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Open AccessArticle

Three-Dimensional Cloud Volume Reconstruction from the Multi-angle Imaging SpectroRadiometer

Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, 1301 W. Green St., Urbana, IL 61801, USA
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Remote Sens. 2018, 10(11), 1858; https://doi.org/10.3390/rs10111858
Received: 21 September 2018 / Revised: 14 November 2018 / Accepted: 16 November 2018 / Published: 21 November 2018
(This article belongs to the Special Issue MISR)
Characterizing 3-D structure of clouds is needed for a more complete understanding of the Earth’s radiative and latent heat fluxes. Here we develop and explore a ray casting algorithm applied to data from the Multi-angle Imaging SpectroRadiometer (MISR) onboard the Terra satellite, in order to reconstruct 3-D cloud volumes of observed clouds. The ray casting algorithm is first applied to geometrically simple synthetic clouds to show that, under the assumption of perfect, clear-conservative cloud masks, the reconstruction method yields overestimation in the volume whose magnitude depends on the cloud geometry and the resolution of the reconstruction grid relative to the image pixel resolution. The method is then applied to two hand-picked MISR scenes, fully accounting for MISR’s viewing geometry for reconstructions over the Earth’s ellipsoidal surface. The MISR Radiometric Camera-by-camera Cloud Mask (RCCM) at 1.1-km resolution and the custom cloud mask at 275-m resolution independently derived from MISR’s red, green, and blue channels are used as input cloud masks. A wind correction method, termed cloud spreading, is applied to the cloud masks to offset potential cloud movements over short time intervals between the camera views of a scene. The MISR cloud-top height product is used as a constraint to reduce the overestimation at the cloud top. The results for the two selected scenes show that the wind correction using the cloud spreading method increases the reconstructed volume up to 4.7 times greater than without the wind correction, and that the reconstructed volume generated from the RCCM is up to 3.5 times greater than that from the higher-resolution custom cloud mask. Recommendations for improving the presented cloud volume reconstructions, as well as possible future passive remote sensing satellite missions, are discussed. View Full-Text
Keywords: MISR; cloud volume; cloud geometry; cloud shape; cloud boundary; cloud volume reconstruction MISR; cloud volume; cloud geometry; cloud shape; cloud boundary; cloud volume reconstruction
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Lee, B.; Di Girolamo, L.; Zhao, G.; Zhan, Y. Three-Dimensional Cloud Volume Reconstruction from the Multi-angle Imaging SpectroRadiometer. Remote Sens. 2018, 10, 1858.

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