An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data

The atmosphere has substantial effects on optical remote sensing imagery of the Earth’s surface from space. These effects come through the functioning of atmospheric particles on the radiometric transfer from the Earth’s surface through the atmosphere to the sensor in space. Precipitable water vapor...

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Published in:Remote Sensing
Main Authors: Bilawal Abbasi, Zhihao Qin, Wenhui Du, Jinlong Fan, Chunliang Zhao, Qiuyan Hang, Shuhe Zhao, Shifeng Li
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2020
Subjects:
Q
Online Access:https://doi.org/10.3390/rs12213469
https://doaj.org/article/50324db0f66141869d20c763ebad7f67
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spelling ftdoajarticles:oai:doaj.org/article:50324db0f66141869d20c763ebad7f67 2023-05-15T13:07:06+02:00 An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data Bilawal Abbasi Zhihao Qin Wenhui Du Jinlong Fan Chunliang Zhao Qiuyan Hang Shuhe Zhao Shifeng Li 2020-10-01T00:00:00Z https://doi.org/10.3390/rs12213469 https://doaj.org/article/50324db0f66141869d20c763ebad7f67 EN eng MDPI AG https://www.mdpi.com/2072-4292/12/21/3469 https://doaj.org/toc/2072-4292 doi:10.3390/rs12213469 2072-4292 https://doaj.org/article/50324db0f66141869d20c763ebad7f67 Remote Sensing, Vol 12, Iss 3469, p 3469 (2020) precipitable water vapor (PWV) ratio technique FengYun-3D (FY-3D) MODTRAN 5 AERONET microwave radiometer (MWR) Science Q article 2020 ftdoajarticles https://doi.org/10.3390/rs12213469 2022-12-31T00:47:17Z The atmosphere has substantial effects on optical remote sensing imagery of the Earth’s surface from space. These effects come through the functioning of atmospheric particles on the radiometric transfer from the Earth’s surface through the atmosphere to the sensor in space. Precipitable water vapor (PWV), CO 2 , ozone, and aerosol in the atmosphere are very important among the particles through their functioning. This study presented an algorithm to retrieve total PWV from the Chinese second-generation polar-orbiting meteorological satellite FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) data, which have three near-infrared (NIR) water vapor absorbing channels, i.e., channel 16, 17, and 18. The algorithm was improved from the radiance ratio technique initially developed for Moderate-Resolution Imaging Spectroradiometer (MODIS) data. MODTRAN 5 was used to simulate the process of radiant transfer from the ground surfaces to the sensor at various atmospheric conditions for estimation of the coefficients of ratio technique, which was achieved through statistical regression analysis between the simulated radiance and transmittance values for FY-3D MERSI-2 NIR channels. The algorithm was then constructed as a linear combination of the three-water vapor absorbing channels of FY-3D MERSI-2. Measurements from two ground-based reference datasets were used to validate the algorithm: the sun photometer measurements of Aerosol Robotic Network (AERONET) and the microwave radiometer measurements of Energy’s Atmospheric Radiation Measurement Program (ARMP). The validation results showed that the algorithm performs very well when compared with the ground-based reference datasets. The estimated PWV values come with root mean square error (RMSE) of 0.28 g/cm 2 for the ARMP and 0.26 g/cm 2 for the AERONET datasets, with bias of 0.072 g/cm 2 and 0.096 g/cm 2 for the two reference datasets, respectively. The accuracy of the proposed algorithm revealed a better consistency with ground-based reference datasets. Thus, ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Remote Sensing 12 21 3469
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic precipitable water vapor (PWV)
ratio technique
FengYun-3D (FY-3D)
MODTRAN 5
AERONET
microwave radiometer (MWR)
Science
Q
spellingShingle precipitable water vapor (PWV)
ratio technique
FengYun-3D (FY-3D)
MODTRAN 5
AERONET
microwave radiometer (MWR)
Science
Q
Bilawal Abbasi
Zhihao Qin
Wenhui Du
Jinlong Fan
Chunliang Zhao
Qiuyan Hang
Shuhe Zhao
Shifeng Li
An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data
topic_facet precipitable water vapor (PWV)
ratio technique
FengYun-3D (FY-3D)
MODTRAN 5
AERONET
microwave radiometer (MWR)
Science
Q
description The atmosphere has substantial effects on optical remote sensing imagery of the Earth’s surface from space. These effects come through the functioning of atmospheric particles on the radiometric transfer from the Earth’s surface through the atmosphere to the sensor in space. Precipitable water vapor (PWV), CO 2 , ozone, and aerosol in the atmosphere are very important among the particles through their functioning. This study presented an algorithm to retrieve total PWV from the Chinese second-generation polar-orbiting meteorological satellite FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) data, which have three near-infrared (NIR) water vapor absorbing channels, i.e., channel 16, 17, and 18. The algorithm was improved from the radiance ratio technique initially developed for Moderate-Resolution Imaging Spectroradiometer (MODIS) data. MODTRAN 5 was used to simulate the process of radiant transfer from the ground surfaces to the sensor at various atmospheric conditions for estimation of the coefficients of ratio technique, which was achieved through statistical regression analysis between the simulated radiance and transmittance values for FY-3D MERSI-2 NIR channels. The algorithm was then constructed as a linear combination of the three-water vapor absorbing channels of FY-3D MERSI-2. Measurements from two ground-based reference datasets were used to validate the algorithm: the sun photometer measurements of Aerosol Robotic Network (AERONET) and the microwave radiometer measurements of Energy’s Atmospheric Radiation Measurement Program (ARMP). The validation results showed that the algorithm performs very well when compared with the ground-based reference datasets. The estimated PWV values come with root mean square error (RMSE) of 0.28 g/cm 2 for the ARMP and 0.26 g/cm 2 for the AERONET datasets, with bias of 0.072 g/cm 2 and 0.096 g/cm 2 for the two reference datasets, respectively. The accuracy of the proposed algorithm revealed a better consistency with ground-based reference datasets. Thus, ...
format Article in Journal/Newspaper
author Bilawal Abbasi
Zhihao Qin
Wenhui Du
Jinlong Fan
Chunliang Zhao
Qiuyan Hang
Shuhe Zhao
Shifeng Li
author_facet Bilawal Abbasi
Zhihao Qin
Wenhui Du
Jinlong Fan
Chunliang Zhao
Qiuyan Hang
Shuhe Zhao
Shifeng Li
author_sort Bilawal Abbasi
title An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data
title_short An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data
title_full An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data
title_fullStr An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data
title_full_unstemmed An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data
title_sort algorithm to retrieve total precipitable water vapor in the atmosphere from fengyun 3d medium resolution spectral imager 2 (fy-3d mersi-2) data
publisher MDPI AG
publishDate 2020
url https://doi.org/10.3390/rs12213469
https://doaj.org/article/50324db0f66141869d20c763ebad7f67
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Remote Sensing, Vol 12, Iss 3469, p 3469 (2020)
op_relation https://www.mdpi.com/2072-4292/12/21/3469
https://doaj.org/toc/2072-4292
doi:10.3390/rs12213469
2072-4292
https://doaj.org/article/50324db0f66141869d20c763ebad7f67
op_doi https://doi.org/10.3390/rs12213469
container_title Remote Sensing
container_volume 12
container_issue 21
container_start_page 3469
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