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Remote-sensing imperatives of the Global Ocean Observing System (GOOS)

DRS at CSIR-National Institute of Oceanography

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Title Remote-sensing imperatives of the Global Ocean Observing System (GOOS)
 
Creator Summerhayes, C.
Desa, E.
Swamy, G.N.
 
Subject research programmes
planning
satellite sensing
remote sensing
monitoring systems
 
Description This paper discusses the implications of the recent progress in the implementation of Global Ocean Observing System (GOOS), to the satellite remote-sensing community. The imperatives are to increase the scales of observation and thus to extend the range of observable phenomena, with reduction in cost and effort. Since GOOS aims at being a systematic, routine and long-term observational arrangement, continuity in satellite missions is essential. Further, the occasional redundancies of satellite data could be treated as valuable data streams in their own right, e.g. for cross-calibration of sensors on different platforms. This is an important aspect the remote-sensing community needs to address. Remote sensing has been highly successful in observing the climatic component of the ocean. It is yet to reach this level of observational strength for the other GOOS components of Living Marine resources (LMR) and Health of the Ocean (HOTO), especially in coastal waters. Appropriate proxy parameters are to be devised for those oceanic variables not measured remotely as of date. In situ validation of these parameters through dedicated cruises, SOOP (Ships of Opportunity), drifters, Argo (the global array of profiling floats) and autonomous moored arrays is crucial. The tasks are thus to advance the function of remote-sensing algorithms to encompass those variables which are presently monitored by in situ systems, leaving these systems to act more as sea-truth validators than as in situ data suppliers.Successful implementation of GOOS therefore depends largely on critical scientific feedback on powerful satellite sensor technology, fine-tuning remote-sensing algorithms, and further data assimilation into real-time operational models.
 
Date 2009-01-09T09:13:34Z
2009-01-09T09:13:34Z
2000
 
Type Conference Article
 
Identifier The Fifth Pacific Ocean Remote Sensing Conference (PORSEC), 5-8 December 2000. Proceedings,Vol.1; 389-396p.
http://drs.nio.org/drs/handle/2264/1693
 
Language en
 
Rights Copyright [2000]. All efforts have been made to respect the copyright to the best of our knowledge. Inadvertent omissions, if brought to our notice, stand for correction and withdrawal of document from this repository.
 
Publisher NIO, Dona Paula, Goa (India)