DOI: 10.1002/jgrd.50172
论文题名: Detecting snowfall over land by satellite high-frequency microwave observations: The lack of scattering signature and a statistical approach
作者: Liu G. ; Seo E.-K.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 3 起始页码: 1376
结束页码: 1387
语种: 英语
英文关键词: CloudSat
; high-frequency microwave
; snowfall detection
Scopus关键词: Algorithms
; Atmospheric humidity
; Clouds
; Microwaves
; Principal component analysis
; Radar
; Scattering
; Table lookup
; Temperature
; Vector spaces
; Brightness temperatures
; CloudSat
; Empirical orthogonal function analysis
; High frequency HF
; Independent variables
; Microwave observations
; Principal Components
; Scattering signatures
; Snow
; algorithm
; light scattering
; microwave radiation
; mountain
; principal component analysis
; probability
; radar imagery
; satellite imagery
; snow
; statistical analysis
英文摘要: It has been long believed that the dominant microwave signature of snowfall over land is the brightness temperature decrease caused by ice scattering. However, our analysis of multiyear satellite data revealed that on most of occasions, brightness temperatures are rather higher under snowfall than nonsnowfall conditions, likely due to the emission by cloud liquid water. This brightness temperature increase masks the scattering signature and complicates the snowfall detection problem. In this study, we propose a statistical method for snowfall detection, which is developed by using CloudSat radar to train high-frequency passive microwave observations. To capture the major variations of the brightness temperatures and reduce the dimensionality of independent variables, the detection algorithm is designed to use the information contained in the first three principal components resulted from Empirical Orthogonal Function (EOF) analysis, which capture ∼99% of the total variances of brightness temperatures. Given a multichannel microwave observation, the algorithm first transforms the brightness temperature vector into EOF space and then retrieves a probability of snowfall by using the CloudSat radar-trained look-up table. Validation has been carried out by case studies and averaged horizontal snowfall fraction maps. The result indicated that the algorithm has clear skills in identifying snowfall areas even over mountainous regions. ©2013. American Geophysical Union. All Rights Reserved. 资助项目: NNX10AG76G
; NNX10AM30G
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63936
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: Department of Earth, Ocean, and Atmospheric Science, Florida State University, 404 Love Building, 1017 Academic Way, Tallahassee, FL 32306-4520, United States; Department of Earth Sciences, Kongju National University, South Korea
Recommended Citation:
Liu G.,Seo E.-K.. Detecting snowfall over land by satellite high-frequency microwave observations: The lack of scattering signature and a statistical approach[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(3)