The Ocean Colour CCI (OC_CCI) project focuses on the Ocean Colour ECV encompassing water-leaving radiance in the visible domain, derived chlorophyll and inherent optical properties and will utilise data archives of from ESA’s MERIS and NASA’s SeaWiFS, MODIS and possibly CZCS (after careful evaluation) sensors archives.
The overall Climate Change Initiative will be progressively built up in three major stages during the six years of the programme: Stage 1 (current 3-year project stage): Requirements analysis and specifications, algorithm development, ECV prototyping, production and validation. Stage 2: Systems development and operational ECV production. Stage 3: User assessment, assimilation and feedback. Over the next 3 years the Ocean Colour Climate Change Initiative project aims to: Develop and validate algorithms to meet the Ocean Colour GCOS ECV requirements for consistent, stable, error-characterized global satellite data products from multi-sensor data archives; Produce and validate, within an R&D context, the most complete and consistent possible time series of multi-sensor global satellite data products for climate research and modelling; Optimize the impact of MERIS data on climate data records; Generate complete specifications for an operational production system; Strengthen inter-disciplinary cooperation between international Earth observation, climate research and modelling communities, in pursuit of scientific excellence.
ESA’s Technical Officer for the Ocean Colour CCI project, Dr Peter Regner, will be working with an international team brought together under the leadership of Dr Shubha Sathyendranath from Plymouth Marine Laboratory (PML, UK) who will lead the scientific programme and will be supported by John Swinton (VEGA, UK) on project management aspects. The consortium comprises three teams with the EO Science Team focusing on algorithm definition and ECV production prototyping, the Climate Research Group will provide independent peer-review analysis of the results and the System Engineering Team will deliver analysis on the ECV data processing and future production aspects.