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The retrievals and analysis of clear-sky water vapor density in the Arctic regions from MWHS measurements on FY-3A satellite
He, Jieying; Zhang, Shengwei; Wang, Zhenzhan; He, JY (reprint author), Chinese Acad Sci, Ctr Space Sci & Appl Res, Beijing 100190, Peoples R China.
Department微波遥感部
Source PublicationRADIO SCIENCE
2012
Volume47Pages:RS2009
ISSN0048-6604
Language英语
AbstractThe atmospheric humidity profiles of clear sky in the Arctic regions were retrieved from the microwave humidity sounder on China's FY-3A satellite using the back-propagation neural network algorithm. The algorithm was developed using the reliable measurements of surface temperature, humidity, and pressure as well as atmospheric temperature and humidity profiles from radiosonde observations. Considering the influence of sounding geometry, different surface types, and atmospheric conditions, we improved the commonly used back-propagation artificial neural network by treating the Mexican hat wavelet function as a transfer function and transforming the input data space. The retrieved root-mean-square (RMS) error is about 0.12 g/m(3) in absolute humidity (water vapor density) profiles and 12.7% in relative humidity profiles. Water vapor density retrievals in winter are in acceptable agreement with profiles from radiosonde, but the agreement of the summer data was not as good. Furthermore, the retrieval model has been used in another Arctic station with a mean water vapor density RMS error of 0.185 g/m(3) and 18.3% for a relative humidity profile for all seasons in 2008 at 12:00 UT.; The atmospheric humidity profiles of clear sky in the Arctic regions were retrieved from the microwave humidity sounder on China's FY-3A satellite using the back-propagation neural network algorithm. The algorithm was developed using the reliable measurements of surface temperature, humidity, and pressure as well as atmospheric temperature and humidity profiles from radiosonde observations. Considering the influence of sounding geometry, different surface types, and atmospheric conditions, we improved the commonly used back-propagation artificial neural network by treating the Mexican hat wavelet function as a transfer function and transforming the input data space. The retrieved root-mean-square (RMS) error is about 0.12 g/m(3) in absolute humidity (water vapor density) profiles and 12.7% in relative humidity profiles. Water vapor density retrievals in winter are in acceptable agreement with profiles from radiosonde, but the agreement of the summer data was not as good. Furthermore, the retrieval model has been used in another Arctic station with a mean water vapor density RMS error of 0.185 g/m(3) and 18.3% for a relative humidity profile for all seasons in 2008 at 12:00 UT.
Indexed BySCI ; EI
Funding Project中国科学院空间科学与应用研究中心
Document Type期刊论文
Identifierhttp://ir.nssc.ac.cn/handle/122/3457
Collection微波遥感部
Corresponding AuthorHe, JY (reprint author), Chinese Acad Sci, Ctr Space Sci & Appl Res, Beijing 100190, Peoples R China.
Recommended Citation
GB/T 7714
He, Jieying,Zhang, Shengwei,Wang, Zhenzhan,et al. The retrievals and analysis of clear-sky water vapor density in the Arctic regions from MWHS measurements on FY-3A satellite[J]. RADIO SCIENCE,2012,47:RS2009.
APA He, Jieying,Zhang, Shengwei,Wang, Zhenzhan,&He, JY .(2012).The retrievals and analysis of clear-sky water vapor density in the Arctic regions from MWHS measurements on FY-3A satellite.RADIO SCIENCE,47,RS2009.
MLA He, Jieying,et al."The retrievals and analysis of clear-sky water vapor density in the Arctic regions from MWHS measurements on FY-3A satellite".RADIO SCIENCE 47(2012):RS2009.
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