Extended Abstract (2.7M)JP1.32
Improved Cloud Detection in CERES Edition 3 Algorithm and Comparison with the CALIPSO Vertical Feature Mask
Qing Z. Trepte, Science Systems and Applications Inc, Hampton, VA; and P. Minnis, C. Trepte, and S. Sun-Mack
For climate and Earth energy budget studies, understanding the presence and distribution of various clouds is a very important first step in any analysis. The Cloud and Earth's Radiant Energy System (CERES) project has produced a 10-year dataset (Edition 2) that has proven valuable for these types of studies. For this dataset, clouds are detected by the CERES cloud mask algorithms using Terra and Aqua MODIS data as well as other ancillary data sets.
An improved cloud mask will be employed for the CERES Edition 3 dataset, expected to begin in 2010. Compared with Edition 2, many improvements have been made in the Edition 3 cloud detection algorithm. These improvements include detecting more daytime ocean cumulus clouds and thin cirrus clouds, better discrimination between polar clouds and snow surfaces as well as between dust and clouds, and a smoother transition from non–polar to polar regions.
Comparisons between the CERES cloud mask and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Vertical Feature Mask (VFM) provides a powerful tool to validate and improve CERES cloud detection globally as well as to understand strengths and limitations of cloud retrievals between active and passive satellite senses. In this paper, examples of improvements in the Edition 3 CERES cloud mask will be presented for different types of clouds over various surfaces. Statistics from comparisons between CERES Edition 3 and CALIPSO VFM will be discussed.
Joint Poster Session 1, Cloud Remote Sensing Posters
Monday, 28 June 2010, 5:30 PM-8:30 PM, Exhibit Hall
Previous paper Next paper