JP1.17
Enhanced Cloud Algorithm From Collocated CALIPSO, CLOUDSAT And MODIS
Sunny Sun-Mack, SSAI, Hampton, VA; and P. Minnis, S. Kato, Y. Chen, Y. Yi, S. Gibson, P. W. Heck, D. M. Winker, and J. K. Ayers
Coincident profile information from CALIPSO's lidar and CloudSat's radar offers a unique opportunity to map the vertical structure of clouds over the globe with accuracies never before realized. The combination of these data with observations from other A-train instruments, CERES1 and MODIS, will lead to new insight into cloud structure and properties, aerosol climate effects, and more accurate estimates of surface longwave fluxes and atmospheric heating rate profiles that are needed to improve climate prediction. An enhancement to NASA Langley's CERES Visible Infrared Solar-infrared Split-window Technique (VISST) (Minnis et al. (2009) was developed to identify and account for situations when disagreement occurs between the VISST and CALIPSO cloud-top heights, particularly for multi-layer cloud systems where VISST retrievals are often incapable of accurately characterizing a particular thin cirrus cloud (Chang et al. 2008). The enhanced retrieval scheme replaces the CERES cloud-top height with its CALIPSO counterpart, and then retrieves cloud temperature and optical depth, as well as cloud microphysical characteristics such as particle size, phase, and liquid or ice water path. This paper presents the implementation of the enhanced CERES clouds algorithm, case studies, and the statistics of cloud property comparisons before and after application of the enhanced scheme, over the period of July 2006 – June 2007.
Joint Poster Session 1, Cloud Remote Sensing Posters
Monday, 28 June 2010, 5:30 PM-8:30 PM, Exhibit Hall
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