DOI: 10.1002/jgrd.50170
论文题名: Retrieving asian dust aot and height from hyperspectral sounder measurements: An artificial neural network approach
作者: Han H.-J. ; Sohn B.J.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 2 起始页码: 837
结束页码: 845
语种: 英语
Scopus关键词: Acoustic devices
; Aerosols
; Dust
; Infrared devices
; Inverse problems
; Neural networks
; Optical radar
; Pixels
; Radiometers
; Satellite imagery
; Aerosol optical thickness
; Artificial neural network approach
; Atmospheric infrared sounders
; Brightness temperatures
; Correlation coefficient
; Hyperspectral measurements
; Moderate resolution imaging spectroradiometer
; Satellite observations
; Infrared instruments
; aerosol property
; air mass
; AIRS
; artificial neural network
; atmospheric modeling
; CALIPSO
; dust
; height determination
; MODIS
; optical depth
; pixel
; Asia
英文摘要: In order to examine potential use of infrared (IR) hyperspectral measurements for dust monitoring, a statistical artificial neural network (ANN) approach was taken as an inverse method of retrieving pixel-level aerosol optical thickness (AOT) and dust height (zdust). The ANN model was trained by relating Atmospheric Infrared Sounder (AIRS) brightness temperatures across 234 channels, surface elevation, and relative air mass to collocated AOT derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and zdust derived from Cloud Aerosol Lidar Infrared Pathfinder Satellite Observation (CALIPSO) observations for Asian dust cases. Results showing correlation coefficients of 0.84 and 0.79, and mean biases of 0.03 and about -0.02 km for AOT and zdust, respectively, suggest that dust retrievals from hyperspectral IR sounder measurements are comparable to MODIS-derived AOT and CALIPSO-measured zdust. The pixel-level retrievals of AOT and zdust during both day and night from IR hyperspectral measurements may offer great potential to improve our ability to monitor and forecast the evolving features of Asian dust. © 2012. American Geophysical Union. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/64012
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: School of Earth and Environmental Sciences, Seoul National University, NS80, Seoul, 151-747, South Korea
Recommended Citation:
Han H.-J.,Sohn B.J.. Retrieving asian dust aot and height from hyperspectral sounder measurements: An artificial neural network approach[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(2)