1. Ocean Time Series Data Products from Systematic Satellite Missions: Moderate Resolution - AVHRR/SeaWiFS/MODIS/VIIRS Stéphane Maritorena, Whit Anderson, Peter Minnett, Bob Evans, Sam Lavender, Odile Hembise

2. Science and Applications OC and SST OC and SST are important variables for Climate variability, trends Weather and ocean forecasting Ocean and atmospheric models (forcing, data assimilation and validation) Primary Production Carbon budget Heat transfer … Satellite data provide best mechanism for producing globally consistent data sets.

3. SST Changes ( 0 C ) +3 +2 -2 +1 -3 0 0 -30 +60 -60 +30 NPP Changes (%) b a c NPP SST

4. A few SST time-series Time-SeriesDataSpatial Resolution Temporal resolution Time period GHRSST L2P L4 1/4 degree - 6kmDaily1985 - Present MODIS Thermal IR Mid-IR 4.5 km – 9 km Daily 8-Day Monthly Annual Feb. 2000 – Present (T) Jul. 2002 – Present (A) AVHRR Pathfinder v54 km Daily 5 Day 7 Day 8 Day Monthly Annual 1985 - 2006 AVHRR MCSST NAVOCEANO Miami 2 km – 18 km Weekly Swath Nov. 1981 – Feb. 2001 Aug. 2001 – Oct. 2005 Aug. 2001 - Present GOES (Regional) 6 kmHourlyMay 2003 - Present NCEP Reynolds OI – MCSST In Situ 2 degrees Weekly Monthly 1981 - Present

5. NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 GHRSST-PP GODAE (Global Ocean Data Assimilation Experiment) High- Resolution SST Pilot Project International project begun in late 2004. To produce SST fields that contain error statistics for each SST pixel. The traceability of the accuracy of the SST pixels through the atmospheric correction and cloud screening algorithms is important to establishing confidence in the SST fields. Validation of satellite derived SSTs from a range of sensors, using various in situ radiometers, each with NIST-traceable calibration, is an important component of this project.

6. SST time-series More than 20 years of data Highly successful data sets Merged data sets (thermal IR and microwave, biases correction among sensors) Perennial (no data gap in sight ?) NASA MEaSUREs: Merged Ultra High Resolution (1 km) SST product

7. Ocean Color time-series (Level-3) http://www.globcolour.info/index.html

8. Satisfy emerging demand for validated merged ocean colour derived information Demonstrate the current state of the art in merging together data streams from different ocean-colour sensors: MERIS (ESA), SeaWiFS (NASA), MODIS-AQUA (NASA) Provide a long time-series (10 years) of ocean-colour information Demonstrate a global NRT ocean-colour service based on merged satellite data Put in place the capacity to continue production of such time series in the future and to prepare for full exploitation of Sentinel 3 (ESA) As such, be the initial step of the Ocean Colour Thematic assembly Centre, part of the future EU GMES Marine Core Service www.globcolour.info http://www.enviport.org/globcolour/validation/ GlobColour Objectives NASA CC & E - April 28, 2008

9. European Service for Ocean Colour GlobColour Products NASA CC & E - April 28, 2008 Global ocean colour data set at 4.6 km, 1/4°, 1° resolution covering 1997-2008 daily, weekly, monthly products: Chlorophyll concentration (Chla) Diffuse attenuation coefficient @ 490nm (K d 490) Total Suspended Matter CDM absorption (aCDM443) Particle backscattering coefficient (bbp443) Aerosol Optical Thickness (T865) Exact normalised water-leaving radiance @ 412, 443, 490, 510, 531, 555, 620nm Water-leaving radiance @ 670, 681, 709nm Data quality flags Cloud fraction Excess of radiance at ~ 555 nm (turbidity index) (EL555) Error estimates per pixel for each layer MODIS-only, MERIS-only

10. Ocean Color time-series (Level-3) o Most products are available as Level-2 data o Many other products available through SeaDAS data processing o CZCS (Nov. 1978 – June 1986) and OCTS data are also available ftp://oceans.gsfc.nasa.gov/ftp://oceans.gsfc.nasa.gov/ http://oceancolor.gsfc.nasa.gov/cgi/level3.p l o Most products are available as Level-2 data o Many other products available through SeaDAS data processing o CZCS (Nov. 1978 – June 1986) and OCTS data are also available ftp://oceans.gsfc.nasa.gov/ftp://oceans.gsfc.nasa.gov/ http://oceancolor.gsfc.nasa.gov/cgi/level3.p l

