I waters in the South China Sea show that the method effectively improves the inversion accuracy of the β(π) profile to about 10% at depths over 50 m where the bio-optical parameters underwater change rapidly, and it can avoid misjudging the subsurface phytoplankton layer. Through detailed data preprocessing, profile parameter inversion and error analysis, this study provides a theoretical foundation for the development of future spaceborne oceanographic lidar data products.

The large signal dynamic range affecting the profile recognition of refined structures is one of the major challenges for future spaceborne oceanographic light detection and ranging (lidar) systems. Reduce the intensity of the sea surface signal and ensure that the detector operates in a linear response region, which helps reduce the subsurface signal error and improves the capability to detect weak signals in deep water. As a solution, the off-nadir pointing could reduce the photon counts from the sea surface but leads to depth aliasing. This reduces the vertical resolution and makes it difficult to determine the sea surface’s position and retrieve the thin chlorophyll layer. The lidar signal’s dynamic range is simulated to improve the detection accuracy. Based on the oceanographic lidar simulator, the laser transmission characteristics are analyzed, taking into account various different environmental parameters (including wind speed, sea surface roughness, concentration of whitecaps and bubbles) and lidar specifications (including laser off-nadir angle, divergence angle, and pulsewidth). The results show that increasing the off-nadir angle to 7°–15° can effectively reduce the dynamic range of the sea surface signal by about one order of magnitude, while increasing the aliasing depth by about 4–8 m. Reducing the beam divergence angle is beneficial for accurate inversion of profiles within the limits of engineering realization. Other parameters, such as pulsewidth, wind speed, and sea surface roughness, have little influence on depth aliasing and depth estimation errors.

Wide swath near-nadir interferometric altimetry is a newly developed technology for sea surface height (SSH) measurement. However, the absence of actual measurement data makes this novel SSH mapping technique difficult to verify and apply for wide swath interferometric altimeters. To verify the designed performance of the scheduled wide swath single-pass interferometric altimeter in the "Guanlan Mission", an airborne campaign was carried out off the coast of Rizhao, China on November 16, 2020. An airborne dual-frequency interferometric radar altimeter system (ADIRAS) with a single-pass mode was utilized for SSH measurement as the first flight. Two pioneering and fundamental works have been conducted: an intensive altimetry error analysis according to the ADIRAS parameter settings along the incident direction, an effective SSH reconstruction approach based on a multichannel likelihood (ML) function, and detailed validation procedures through airborne campaigns illustrated in this study. The results indicated that the difference between the wave-induced sea surface elevation (WSSE) variances derived by the ML approach and GNSS buoy was 2 cm2, which was smaller than the results of the single band on Ku (11 cm2) and Ka (6 cm2). Moreover, the estimated Significant Waves Height (SWH) bias of joint bands was 10 cm, which was also superior to that of Ku (39 cm) and Ka (24 cm). Both simulated data and real airborne dual-frequency InSAR data were employed in this study for cross-validation of the proposed method. This approach represents an effective technique for SSH reconstruction of future spaceborne/airborne interferometric altimeters.

Ocean color satellite sensors have become an indispensable component in the Earth Observing System, in which the use of multiple ocean color satellite sensors not only improves the spatiotemporal coverage of the global oceans but also maintains the continuity of the data products for long-term monitoring. In this research, the performance of a new ocean color satellite sensor Chinese Ocean Color and Temperature Scanner (COCTS) from HY1C launched in September 2018 is thoroughly evaluated with two important aspects: the signal-to-noise ratio (SNR) at the top of the atmosphere and the uncertainty in the remote-sensing reflectance Rrs) products. The results showed that the SNR of the COCTS can satisfy the requirements of the ocean color applications, and the uncertainty in the Rrs at the blue bands in the ocean waters meets the demand of less than 5%. A further comparison with other well-known ocean color sensors indicates that not only the COCTS can provide reliable ocean color data but also the processing system is robust and reliable. These results provide a solid base for merging the COCTS products with other ocean color sensors for the studies of ocean biogeochemistry.

This paper presents a result of crossover analysis between HY-2 and Jason-2 mission over ocean. The major objectives of this paper are to assess HY-2 IGDR (Interim Geophysical Data Record) derived SSHs by comparing HY-2 measurements with the reference mission Jason-2, and further to illustrate the potential of HY-2 data in monitoring global sea level variability. The instrument-independent models and data are applied for both HY-2 and Jason-2 to correct the errors including range delays and geophysical effects, thus provide an objective assessment. All the results indicate a good performance of HY-2 measurements. A standard deviation of 6.6 cm and a bias of 0.26 cm between HY-2 and Jason-2 SSHs (Sea Surface Height) is acquired from 50°S to 50°N which is close to the Jason-1 and Jason-2 performance. The results suggest that a promising situation in terms of HY-2 observations.

A forward Monte Carlo 3-D (FMC3D) model is developed for simulating light fields in a volume of water where the boundary conditions for radiance values can be expressed by mathematical formulas, which cannot be done using the radiative transfer models currently available such as HydroLight. Water is assumed parallel homogenous for these models, which are incapable of investigating the sidewall reflectance effect on the light fields. These ones are called quasi-3-D radiative transfer models. The FMC3D model perfects the assumption and the incapability and is validated using the in situ data measured in the tank experiment. The FMC3D model is first applied to investigate the sidewall reflectance effect on the remote sensing reflectanceRrsfor waters in a fabricated tank with infinite depth and different radii. The investigation shows that the effect is decreasing with the increase in the tank radius and that the minimum radius that the effect is negligible for highly scattering water is bigger than that for highly absorbing water. Taking the tank used in the experiment carried out in a previous work by Han and Rundquist as an example, the FMC3D model is second applied to investigate the combining effects onRrsfrom bottom and sidewall reflectances. Compared withRrsfor open water, theRrsfor tank water having the same inherent optical properties is underestimated. The underestimation is increasing with the increase in the single scattering albedo ω and can be up to 32% for water with ω = 0.88, showing that the effects cannot be removed by the black inside wall, which is a method commonly used in tank experiments. The potential applications of the FMC3D model are discussed, taking the examples of the correction for the wall reflectance effect on apparent spectra measured in tank experiments and of the scattering error correction for the reflective tube absorption coefficient measured using a WET Labs AC-9 or AC-S device.