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Comparison of NASA Team2 and AES-York Ice Concentration Algorithms Against Operational Ice Charts From the Canadian Ice ServiceIce concentration retrieved from spaceborne passive-microwave observations is a prime input to operational sea-ice-monitoring programs, numerical weather prediction models, and global climate models. Atmospheric Environment Service (AES)- York and the Enhanced National Aeronautics and Space Administration Team (NT2) are two algorithms that calculate ice concentration from Special Sensor Microwave/Imager observations. This paper furnishes a comparison between ice concentrations (total, thin, and thick types) output from NT2 and AES-York algorithms against the corresponding estimates from the operational analysis of Radarsat images in the Canadian Ice Service (CIS). A new data fusion technique, which incorporates the actual sensor's footprint, was developed to facilitate this study. Results have shown that the NT2 and AES-York algorithms underestimate total ice concentration by 18.35% and 9.66% concentration counts on average, with 16.8% and 15.35% standard deviation, respectively. However, the retrieved concentrations of thin and thick ice are in much more discrepancy with the operational CIS estimates when either one of these two types dominates the viewing area. This is more likely to occur when the total ice concentration approaches 100%. If thin and thick ice types coexist in comparable concentrations, the algorithms' estimates agree with CIS'S estimates. In terms of ice concentration retrieval, thin ice is more problematic than thick ice. The concept of using a single tie point to represent a thin ice surface is not realistic and provides the largest error source for retrieval accuracy. While AES-York provides total ice concentration in slightly more agreement with CIS'S estimates, NT2 provides better agreement in retrieving thin and thick ice concentrations.
Document ID
20080040137
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Shokr, Mohammed
(Meteorological Service of Canada Toronto, Ontario, Canada)
Markus, Thorsten
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 24, 2013
Publication Date
August 1, 2006
Publication Information
Publication: IEEE Transactions on Geoscience and Remote Sensing
Volume: 44
Issue: 8
ISSN: 0196-2892
Subject Category
Meteorology And Climatology
Funding Number(s)
CONTRACT_GRANT: MOA 02MOA26002
Distribution Limits
Public
Copyright
Other

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