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.
CITATION STYLE
Yu, H., Ma, J., Ahmad, S., Sun, E., Li, C., Li, Z., & Hong, J. (2019). Three-dimensional cloud structure reconstruction from the directional polarimetric camera. Remote Sensing, 11(24). https://doi.org/10.3390/rs11242894
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