1. Optical variability and optical « anomalies » in Mediterranean waters André Morel, David Antoine and Hervé Claustre Laboratoire d’Océanographie de Villefranche (CNRS and Univ. P. M. Curie)

2. Is desert dust making oligotrophic waters greener? ( H. Claustre et al., GRL, 2002) Field data (PROSOPE Cruise), versus Remote Sensing OC algorithms (OC4V4 and OC4Me) Blue-to-green ratio: Anomalously low In Med-Sea PROSOPE cruise

3. Depth of the euphotic layer, as expected from Surface [Chl] Hyperspectral Model (MM01) Sun at 0° or 75° -Uniform profiles (solid lines) or -profiles including a DCM (dashed lines) Recent data Med-Sea data (anomalously low Zeu) (Morel & Gentili, 2004)

4. Mediterranean Sea : A semi-enclosed basin, Rather well ventilated, however (water residence time rather short ~ 70 y) Arid climate, and reduced run off limited continental shelf A priori, a Case 1 water domain, with varying trophic status: Predominantly oligotrophic, sporadically and periodically mesotrophic (Blooms) SO, why « anomalies »?

5. Anomalies, or nuances, detectable against « a standard » for Case 1 waters Therefore, Defining a « standard » is a prerequisite, Possibility: Consider the average empirical relationships established between some optical properties (IOP and AOP) and (Chl), used as an index of the bio-optical state.

6. « Standard » for Case 1 waters? Historical empirical relationships provide such average laws (+ SD), (generally non-linear laws of (Chl)) For instance: IOP ap(λ, [Chl]) = A(λ) [Chl] ^B(λ) Bricaud et al, bp(λ, [Chl]) = Bo(λ) [Chl] ^ β(λ) Gordon-Morel, Loisel-Morel cp(λ, [Chl]) = Co(λ) [Chl] ^ γ (λ) Voss AOP Kd(λ,[Chl]) = Kw (λ) + χ(λ) [Chl] ^e(λ) Morel-Maritorena. Rrs(λ1) / Rrs(λ2) = Pol ([Chl]) O’Reilly et al.

7. COMPATIBILITY BETWEEN THESE EMPiRICAL LAWS ? has to be checked before ascertaining “Standards”, and being able to identify “nuances” 1) Closure (IOP) ? ? ap (λ, [Chl]) + bp(λ, [Chl]) = cp(λ, [Chl]) (Bricaud et al, ) (Gordon-Loisel-Morel) (Voss) 2) Coherency (IOP/AOP) ? Possible Inversion Kd (λ, [Chl]) → atot (λ, [Chl]), (with atot = ap + ay + aw) ? atot (λ, [Chl]) > ap (λ, [Chl]) if yes then ay (λ, [Chl]) = ? :

8. From Bricaud et al., 1998: ap(λ) as f(Chl) Average law and confidence interval (example for 440nm) Data Med-Sea

9. Loisel-Morel, L&O, 1998 slope 0.766

10. Closure: c = a + b - Medit. Sea (above average relationship

11. (Med-Sea)

12. Kd = 1.0395 (μ d ) -1 (a + b b ) R = f’ [b b / (a + b b )] a(λ) = 0.962 Kd (λ) µ d (θ s, λ, Chl ) [ 1 - R(λ ) / f’(θ s, λ, Chl )] b b (λ) = 0.962 Kd (λ) μ d (θ s, λ, Chl ) [ R(λ ) / f’(θ s, λ, Chl )] Look up Tables for μd and f’ (Morel-Gentili, JGR 2004) INVERSION (AOP -> IOP)

13. Compatibility between ap and Kd Inversion (Kd → atot) through: atot(λ,[Chl]) = 0.962 Kd (λ,[Chl],θs) μd(λ,[Chl],θs) { 1- R(λ,[Chl],θs)/f’(λ,[Chl],θs)} R(λ,[Chl],θs), f’(λ,[Chl],θs), and μd(λ,[Chl],θs) in LUTs (from RTE computations) Then: atot = ap + ay + aw Is atot coherent with ap ? (i.e., atot > ap )

14. Examples of Kd(λ) ↔ (Chl) empirical relationships NOMAD Data Black curves: Morel-Maritorena Statistical relationships

15. Example of Inversion Kd(412)  atot (412 ) Then Decomposition atot = (ap + aw) + ay

16. a y (412) from the previous figure + a y Data (Pacific) also obtained by inversion using Kd and R Conclusion; Pacific waters close to standard Case 1 water regarding ay

17. a y (412) from the previous figure + Data (Med. Sea) also obtained by inversion Moroccan upwelling Conclusion: Med-Sea waters above standard regarding ay

18. CONCLUSION Empirical relationships are compatible, can be used to define « standard », Chl-dependent, Case 1 waters With respect to this standard, Med-Sea waters exhibit notable, and identified nuances (thence anomalous reflectances already detected) ( Note: particulate absorption, as usual ) 1) excess of Yellow Substance (seasonal? regional? Blooms in the Northern part? bacterial activity?) 2) slight excess of particle scattering (Saharan dust? Coccoliths?) 3) Bio-geo-chemical reasons are not yet elucidated