Ocean Colour Climate Change Initiative: Future Plans

Slide 2

•  Phase 1 focussed on Case-1 waters, which are considered single-variable systems

•  Case-2 waters are multi-variable, optically-complex waters, often encountered in coastal waters and inland waters

•  Coastal issues high in priority for many users

•  User consultation: where do Case-1 waters stop and Case-2 waters begin?

Phase 2 Plans: •  Extend results to Case-2 waters •  Build on results of DUE CoastColour Project •  Note: extreme cases out of scope •  Important to maintain consistency of approach across Case-1 and Case-2 waters

Principal source of variation in Case-1 waters (other substances, if present, co-vary with phytoplankton)

Independent variation of other components cannot be ignored in Case-2 waters

Extend results to optically-complex coastal waters

Slide 3

Uncertainty Maps

Uncertainty maps based on validation of products against in situ data Extrapolation based on optical classification of pixels Phase 2 Plans •  Explore methods to improve optical

classification

•  Extend to Case-2 waters

Slide 4

Improve in situ database

RRS: RMSD per class and waveband

Chla: RMSD per class

Optical water class

Optical water class

Optical water class

Phase 2 Plans: •  Improve in situ database for next round robin and for validation •  Priority for additional data from Case-2 waters, oligotrophic gyres and poorly-

sampled geographic regions (e.g. high latitudes)

MERIS Radiance MODIS-A Radiance

Band-shifting, bias correction, Merged product

Improve Consistency Across Sensors

POLYMER SeaDAS

SeaDAS

Phase 2 Plans: •  Improve consistency in processing

across sensors, without sacrificing quality of product

Slide 6

GCOS Requirements and OC-CCI Products

GCOS-154 updated December 2011

Variable/ Parameter  

Horizontal Resolution  

Vertical Resolution  

Temporal Resolution  

Accuracy  

Stability  

Water Leaving Radiance   4km   N/A   daily   5%   0.5%  

Chlorophyll-a concentration   30km   N/A   weekly

averages   30%   3%  

Meets, or better than, GCOS Requirement

Colour Code:

Partially meets GCOS Requirements

To be evaluated

Phase 2 Plans: Strive to improve performance against GCOS requirements

Sensors used in OC-CCI

1985 1990 1995 2000 2005 2010 2015

OLCI

VIIRS*

OCM-2*

MODIS

MERIS

SeaWiFS

*being evaluated for phase 2 POLYMER applied to VIIRS

Sensors & Periods: All products

Currently, OC-CCI time series precariously dependent on a single sensor: MODIS Phase 2 Plans: •  Evaluate additional sensors for inclusion in OC-CCI •  Plan for OLCI on Sentinel 3

User Engagement

Phytoplankton phenology: climatology. Saux-Picart et al. Start data, duration and end date of blooms

Data assimilation of OC-CCI data in marine ecosystem models

Reanalysis of carbon fluxes in the North East Atlantic

Model without data assimilation

Model with data assimilation

OC- CCI data (V1)

Chlorophyll [mg m-3 ] 30 Apr. 2004

Changes in simulated C fluxes, May 2004

Air-sea flux [mol C m-2 month-1]

Net PP [mol C m-2 month-1]

after Ciavatta et al. JGR 2011

Phase 2 Plans: Enhance, expand engagement with the user community, especially marine ecosystem models

Slide 9

Data Dissemination http://oceancolour.org/

Phase 2 Plans: Expand portfolio of access modes: for discovery, subsetting, download, analysis…

ftp directory structure OPeNDAP

Open Geospatial Consortium web map &

functionalities

web browser (composites)

Slide 10

Inter-CCI connections

From Quinn & Bates 2011

Phase 2 Plans: OC-CCI, Aerosol, SST Option: 1.  To study significance of gaps in

OC-CCI data. 2.  Explore correlations between

chlorophyll, SST, aerosol and winds in selected areas of the world ocean to evaluate potential bias arising from gaps.

3.  Use aerosol data from Aerosol CCI to examine whether ocean-colour atmospheric correction procedures estimate aerosol properties accurately, and potential implications for quality of OC-CCI products.

Slide 11

Inter-CCI connections

Phase 2 Plans: •  Option to explore ocean-colour,

sea ice and SST connections in the Arctic

•  Improve sea-ice classification for ocean colour and SST at high spatial resolution

•  Study dynamics and biogeochemistry next to ice edge

2004

2011

Slide 12

Project Partnership

ESA

Shubha Sathyendranath, Science Lead, PML, UK

EO Science Team European R. Brewin, PML, UK V. Brotas, FCUL, Portugal C. Brockmann, BC, Germany A.B. Couto, FCUL, Portugal R. Doerffer, BC, Germany S. Groom, PML, UK T. Jackson, PML, UK H. Krasemann, HZG, Germany F. Mélin, JRC, EU D. Müller, HZG, Germany M. Peters, BC, Germany D. Ramon, HYGEOS, France L. Santoleri, CNR, Italy T. Storm, BC, Germany T. Platt, PML, UK F. Steinmetz, HYGEOS, France P.-Y. Deschamps, HYGEOS, France A. Valente, FCUL, Portugal

M. Dowell, Observer, JRC, Italy Non-European E. Devred, LU, Canada G. Feldman, NASA, USA B. Franz, NASA, USA Z.-P. Lee, BU, USA T. Hirata, HU, Japan T. Moore, UNH, USA M. Wang, NOAA, USA

Climate Research Group I. Allen, PML, UK L. Bertino, NERSC, Norway S. Ciavatta, PML, UK W. Gregg, NASA, USA T. Hirata, HU, Japan C. Le Quéré, UEA, UK S. Saux-Picart, PML, UK E. Simon, NERSC, Norway H. Von Storch, HZG, Germany

System Engineering M. Boettcher, BC, Germany N. Formferra, BC, Germany M. Grant, PML, UK A. Chuprin, PML, UK J. Swinton, TPZ Vega, UK

John Swinton, Project Manager, TPZ Vega, UK