Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 21 September 2018 / Approved: 22 September 2018 / Online: 22 September 2018 (23:00:20 CEST)

A peer-reviewed article of this Preprint also exists.

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. 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.

Journal reference: Remote Sens. 2018, 10, 1858
DOI: 10.3390/rs10111858

Abstract

Abstract: Characterization the 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 the Multi-angle Imaging SpectroRadiometer (MISR) on board the Terra satellite, to reconstruct 3-D cloud volumes for 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 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 select MISR scenes, fully accounting for MISR’s viewing geometry for reconstructions over the Earth’s ellipsoidal surface. The MISR Radiometric Camera-by-camera Cloud Masks at 1.1 km resolution and custom cloud masks at 275 m resolution independently derived from MISR RGB channels are used as input cloud masks. A wind correction method, termed “cloud spreading”, is devised and applied to the cloud masks to offset potential cloud movements over short time intervals (around 7 minutes at maximum) between the cameras. The MISR cloud top height product is used as a constraint to reduce the overestimation at the cloud top. The reconstruction results show that their uncertainty is significant when the wind correction is applied, and that they have more refined structures when the input cloud mask has a higher resolution. Recommendations for improving the presented cloud volume reconstructions as well as for future passive remote sensing satellite missions are discussed.

Subject Areas

MISR; cloud volume; cloud geometry; cloud shape; cloud boundary; cloud volume reconstruction.

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