David Antoine; André Morel

Ocean Optics XXI, Glasgow, Scotland, October 8-12, 2012

David Antoine; André MorelLaboratoire d’Océanographie de Villefranche (LOV), CNRS and Université Pierre et

Marie Curie, Paris 06, UMR 7093, Villefranche-sur-Mer, France

Stéphane Maritorena; David A Siegel; Norm B Nelson Earth Research Institute (ERI), University of California at Santa Barbara (UCSB), Santa

Barbara, California, United States of America.Department of Geography, University of California at Santa Barbara (UCSB), Santa

Barbara, California, United States of America

Hubert Loisel; David DessaillyLaboratoire d’Océanologie et de Géosciences (LOG), CNRS and Université du littoral,

côte d’opale, Wimereux, France

Evaluation of Particulate Backscattering InversionAlgorithms in Clear Oceanic Case 1 Waters


Rationale (1/3)

A number of “bbp algorithms”, i.e., inversion of radiometric quantities in terms of a and bb, exist (see, e.g., IOCCG report N°5, 2006)

Validation of the bbp retrieval from these algorithms is still quite limited, because of

1 – A lack of bb measurements (although the situation improves now)

2 – bb measurements are still dominated by either coastal waters or open ocean waters with relatively high [Chl], i.e., bbp(550) > ~0.002 m-1

Therefore, we don’t really know how these algorithms perform for waters that represent more than half of the global ocean, i.e., waters with bbp(550) < ~0.001-0.002 m-1

See, e.g., recent paper by Dall’Olmo et al., 2012, Optics Express 20(19)


Figs. 5A in Kostadinov et al., 2009, J. Geophys. Res., 114, C09015, doi:10.1029/2009JC005303

Average global repartition of bbp at 550 nm


Rationale (2/3)

This is important in particular in view of reducing uncertainty on the behaviour of particulate backscattering for low-Chl waters

Fig. 1 in Behrenfeld et al., 2005, Global Biogeochem. Cycles, 19, GB1006, doi10.1029 / 2004GB002299

Fig. 5a in Antoine et al., 2011, L&O, 56(3), 955–973

Fig. 1A in Huot et al., 2008, Biogeosciences, 5, 495–507


Rationale (3/3)A number of applications exist that use “satellite bbp” How uncertainties in bbp retrievals for clear waters may affect these results?

Fig. 3 in Loisel et al., 2006, J. Geophys. Res., 111, C09024, doi:10.1029 / 2005JC003367 Fig. 4C in Behrenfeld et al., 2005, Global Biogeochem.

Cycles, 19, GB1006, doi10.1029 / 2004GB002299

Figs. 5A and 7A in Kostadinov et al., 2009, J. Geophys. Res., 114, C09015, doi:10.1029/2009JC005303


Objectives

Use inversion algorithms of quite different nature, and apply them to in situ data sets in order to evaluate uncertainty in the final bbp product for clear waters.

The goal is not to perform an inter-comparison of algorithms with the idea of ranking algorithms

Application of the algorithms is performed in different configurations in order to evaluate robustness to:

1 – Loss of some information when using a single input quantity (Rrs) instead of both R and Kd

2 – