The CALIPSO Lidar Cloud and Aerosol Discrimination: Version 2 Algorithm and Initial Assessment of Performance
| Autor: | Ali Omar, Chieko Kittaka, Mark A. Vaughan, Zhaoyan Liu, Ralph Kuehn, David M. Winker, Brian Getzewich, Kathleen A. Powell, Chris A. Hostetler, Charles R. Trepte |
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| Rok vydání: | 2009 |
| Předmět: | |
| Zdroj: | Journal of Atmospheric and Oceanic Technology. 26:1198-1213 |
| ISSN: | 1520-0426 0739-0572 |
| Popis: | The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite was launched in April 2006 to provide global vertically resolved measurements of clouds and aerosols. Correct discrimination between clouds and aerosols observed by the lidar aboard the CALIPSO satellite is critical for accurate retrievals of cloud and aerosol optical properties and the correct interpretation of measurements. This paper reviews the theoretical basis of the CALIPSO lidar cloud and aerosol discrimination (CAD) algorithm, and describes the enhancements made to the version 2 algorithm that is used in the current data release (release 2). The paper also presents a preliminary assessment of the CAD performance based on one full day (12 August 2006) of expert manual classification and on one full month (July 2006) of the CALIOP 5-km cloud and aerosol layer products. Overall, the CAD algorithm works well in most cases. The 1-day manual verification suggests that the success rate is in the neighborhood of 90% or better. Nevertheless, several specific layer types are still misclassified with some frequency. Among these, the most prevalent are dense dust and smoke close to the source regions. The analysis of the July 2006 data showed that the misclassification of dust as cloud occurs for |
| Databáze: | OpenAIRE |
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