globalchange  > 影响、适应和脆弱性
DOI: 10.1002/jgrd.50579
论文题名:
From CloudSat-CALIPSO to EarthCare: Evolution of the DARDAR cloud classification and its comparison to airborne radar-lidar observations
作者: Ceccaldi M.; Delanoë J.; Hogan R.J.; Pounder N.L.; Protat A.; Pelon J.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期:14
起始页码: 7962
结束页码: 7981
语种: 英语
英文关键词: classification ; clouds ; DARDAR ; lidar ; radar
Scopus关键词: Algorithms ; Classification (of information) ; Clouds ; Pixels ; Radar ; Spectral resolution ; Troposphere ; Classification algorithm ; Cloud classification ; DARDAR ; Doppler measurement ; Field experiment ; High spectral resolution lidars ; Similar pattern ; Target Classification ; Optical radar ; algorithm ; CALIPSO ; CloudSat ; lidar ; observational method ; pixel ; radar ; spectral resolution ; troposphere
英文摘要: This paper presents the implementation of a new version of the DARDAR (radar lidar) classification derived from CloudSat and CALIPSO data. The resulting target classification called DARDAR v2 is compared to the first version called DARDAR v1. Overall DARDAR v1 reports more cloud or rain pixels than DARDAR v2. In the low troposphere this is because v1 detects too many liquid cloud pixels, and in the higher troposphere this is because v2 is more restrictive in lidar detection than v1. Nevertheless, the spatial distribution of different types of hydrometeors show similar patterns in both classifications. The French airborne Radar-Lidar (RALI) platform carries a CloudSat/CALIPSO instrument configuration (lidar at a wavelength of 532nm and a 95GHz cloud radar) as well as an EarthCare instrument configuration (high spectral resolution lidar at 355nm and a 95GHz Doppler cloud radar). It therefore represents an ideal go-between for A-Train and EarthCare. The DARDAR v2 classification algorithm is adapted to RALI data for A-Train overpasses during dedicated airborne field experiments using the lidar at 532nm and the radar Doppler measurements. The results from the RALI classification are compared with the DARDAR v2 classification to identify where the classification should still be interpreted with caution. Finally, the RALI classification algorithm with lidar at 532nm is adapted to RALI with high spectral resolution lidar data at 355nm in preparation for EarthCare. Key Points A new DARDAR classification is developed from CloudSat and CALIOP profiles The new version is compared to the first one and it shows improvements The method is adapted to airborne data for validation and preparation to E-Care ©2013. American Geophysical Union. All Rights Reserved.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63504
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: Laboratoire Atmosphères, Milieux, Observations Spatiales, 11 Boulevard d'Alembert, FR-78280 Guyancourt, France; Department of Meteorology, University of Reading, Reading, United Kingdom; Centre for Australian Weather and Climate Research, Australian Bureau of Meteorology, CSIRO, Melbourne VIC, Australia; Laboratoire Atmosphères, Milieux, Observations Spatiales, Université Pierre et Marie Curie, Paris, France

Recommended Citation:
Ceccaldi M.,Delanoë J.,Hogan R.J.,et al. From CloudSat-CALIPSO to EarthCare: Evolution of the DARDAR cloud classification and its comparison to airborne radar-lidar observations[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(14)
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