DOI: 10.1002/2016JD025183
论文题名: Quantifying uncertainties in radar forward models through a comparison between CloudSat and SPartICus reflectivity factors
作者: Mascio J. ; Mace G.G.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2017
卷: 122, 期: 3 起始页码: 1665
结束页码: 1684
语种: 英语
英文关键词: CloudSat
; mass-dimensional relationship
; optimal estimation
; radar forward model
; reflectivity
; SPartICus
Scopus关键词: airborne survey
; algorithm
; atmospheric particle
; bootstrapping
; cirrus
; cloud microphysics
; CloudSat
; data interpretation
; ice crystal
; numerical method
; numerical model
; optimization
; particle size
; radar
; reflectivity
; uncertainty analysis
英文摘要: Interpretations of remote sensing measurements collected in sample volumes containing ice-phase hydrometeors are very sensitive to assumptions regarding the distributions of mass with ice crystal dimension, otherwise known as mass-dimensional or m-D relationships. How these microphysical characteristics vary in nature is highly uncertain, resulting in significant uncertainty in algorithms that attempt to derive bulk microphysical properties from remote sensing measurements. This uncertainty extends to radar reflectivity factors forward calculated from model output because the statistics of the actual m-D in nature is not known. To investigate the variability in m-D relationships in cirrus clouds, reflectivity factors measured by CloudSat are combined with particle size distributions (PSDs) collected by coincident in situ aircraft by using an optimal estimation-based (OE) retrieval of the m-D power law. The PSDs were collected by 12 flights of the Stratton Park Engineering Company Learjet during the Small Particles in Cirrus campaign. We find that no specific habit emerges as preferred, and instead, we find that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum-defying simple categorization. With the uncertainties derived from the OE algorithm, the uncertainties in forward-modeled backscatter cross section and, in turn, radar reflectivity is calculated by using a bootstrapping technique, allowing us to infer the uncertainties in forward-modeled radar reflectivity that would be appropriately applied to remote sensing simulator algorithms. ©2017. American Geophysical Union. All Rights Reserved. 资助项目: NNX10AM42G
; NNX15AK17G
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62693
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 Atmospheric Sciences, University of Utah, Salt Lake City, UT, United States
Recommended Citation:
Mascio J.,Mace G.G.. Quantifying uncertainties in radar forward models through a comparison between CloudSat and SPartICus reflectivity factors[J]. Journal of Geophysical Research: Atmospheres,2017-01-01,122(3)