An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data

Zhou, F-C; Song, X; Leng, P; Wu, H; Tang, B-H

An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data

Zhou, F-C Song, X Leng, P Wu, H Tang, B-H

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Publisher:: Hindawi Limited
Publication Type:: Journal Article
Citation:: Advances in Meteorology, 2016, 2016, pp. 1-11
Issue Date:: 2016-01-01

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Field	Value	Language
dc.contributor.author	Zhou, F-C
dc.contributor.author	Song, X
dc.contributor.author	Leng, P
dc.contributor.author	Wu, H
dc.contributor.author	Tang, B-H
dc.date.accessioned	2022-03-21T00:12:44Z
dc.date.available	2022-03-21T00:12:44Z
dc.date.issued	2016-01-01
dc.identifier.citation	Advances in Meteorology, 2016, 2016, pp. 1-11
dc.identifier.issn	1687-9309
dc.identifier.issn	1687-9317
dc.identifier.uri	http://hdl.handle.net/10453/155397
dc.description.abstract	<jats:p>Precipitable water vapor (PWV) is one of the most variable components of the atmosphere in both space and time. In this study, a passive microwave-based retrieval algorithm for PWV over land without land surface temperature (LST) data was developed. To build the algorithm, two assumptions exist: (1) land surface emissivities (LSE) at two adjacent frequencies are equal and (2) there are simple parameterizations that relate transmittance, atmospheric effective radiating temperature, and PWV. Error analyses were performed using radiosonde sounding observations from Zhangye, China, and CE318 measurements of Dalanzadgad (43°34′37′′N, 104°25′8′′E) and Singapore (1°17′52′′N, 103°46′48′′E) sites from Aerosol Robotic Network (AERONET), respectively. In Zhangye, the algorithm had a Root Mean Square Error (RMSE) of 4.39 mm and a bias of 0.36 mm on cloud-free days, while on cloudy days there was an RMSE of 4.84 mm and a bias of 0.52 mm because of the effect of liquid water in clouds. The validations in Dalanzadgad and Singapore sites showed that the retrieval algorithm had an RMSE of 4.73 mm and a bias of 0.84 mm and the bigger errors appeared when the water vapor was very dry or very moist.</jats:p>
dc.language	en
dc.publisher	Hindawi Limited
dc.relation.ispartof	Advances in Meteorology
dc.relation.isbasedon	10.1155/2016/4126393
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0401 Atmospheric Sciences
dc.title	An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data
dc.type	Journal Article
utslib.citation.volume	2016
utslib.for	0401 Atmospheric Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2022-03-21T00:12:43Z
pubs.publication-status	Published
pubs.volume	2016

Abstract:

Precipitable water vapor (PWV) is one of the most variable components of the atmosphere in both space and time. In this study, a passive microwave-based retrieval algorithm for PWV over land without land surface temperature (LST) data was developed. To build the algorithm, two assumptions exist: (1) land surface emissivities (LSE) at two adjacent frequencies are equal and (2) there are simple parameterizations that relate transmittance, atmospheric effective radiating temperature, and PWV. Error analyses were performed using radiosonde sounding observations from Zhangye, China, and CE318 measurements of Dalanzadgad (43°34′37′′N, 104°25′8′′E) and Singapore (1°17′52′′N, 103°46′48′′E) sites from Aerosol Robotic Network (AERONET), respectively. In Zhangye, the algorithm had a Root Mean Square Error (RMSE) of 4.39 mm and a bias of 0.36 mm on cloud-free days, while on cloudy days there was an RMSE of 4.84 mm and a bias of 0.52 mm because of the effect of liquid water in clouds. The validations in Dalanzadgad and Singapore sites showed that the retrieval algorithm had an RMSE of 4.73 mm and a bias of 0.84 mm and the bigger errors appeared when the water vapor was very dry or very moist.

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http://hdl.handle.net/10453/155397