Comparisons of ocean colour merged data sets

Stéphane MaritorenaICESS

University of California, Santa Barbara

Special thanks to Odile, Antoine and the ACRI-ST Team

OUTLINE

• Current Ocean Colour merged data sets and associated merging techniques and products.

• Coverage• Time-series• Matchups• Frequency distributions• Error estimates

Ocean Color Merged Data Sets

• REASoN (ICESS/UCSB)

• NASA OBPG

• GlobCOLOUR

MERGED DATA SETS

REASoN NASA OBPG GlobCOLOUR

Input DataSeaWiFS

MODIS-AQUA

SeaWiFS

MODIS-AQUA

MERIS

SeaWiFS

MODIS-AQUA

Merging methodGSM01 model (merges the Lwn())

Weighted average GSM01 model

(Lwn() weighting)

Weighted average

Products

CHL

CDM

BBP

(+ uncertainties)

CHL 19 products

(+ uncertainties for some)

Spatial, temporal resolution

9 km

Daily, 4-Day, 8-Day, Monthly

9 km

Daily, 8-Day, Monthly, Yearly

4.5, 1/4, 1Daily, 8-Day, Monthly

Daily coverage using SeaWiFS/Aqua and Meris (2003 data)

GlobCOLOURNASAREASoN

Sensor(s) Coverage (%) Std. Dev. (%)

SeaWiFS 16.65 2.01

Aqua 13.76 1.15

Meris 8.51 1.48

SeaWiFS/Aqua 24.22 1.94

SeaWiFS/Meris 22.24 2.40

Aqua/ Meris 19.92 1.74

SeaWiFS/Aqua/Meris 28.85 2.241

Ocean color sensorsaverage daily coverage (2003 data)

Da

ys

FREQUENCY OF COVERAGE (2005)

Merged

SeaWiFS Aqua

MERIS

AQUA

SeaWiFS

Relative contribution of each sensor to an 8-Day composite

THE 30 ZONES

Time-series CHL - Monthly data (Cont’d)

Time-series CHL - Monthly data (Cont’d)

Time-series - CDM - Monthly data

Time-series BBP - Monthly data

Issues with the particulate backscattering product

Meris issue

Mostly a SeaWiFS issue

Noise in the SeaWiFS Lwn() around gaps caused by clouds. In these areas, the Lwn() are sometimes higher than in nearby gap-free areas and this results in enhanced bbp (443) values.

Problem does not exist in Aqua data

MERIS shows some stripes of high BBP values on some swaths.

Matchups - CHL

In situ data set (NOMAD + SeaBASS) withCHL: ~3100 stationsCDM: ~700 stationsBBP: ~180 stations

Same day matchups, 3x3 box,9 km data (4.5 km for GlobCOLOUR).

Glo

bCO

LOU

RR

EA

SoN

CDM BBP

FREQUENCY DISTRIBUTION - CHL - 50N-50S Deep Water

FREQUENCY DISTRIBUTION - CDM - 50N-50S Deep Water

FREQUENCY DISTRIBUTION - BBP - 50N-50S Deep Water

Monthly ChlorophyllMay 2006

Error estimates at pixel level (%)Chla – May 2006

100%

50%

0%

Summary

• The GlobCOLOUR data set provides better daily coverage thanks to the use of the MERIS data.• GlobCOLOUR also offers more products and several resolutions.

• CHL• The three merged data sets are very consistent most of the time, except in coastal zones (Z < 1000 m).• MERIS alone tends to produce higher CHL values than SeaWiFS or AQUA.• AQUA alone tends to produce lower CHL values than SeaWiFS or MERIS

Summary (Cont’d)

• CHL (Cont’d)• The REASoN and GlobCOLOUR (GSM) data contain less

low CHL values than the NASA OBPG data. Also true for REASoN at high CHL values but better agreement in summer.

• CDM• The agreement between the GlobCOLOUR and REASoN

merged CDM products is excellent, always, everywhere.

• BBP• SeaWiFS and MERIS BBP products are sometimes very

(too) high. MODIS-AQUA BBP product appears more stable and reasonable.

Conclusion

• The three merged data sets look good and are in good agreement overall.

• Better agreement between the merged products than between the products from the individual sensors.

• Some issues exist (BBP mostly) that need to be looked at.