Contributors:

1. The IOCCG Atmospheric Correction Working Group Status ReportThe Eighth IOCCG Committee Meeting Department of Animal Biology and Genetics University of Florence, Florence, ItalyFebruary 24-26, 2003Menghua Wang Contributors: MERIS D. Antoine, A. Morel, B. GentiliOCTS/GLI H. Fukushima, R. FrouinPOLDER P. Deschamps, J-M. NicolasMODIS H. GordonSeaWiFS M. Wang

2. Goal of the Atmospheric Correction Working Group • The atmospheric correction working group activity was proposed by R. Frouin at the 5th IOCCG committee meeting in Hobart, Tasmania, and endorsed by committee and representatives of various space agencies participated at the meeting. • The main objective of the working group is to • quantify the performance of the various exiting atmospheric correction algorithms used in the various ocean color satellite sensors; • the derived products from various ocean color missions (projects) can be meaningfully compared and possibly merged. • how can derived ocean color products from one sensor be best compared with those from others?

3. Membership The Working Group is composed of: Antoine, Morel MERIS Dechamps POLDER Fukushima, Frouin OCTS/GLI Gordon MODIS Wang SeaWiFS Others are welcome to participate. A general requirement for people to join the Working Group is that they can contribute a well documented algorithm and participate some of tests.

4. Atmospheric Correction Algorithms The performance of the following atmospheric correction algorithms are intended to be tested and compared: • SeaWiFS/MODIS algorithm (Gordon and Wang, 1994) • POLDER algorithm (POLDER document, Feb. 1999) • OCTS/GLI algorithm (Fukushima et al, 1998) • MERIS algorithm (Antoine & Morel, 1999) Testing of the above 4 operational algorithms is the necessary requirementfor the objective of the Working Group. Results from other algorithms for some special cases, e.g., Spectral Matching algorithm for absorbing aerosols, are also useful.

5. Parameters The derived parameters to be compared and tested are: • the normalized water-leaving reflectances at the visible wavelength bands; • two-band ratio values of the derived normalized water-leaving reflectances, i.e., 443/555 and 490/555; and • the atmospheric parameter--the derived aerosol optical thickness at 865 nm.

6. Sensor Spectral Characterizations All comparison algorithms are operated (some have been modified for this purpose) using the same spectral bands of 443, 490, 555, 765, and 865 nm.

7. The TOA Reflectance (testing data) Generation The TOA reflectances were generated based on the following: • rwis the water-leaving reflectance from model (Case-1) or measurements (Case-2). • rristhe Rayleigh reflectance. • A = ra+rrais the aerosol and Rayleigh-aerosol contributions. • t is the atmospheric diffuse transmittance. • the sun glint and whitecap contributions are ignored. • gas absorption is ignored.

8. Testing Data Sets Simulated Data Sets: • For the open ocean cases • a polarized RTE (Monte Carlo method) was used for simulations with 15 million photons for each vector RTE run (within ~0.5% at blue); • TOA reflectances for spectral bands at 412, 443, 490, 510, 555, 670, 708, 765, 779, and 865 nm (total 10 spectral bands) were generated; • a two-layer plane-parallel atmospheric model (78% of molecules at the top layer); • aerosols (Maritime with RH=80%,M80) located at the bottom layer mixed with 22% of molecules (Rayleigh scattering); • aerosol optical thicknesses at 865 nm: 0.05, 0.1, and 0.2; • a Fresnel reflecting ocean surface with pigment concentrations of 0.03, 0.1, 0.3, and 1.0 (mg/m3) from Gordon et al. (1988) model; • no gas absorption, no whitecap contributions; • the solar zenith angles: 0o, 45o, 60o, 65o, 70o, and 78o; sensor viewing angles: 5o, 25o, 45o, 55o, and 65o; and relative azimuth angle of 90o.

