Three-Dimensional Cloud Structure Reconstruction from the Directional Polarimetric Camera

Abstract

Clouds affect radiation transmission through the atmosphere, which impacts the Earth’ s energy balance and climate. Currently, the study of clouds is mostly based on a two-dimensional (2-D) plane rather than a three-dimensional (3-D) space. However, 3-D cloud reconstruction is playing an important role not only in a radiation transmission calculation but in forecasting climate change as well. Currently, the study of clouds is mostly based on 2-D single angle satellite observation data while the importance of a 3-D structure of clouds in atmospheric radiation transmission is ignored. 3-D structure reconstruction would improve the radiation transmission accuracy of the cloudy atmosphere based on multi-angle observations data. Characterizing the 3-D structure of clouds is crucial for an extensive study of this complex intermediate medium in the atmosphere. In addition, it is also a great carrier for visualization of its parameters. Special attributes and the shape of clouds can be clearly illustrated in a 3-D cloud while these are difficult to describe in a 2-D plane. It provides a more intuitive expression for the study of complex cloud systems. In order to reconstruct a 3-D cloud structure, we develop and explore a ray casting algorithm applied to data from the Directional Polarimetric Camera (DPC), which is onboard the GF-5 satellite. In this paper, we use DPC with characteristics of imaging multiple angles of the same target, and characterize observations of clouds from different angles in 3-D space. This feature allows us to reconstruct 3-D clouds from different angles of observations. In terms of verification, we use cloud profile data provided by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to compare with the results of reconstructed 3-D clouds based on DPC data. This shows that the reconstruction method has good accuracy and effectiveness. This 3-D cloud reconstruction method would lay a scientific reference for future analysis on the role of clouds in the atmosphere and for the construction of 3-D structures of aerosols.

Multi-View Polarimetric Scattering Cloud Tomography and Retrieval of Droplet Size

“…On the other hand, the multi-view technique of "space carving"-used here for initializing the iterative tomography-defines the 3D region that contains a certain cloud by intersecting threshold-based cloud masks from multiple directions. Space carving methods have been applied to determine conservatively the outer shape of clouds observed with the airborne hyperangular Research Spectro-Polarimeter (RSP) [34], MISR [35] (same cloud as Reference [29]), and other sensors (e.g., References [36,37]). Note that methods based on cloud-masking, feature detection-and-tracking and/or stereoscopic location do not require radiometrically calibrated sensors.…”

Three-dimensional model of cloud layers based on all-sky polarization imaging data

“…Besides, C. Cornet and R. Davies (2010) 2 implicated COT by Multiangle Imaging Spectroradiometer (MISR) in the base of a 3-D Monte Carlo model. Then, Haixiao Yu et al (2019) 3 reconstructed 3-D clouds from Directional Polarimetric Camera (DPC) installed on the GF-5 satellite. Although these methods could obtain a 3-D structure with high-level accuracy, they could not reconstruct 3D cloud layers and measure the cloud optical thickness in real-time in selected regions during the daytime.…”

Analysis and correction of environmental differences in geometric performance of spaceborne optical instruments

“…It can provide multi-angle, multi-spectral, and polarized radiation information of the detection target. Combined with the atmospheric property inversion model based on polarization information, DPC will play an important role in the inversion of atmospheric aerosol and cloud properties [4][5][6] . The GaoFen-5-01(GF-5-01) satellite launched in May 2018 and the GaoFen-5-02(GF-5-02) satellite launched in September 2021 are equipped with DPC.…”