Ocean Time Series Data Products from Systematic Satellite Missions: Moderate Resolution AVHRRSeaWiFS

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 ApplicationsOC 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
(No Transcript)
4
A few SST time-series
5
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

• GlobColour Objectives
• NASA CC E - April 28, 2008

• 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 inthe 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/

9
GlobColour Products NASA CC E - April 28, 2008
European Service for Ocean Colour
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 _at_ 490nm (Kd490)
• Total Suspended Matter
• CDM absorption (aCDM443)
• Particle backscattering coefficient (bbp443)
• Aerosol Optical Thickness (T865)
• Exact normalised water-leaving radiance _at_ 412,
  443, 490, 510, 531, 555, 620nm
• Water-leaving radiance _at_ 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)

• Most products are available as Level-2 data
• Many other products available through SeaDAS
  data processing
• CZCS (Nov. 1978 June 1986) and OCTS data are
  also available
• ftp//oceans.gsfc.nasa.gov/
  http//oceancolor.gsfc.nasa.gov/cgi/level3.pl

11
Ocean Color time-series (Level-3) Contd

• Data available at
• ftpftp.oceancolor.ucsb.edu/pub/org/oceancolor/RE
  ASoN/
• OPeNDAP server http//dap.oceancolor.ucsb.edu/cg
  i-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
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
CAL/VAL
GHRSST Matchups
Ocean Color Matchups
15
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
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
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
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 gt 10yrs old, gt3500 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?