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

Abstract

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 sunmore » 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.« less

Authors:

Abbasi, Bilawal  ^[1];

• Search DOE PAGES for author "Abbasi, Bilawal"
• Search DOE PAGES for ORCID "0000-0001-6484-6695"

Qin, Zhihao ^[1]; Du, Wenhui ^[1]; Fan, Jinlong ^[2]; Zhao, Chunliang ^[1]; Hang, Qiuyan ^[3]; Zhao, Shuhe ^[4]; Li, Shifeng ^[1]

---

+ Show Author Affiliations

1. Chinese Academy of Agricultural Sciences, Beijing (China)
2. China Meteorological Administration, Beijing (China)
3. Guangxi Teachers Education Univ. (China)
4. Nanjing Univ. (China)

Publication Date:

Thu Oct 22 00:00:00 EDT 2020

Research Org.:

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Biological and Environmental Research (BER); National Key Research and Development Project of China; National Natural Science Foundation of China (NSFC)

OSTI Identifier:

1706617

Grant/Contract Number:  

AC05-76RL01830; 2016YFA0600302; 41771406; 41921001; 41661090

Resource Type:

Accepted Manuscript

Journal Name:

Remote Sensing

Additional Journal Information:

Journal Volume: 12; Journal Issue: 21; Journal ID: ISSN 2072-4292

Publisher:

MDPI

Country of Publication:

United States

Language:

English

Subject:

54 ENVIRONMENTAL SCIENCES; precipitable water vapor (PWV); ratio technique; FengYun-3D (FY-3D); MODTRAN 5; AERONET; microwave radiometer (MWR)