Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic

The cloud phase is one of the most important parameters of clouds. In this paper, we propose a method for cloud phase classification that synergistically utilizes the far- and thermal-infrared bands based on the Atmospheric Emitted Radiance Interferometer (AERI) at the Atmospheric Radiation Measurem...

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Published in:Remote Sensing
Main Authors: Hong Ren, Lei Liu, Jin Ye, Hailing Xie
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2023
Subjects:
Q
Online Access:https://doi.org/10.3390/rs16010071
https://doaj.org/article/ce1a707432274525b3c53c6c500392c0
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spelling ftdoajarticles:oai:doaj.org/article:ce1a707432274525b3c53c6c500392c0 2024-02-11T09:58:49+01:00 Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic Hong Ren Lei Liu Jin Ye Hailing Xie 2023-12-01T00:00:00Z https://doi.org/10.3390/rs16010071 https://doaj.org/article/ce1a707432274525b3c53c6c500392c0 EN eng MDPI AG https://www.mdpi.com/2072-4292/16/1/71 https://doaj.org/toc/2072-4292 doi:10.3390/rs16010071 2072-4292 https://doaj.org/article/ce1a707432274525b3c53c6c500392c0 Remote Sensing, Vol 16, Iss 1, p 71 (2023) Atmospheric Emitted Radiance Interferometer (AERI) far-infrared (FIR) Antarctic cloud phase Science Q article 2023 ftdoajarticles https://doi.org/10.3390/rs16010071 2024-01-14T01:38:50Z The cloud phase is one of the most important parameters of clouds. In this paper, we propose a method for cloud phase classification that synergistically utilizes the far- and thermal-infrared bands based on the Atmospheric Emitted Radiance Interferometer (AERI) at the Atmospheric Radiation Measurement West Antarctic Radiation Experiment (AWARE) observatory in 2016. The possible features in the far- and thermal-infrared bands are analyzed based on the differences in the simulated cloud brightness temperature (BT) spectra with different cloud phases. Using the support vector machine (SVM) algorithm, four features are determined to identify the cloud phase, which include the BT at 900 cm −1 , the slope of the fitted function of BT in the 900–1000 cm −1 interval, the BT difference (BTD) between 512 cm −1 and 726 cm −1 , and the BTD between 550 cm −1 and 726 cm −1 . Here, the performance of the proposed method is evaluated with Shupe’s and Turner’s method. The monthly average accuracy of the proposed method, the method without the two far-infrared features, and Turner’s method are about 76%, 36%, and 49%, respectively, which infer the good performance of the proposed method and also indicate that the far-infrared band features can effectively enhance cloud phase classification. It is notable that, compared to Shupe’s method, the accuracy for the proposed method is only 61% during the Antarctic summer, which results from the definitions of cloud phase and radiative effect. In addition, the accuracy is only 44% for Turner’s method in seasons with a low frequency of mixed clouds due to the significant effect of water vapor. Article in Journal/Newspaper Antarc* Antarctic Directory of Open Access Journals: DOAJ Articles Antarctic The Antarctic Remote Sensing 16 1 71
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Atmospheric Emitted Radiance Interferometer (AERI)
far-infrared (FIR)
Antarctic
cloud phase
Science
Q
spellingShingle Atmospheric Emitted Radiance Interferometer (AERI)
far-infrared (FIR)
Antarctic
cloud phase
Science
Q
Hong Ren
Lei Liu
Jin Ye
Hailing Xie
Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic
topic_facet Atmospheric Emitted Radiance Interferometer (AERI)
far-infrared (FIR)
Antarctic
cloud phase
Science
Q
description The cloud phase is one of the most important parameters of clouds. In this paper, we propose a method for cloud phase classification that synergistically utilizes the far- and thermal-infrared bands based on the Atmospheric Emitted Radiance Interferometer (AERI) at the Atmospheric Radiation Measurement West Antarctic Radiation Experiment (AWARE) observatory in 2016. The possible features in the far- and thermal-infrared bands are analyzed based on the differences in the simulated cloud brightness temperature (BT) spectra with different cloud phases. Using the support vector machine (SVM) algorithm, four features are determined to identify the cloud phase, which include the BT at 900 cm −1 , the slope of the fitted function of BT in the 900–1000 cm −1 interval, the BT difference (BTD) between 512 cm −1 and 726 cm −1 , and the BTD between 550 cm −1 and 726 cm −1 . Here, the performance of the proposed method is evaluated with Shupe’s and Turner’s method. The monthly average accuracy of the proposed method, the method without the two far-infrared features, and Turner’s method are about 76%, 36%, and 49%, respectively, which infer the good performance of the proposed method and also indicate that the far-infrared band features can effectively enhance cloud phase classification. It is notable that, compared to Shupe’s method, the accuracy for the proposed method is only 61% during the Antarctic summer, which results from the definitions of cloud phase and radiative effect. In addition, the accuracy is only 44% for Turner’s method in seasons with a low frequency of mixed clouds due to the significant effect of water vapor.
format Article in Journal/Newspaper
author Hong Ren
Lei Liu
Jin Ye
Hailing Xie
author_facet Hong Ren
Lei Liu
Jin Ye
Hailing Xie
author_sort Hong Ren
title Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic
title_short Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic
title_full Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic
title_fullStr Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic
title_full_unstemmed Using Downwelling Far- and Thermal-Infrared Hyperspectral Radiance for Cloud Phase Classification in the Antarctic
title_sort using downwelling far- and thermal-infrared hyperspectral radiance for cloud phase classification in the antarctic
publisher MDPI AG
publishDate 2023
url https://doi.org/10.3390/rs16010071
https://doaj.org/article/ce1a707432274525b3c53c6c500392c0
geographic Antarctic
The Antarctic
geographic_facet Antarctic
The Antarctic
genre Antarc*
Antarctic
genre_facet Antarc*
Antarctic
op_source Remote Sensing, Vol 16, Iss 1, p 71 (2023)
op_relation https://www.mdpi.com/2072-4292/16/1/71
https://doaj.org/toc/2072-4292
doi:10.3390/rs16010071
2072-4292
https://doaj.org/article/ce1a707432274525b3c53c6c500392c0
op_doi https://doi.org/10.3390/rs16010071
container_title Remote Sensing
container_volume 16
container_issue 1
container_start_page 71
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