Background noise model of spaceborne photon-counting lidars over oceans and aerosol optical depth retrieval from ICESat-2 noise data

Abstract

The ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) photon-counting lidar is a revolutionary active remote sensing device and is extremely sensitive to both laser signal and solar background induced noise photons. The weak laser signals, such as aerosol and water subsurface backscattered laser photons, may be buried in noise in the daytime. A noise model for spaceborne photon-counting lidars is of vital importance in understanding and evaluating the performance of a lidar system, as well as in data processing and applications. From the reciprocity perspective, the main noise source for photon-counting lidars is solar background radiation, which in turn is the signal source of ocean color sensors. In the absence of clouds, it is possible to estimate the aerosol information using background noise data of ICESat-2 if the background noise is accurately modeled. In this study, a background noise model of photon-counting lidars over oceans is proposed that carefully considers the contributions of gas molecules, aerosol, water surface, subsurface, and detector dark noise. As the background rate from clouds are much larger than the sum of other factors, in this study, we only consider the cloudless atmosphere by using a cloud screening process. By inputting the system and environmental parameters, the theoretical predictions of noise level in six study areas have an average MAPE of ∼5% compared with ICESat-2 measured noise data. The results also indicate that without clouds, the variation of aerosols dominates the variation of ICESat-2 total background noise in open ocean areas. Then, based on this noise model, a method to estimate aerosol optical depths (AODs) over oceans is proposed solely on the ICESat-2 product including background noise rate and environmental data. Validation against MODIS (Moderate Resolution Imaging Spectroradiometer) daily AODs indicates that the average MAPE is <20% and the average correlation coefficient is 0.95 in six study areas. This method may provide a new AOD retrieval way over oceans in the daytime, when it is difficult to directly calculate AODs using lidar backscattered signal under strong background noise. In addition, the background noise of the ICESat-2 photon-counting lidar in its six channels (or pixels) has the potential to be regarded as the signal of an “ocean color camera” with only a single narrow green band. Based on this consideration, future works may be conducted to combine ocean color remote sensing with ICESat-2 photon-counting lidar.