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Open AccessArticle

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

1
MOA Key Laboratory of Agricultural Remote Sensing, Institute of Agro-Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
2
National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
3
School of Geography and Planning, Guangxi Teachers Education University, Nanning 530001, Guangxi, China
4
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, Jiangsu, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(21), 3469; https://doi.org/10.3390/rs12213469
Received: 21 August 2020 / Revised: 27 September 2020 / Accepted: 19 October 2020 / Published: 22 October 2020
(This article belongs to the Special Issue Remote Sensing of the Water Cycle)
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), CO2, 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/cm2 for the ARMP and 0.26 g/cm2 for the AERONET datasets, with bias of 0.072 g/cm2 and 0.096 g/cm2 for the two reference datasets, respectively. The accuracy of the proposed algorithm revealed a better consistency with ground-based reference datasets. Thus, the proposed algorithm could be used as an alternative to retrieve PWV from FY-3D MERSI-2 data for various remote sensing applications such as agricultural monitoring, climate change, hydrologic cycle, and so on at various regional and global scales. View Full-Text
Keywords: precipitable water vapor (PWV); ratio technique; FengYun-3D (FY-3D); MODTRAN 5; AERONET; microwave radiometer (MWR) precipitable water vapor (PWV); ratio technique; FengYun-3D (FY-3D); MODTRAN 5; AERONET; microwave radiometer (MWR)
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MDPI and ACS Style

Abbasi, B.; Qin, Z.; Du, W.; Fan, J.; Zhao, C.; Hang, Q.; Zhao, S.; Li, S. An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data. Remote Sens. 2020, 12, 3469. https://doi.org/10.3390/rs12213469

AMA Style

Abbasi B, Qin Z, Du W, Fan J, Zhao C, Hang Q, Zhao S, Li S. An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data. Remote Sensing. 2020; 12(21):3469. https://doi.org/10.3390/rs12213469

Chicago/Turabian Style

Abbasi, Bilawal; Qin, Zhihao; Du, Wenhui; Fan, Jinlong; Zhao, Chunliang; Hang, Qiuyan; Zhao, Shuhe; Li, Shifeng. 2020. "An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data" Remote Sens. 12, no. 21: 3469. https://doi.org/10.3390/rs12213469

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