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.
Highlights
Cloud is the necessary medium in radiation process from a solar environment to an atmosphere
The result presented shows different reconstructed cloud structures above the land and ocean surface from Directional Polarimetric Camera (DPC) data
A 3-D cloud reconstruction algorithm explored in this paper takes into account the differences caused by different cloud elevations, and it has a good reconstruction effect for clouds at different altitudes
Summary
Cloud is the necessary medium in radiation process from a solar environment to an atmosphere. Clouds affect radiant flux of the entire atmosphere by absorbing, reflecting, transmitting, and emitting electromagnetic waves, which, in turn, affects global climate It can interfere in the interpretation of remote sensing images and can reduce utilization of images by covering ground information. In cloud detection and property inversion based on channel radiance, the Multi-angle Imaging SpectroRadiometer (MISR) provide less information than DPC. The only satellites which directly detect 3-D structure information of clouds are CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (Calipso). These platforms use active microwave radar and lidar to accurately detect the cloud boundary and its vertical structure [8,9,10], but with small observation widths. Compared with other sensors that already applied to 3-D cloud reconstruction, it has characteristics of short revisit periods and rich channel information, which provide a better data source for 3-D cloud reconstruction
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