DOI: 10.1002/2016JD025207
论文题名: Improvements on the ice cloud modeling capabilities of the Community Radiative Transfer Model
作者: Yi B. ; Yang P. ; Liu Q. ; van Delst P. ; Boukabara S.-A. ; Weng F.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2016
卷: 121, 期: 22 起始页码: 577
结束页码: 590
语种: 英语
英文关键词: CRTM
; ice cloud
; optical properties
; radiative transfer
Scopus关键词: AIRS
; atmospheric modeling
; brightness temperature
; cloud microphysics
; ice
; MODIS
; optical property
; radiative transfer
; scattering
; size distribution
英文摘要: Noticeable improvements on the ice cloud modeling capabilities of the Community Radiative Transfer Model (CRTM) are reported, which are based on the most recent advances in understanding ice cloud microphysical (particularly, ice particle habit/shape characteristics) and optical properties. The new CRTM ice cloud model is derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 ice cloud habit model, which represents ice particles as severely roughened hexagonal ice column aggregates with a gamma size distribution. The single-scattering properties of the new ice particle model are derived from a state-of-the-art ice optical property library and are constructed as look-up tables for rapid CRTM computations. Various sensitivity studies concerning instrument-specific applications and simulations are performed to validate CRTM against satellite observations. In particular, radiances in a spectral region covering the infrared wavelengths are simulated. Comparisons of brightness temperatures between CRTM simulations and observations (from MODIS, the Atmospheric Infrared Sounder, and the Advanced Microwave Sounding Unit) show that the new ice cloud optical property look-up table substantially enhances the performance of the CRTM under ice cloud conditions. ©2016. American Geophysical Union. All Rights Reserved. 资助项目: NA15NES4400003
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62799
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, Texas A&M University, College Station, TX, United States; ESSIC, University of Maryland, College Park, MD, United States; Joint Center for Satellite Data Assimilation, College Park, MD, United States; NOAA/NESDIS/STAR, College Park, MD, United States
Recommended Citation:
Yi B.,Yang P.,Liu Q.,et al. Improvements on the ice cloud modeling capabilities of the Community Radiative Transfer Model[J]. Journal of Geophysical Research: Atmospheres,2016-01-01,121(22)