11. Ocean Color time-series (Level-3) Contd Data available at: ftp:ftp.oceancolor.ucsb.edu/pub/org/oceancolor/REASoN/ OPeNDAP server: http://dap.oceancolor.ucsb.edu/cgi-bin/nph-dods/data/oceancolor/ NASA GIOVANNI (Monthly): http://reason.gsfc.nasa.gov/Giovanni/ Data available at: ftp:ftp.oceancolor.ucsb.edu/pub/org/oceancolor/REASoN/ OPeNDAP server: http://dap.oceancolor.ucsb.edu/cgi-bin/nph-dods/data/oceancolor/ NASA GIOVANNI (Monthly): http://reason.gsfc.nasa.gov/Giovanni/ Other local/regional time-series exist, e.g. NOAAs COASTLOOK Upcoming OC sensors: VIIRS (NPP/NPOES), OCL (S3, ESA), OCM-2 (Oceansat-2, ISRO)

12. ESDRs, CDRs and CAL/VAL

13. NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 Climate Data Records National Academy of Sciences Report (NRC, 2000): a data set designed to enable study and assessment of long-term climate change, with long-term meaning year-to-year and decade-to-decade change. Climate research often involves the detection of small changes against a background of intense, short-term variations. Calibration and validation should be considered as a process that encompasses the entire system, from the sensor performance to the derivation of the data products. The process can be considered to consist of five steps: –instrument characterization, –sensor calibration, –calibration verification, –data quality assessment, and –data product validation.

14. GHRSST Matchups Ocean Color Matchups CAL/VAL

15. NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 M-AERI cruises and MODIS validation statistics

16. ISSUES/CONCERNS

17. Ocean color time-series Bias among sensors exist.This needs to be reconciled to develop CDRs or ESDRs Quality issues (aging sensors.e.g. SeaWiFS) ? Concerns about the possible interruption of the current time-series Is VIIRS going to be a sub- PAR ocean color sensor ?

18. NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 Long-time series measurements of SST Multi-decadal time series require accurate measurements from several series of satellites and sensors. All have particular sampling and accuracy problems: –Infrared polar orbiters (AVHRRs, (A)ATSRs, MODISs, Met-Op AVHRR/3… VIIRS): ·More complex instruments (MODIS, VIIRS) leads to more instrumental artifacts ·Limited degrees of freedom for atmospheric corrections –Microwave polar orbiters (AMSR-E… AMSR follow-on GCOM-W ): ·Calibration issues ·Footprint size ·Side-lobe contamination –Infrared geostationary (GOES Imager, MSG SEVIRI… GOES-R ABI ): ·No high latitude coverage ·Diurnal heating cycle of s/c and instrument (3-axis GOES s/c)

19. NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 Concerns about sustaining SST CDRs Complex instruments need very careful pre-launch characterization Accurate validation must be sustained throughout s/c missions Overlap of missions of ~1yr desired

20. NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 NASA Carbon Cycle and Ecosystems Joint Science Workshop April 28, 2008 Concerns about sustaining validation capabilities CDRs require traceability to NIST standards For AVHRR, (A)ATSR, MODIS, AMSR-E through M-AERIs and Calibration Facilities at UM-RSMAS M-AERIs > 10yrs old, >3500 sea-days, rely on obsolete components, need replacing Calibration Facilities must be sustained Ship-based radiometry for validation must be sustained into the NPOESS era

21. Objectives of this breakout Discuss the scientific questions and issues that are being addressed by existing space-based observations. Discuss current time series data products and their scientific application Discuss their future as Climate Data Records (CDRs) and/or Earth System Data Records (ESDRs). Discuss calibration/validation, airborne science, in situ observational needs Identify opportunities, recommend priorities, raise issues or concerns Questions: What are the key products (CDR or ESDR) for understanding the ocean over time ? What does the carbon cycle and ecosystems community and modelers expect or need of this effort? What are our biggest challenges in this area, and how do we address them? Is our list of identified data records complete, or is something missing? Does the carbon cycle and ecosystems community need to establish priorities for these and other activities, and, if so, how should they be established?