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
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.
SST
NPP
SST
NPP
NPP Changes (%)
SST Changes ( 0C )
+3
+60
a
+2
+1
0
-1
-2
-3
b
+30
0
-30
-60
c
A few SST time-series
Time-Series
Data
Spatial Resolution
Temporal
resolution
Time period
GHRSST
L2P
L4
1/4 degree - 6km
Daily
1985 - Present
4.5 km – 9 km
Daily
8-Day
Monthly
Annual
Feb. 2000 – Present (T)
Jul. 2002 – Present (A)
4 km
Daily
5 Day
7 Day
8 Day
Monthly
Annual
1985 - 2006
2 km – 18 km
Weekly
Swath
Nov. 1981 – Feb. 2001
Aug. 2001 – Oct. 2005
Aug. 2001 - Present
6 km
Hourly
May 2003 - Present
2 degrees
Weekly
Monthly
1981 - Present
MODIS
Thermal IR
Mid-IR
AVHRR
Pathfinder
v5
AVHRR
MCSST
NAVOCEANO
Miami
GOES
(Regional)
NCEP
Reynolds
OI – MCSST
In Situ
GHRSST-PP
• GODAE (Global Ocean Data
Assimilation Experiment) HighResolution 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.
NASA Carbon Cycle and Ecosystems Joint Science Workshop
April 28, 2008
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
Ocean Color time-series (Level-3)
Source
ESA
GlobCOLOUR
SeaWiFS
MODIS-AQUA
MERIS
Products
CHL1 (2)
TSM CDM
BBP K490
nLw(λ)
EL555
AOT
Cloud Fraction
(+ uncertainties for
some)
Merged
http://www.globcolour.info/index.html
Spatial
resolution
4.5 km
1/4
1
Temporal
resolution
Daily
8-Day
Monthly
Time period
Sep. 1997 – Present
(SeaWiFS)
Jul. 2002 – Present
(Merged)
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 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 Products
European Service
for Ocean Colour
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 (Kd490)
•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
Ocean Color time-series (Level-3)
Source
NASA OBPG
SeaWiFS
MODIS-TERRA
MODIS-AQUA
Products
CHL
K490
nLw(λ)
PAR (SeaWiFS)
SST
AOT
Angstrom
coeff.
ε_78
Merged CHL
Calcite
FLH
KPAR
Zeuph
Spatial
resolution
4.5 – 9 km
Temporal
resolution
Daily
(3-Day – Aqua)
8-Day
Monthly
Seasonal
Yearly
Time period
Sep. 1997 – Present
(SeaWiFS)
Feb. 2000 – Present
(Terra)
Jul. 2002 – Present
(Aqua)
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/
http://oceancolor.gsfc.nasa.gov/cgi/level3.pl
Ocean Color time-series (Level-3) Cont’d
Source
Products
NASA
ReaSON
(UCSB)
GSM CHL
GSM CDM
GSM BBP
+
Confidence
intervals
SeaWiFS
MODIS-AQUA
Merged
&
individual
sensors
Spatial
resolution
Temporal
resolution
9 km
Daily
4-Day
8-Day
Monthly
Time period
Sep. 1997 – Present
(SeaWiFS)
Jul. 2002 – Present
(Merged & Aqua)
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. NOAA’s COASTLOOK
Upcoming OC sensors: VIIRS (NPP/NPOES), OCL (S3, ESA), OCM-2 (Oceansat-2, ISRO)
ESDRs, CDRs and CAL/VAL
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.”
NASA Carbon Cycle and Ecosystems Joint Science Workshop
April 28, 2008
CAL/VAL
GHRSST Matchups
Ocean Color Matchups
M-AERI cruises and MODIS validation statistics
NASA Carbon Cycle and Ecosystems Joint Science Workshop
April 28, 2008
ISSUES/CONCERNS
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 subPAR ocean color sensor ?
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, MODIS’s, 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)
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
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-AERI’s and Calibration Facilities at UM-RSMAS
• M-AERI’s > 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
NASA Carbon Cycle and Ecosystems Joint Science Workshop
April 28, 2008
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?