9. Therefore, 15 million photons were used for each vector RTE simulation

10. Uncertainty is usually within ~0.5% at the blue

11. Testing Data Sets (cont.) • Some cases for sensitivity studies (simulated data sets) • absorbing aerosols: Urban aerosols with two type vertical distributions, i.e., two-layer and uniformly mixed one-layer cases; • case 2 water—although algorithms are mostly intended for case 1 water, a quantitative estimation of atmospheric correction error over case 2 water is needed. Data from SeaWiFS measurements (this is still open….): • open ocean cases (with various locations and seasons); • coastal region ocean waters; • some trouble cases, e.g., nLw<0, dust contamination, etc. For testing and comparison, SeaWiFS data sets are usually co-located with in situ measurements. It was agreed that SeaDAS will be used.

12. Diffuse Transmittance Issue It was realized that there were two fundamentally different approaches in computing the atmospheric diffuse transmittance and effect the atmospheric correction: • the SeaWiFS/MODIS algorithm assumes that the water-leaving radiance justBENEATHthe sea surface is uniform. • the POLDER algorithm (University of Lille) assumes that the water-leaving radiance justABOVEthe sea surface is uniform. • in addition, the POLDER team includes a factor of the multiple surface reflection contribution, i.e., 1/[1-S*rwn]. However, the t difference is usually within ~2%, while difference from the multiple surface reflection factor is within ~1%. Therefore, a simple correction to the POLDER results was proposed and agreed within the group. The correction has been applied to the POLDER results.

14. Atmospheric Contributions: Maritime Aerosol(2-layer)

15. Atmospheric Contributions: Absorbing Aerosol (2-layer)

17. NOTE: Significant different contribution in magnitude from these two type waters !!

18. Maritime Aerosol(2-layer) Cases

19. Maritime Aerosol(2-layer) Cases

20. Absorbing Aerosol (2-layer) Cases

21. Absorbing Aerosol (1-layer) Cases

22. NIR reflectances are not enough to retrieve absorbing aerosol properties

24. ALL COMPARISON RESULTS AREPRELIMINARY!

25. WORK IS IN PROGRESS …….

26. IOCCG Report Outline • Introduction • Atmospheric correction working group: objectives, members, procedures, etc. • Overview of the atmospheric correction for ocean color sensors • Algorithm Description • MERIS • POLDER • OCTS/GLI • SeaWiFS/MODIS • Others, e.g., spectral-match algorithm for absorbing aerosols, etc. • Simulated Data Set • Brief description of the vector Monte-Carlo RTE for the data set • Uncertainty of the data set, e.g., noise, accuracy, etc. • Atmospheric model, e.g., two-layer, one-layer, aerosols: M80, U80, surface, etc. • Ocean data set: Case-1 and Case-2 • Diffuse transmittance: assumptions, computations, and two approaches • Generating TOA data from atmosphere and ocean data set

27. IOCCG Report Outline (cont.) • Comparison Results • Open ocean (Case-1) with Maritime aerosols • Case-1 water with absorbing (Urban) aerosols • Case-2 water with Maritime aerosols • Case-2 water with absorbing (Urban) aerosols • Vertical effects for the absorbing aerosols • Discussions • Errors from various algorithms: radiance, ratio, aerosol thickness • Influence of errors in the ratio values (the normalized water-leaving radiance) to the bio-optical algorithm, e.g., the chlorophyll retrievals • Cases for absorbing aerosols, Case-2 waters, etc. • Vicarious calibration • Others • Recommendations and Conclusions • Future Work • Algorithm comparison with real satellite measured data, e.g., SeaWiFS data

28. Status/Time Schedule • Setting up working group (done). • Draft a proposal for discussing in the 1st working group meeting in May 16-18, 2000 (done). • Revise working plan based on discussions(done). • Generate the testing data sets: ~3-4 months (done). • The 2nd working group meeting was held on 1/18/2002 (done). • Diffuse transmittance issue was resolved: ~5 months (done). • Algorithm testing and results analyses: (on going). • Write up an IOCCG report: (on going). • Workshop for the working group: (planned). • A journal paper: (planned). • Algorithm comparison with real satellite data (e.g., SeaWiFS, data)??? (open).