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Polarization enhancement of passive SWIR cloud thermodynamic phase remote sensing
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Paper Abstract

Determining whether a cloud is composed of spherical water droplets of polyhedral ice crystals (i.e., the thermodynamic phase) from a passive remote sensing instrument is very difficult because of the immense variety of clouds and their highly variable microphysical properties. To improve upon the popular method of radiance ratios, we enhance the classification ability by adding polarimetric sensitivity to an instrument that measures radiance in three short-wave infrared bands. Clouds typically induce a polarization signature on the order of a percent, and so sensitive optics are required for accurate classification. In this paper, we present the combination of spectral and polarimetric sensitivity for cloud thermodynamic phase classification using data from a ground-based, 3-band, short-wave infrared polarimeter and cloud-phase validation from a dual-polarization lidar. We then analyze the classification quality of various methods using surface-fitting techniques to show that the addition of polarimetry is advantageous for cloud classification.

Paper Details

Date Published: 6 September 2019
PDF: 9 pages
Proc. SPIE 11132, Polarization Science and Remote Sensing IX, 1113206 (6 September 2019); doi: 10.1117/12.2530128
Show Author Affiliations
Martin Jan Tauc, Montana State Univ. (United States)
Elizabeth M. Rehbein, Montana State Univ. (United States)
Laura M. Eshelman, Montana State Univ. (United States)
Polaris Sensor Technologies, Inc. (United States)
Joseph A. Shaw, Montana State Univ. (United States)


Published in SPIE Proceedings Vol. 11132:
Polarization Science and Remote Sensing IX
Julia M. Craven; Joseph A. Shaw; Frans Snik, Editor(s)

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