Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

Barta, Andras, Horvath, Gabor, Horvath, Akos, Egri, Adam, Blaho, Miklos, Barta, Pal, Bumke, Karl and Macke, Andreas (2015) Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms. Applied Optics, 54 (5). pp. 1065-1077. DOI 10.1364/AO.54.001065.

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Abstract

Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

Document Type: Article
Additional Information: WOS:000349684600014
Keywords: Clouds, meteorology, image analysis, polarimetric imaging, passive remote sensing, RV Polarstern
Research affiliation: OceanRep > GEOMAR > FB1 Ocean Circulation and Climate Dynamics > FB1-ME Maritime Meteorology
Refereed: Yes
Open Access Journal?: No
DOI etc.: 10.1364/AO.54.001065
ISSN: 0003-6935
Expeditions/Models/Experiments:
Date Deposited: 09 Feb 2015 08:41
Last Modified: 20 Jun 2018 09:51
URI: http://oceanrep.geomar.de/id/eprint/27343

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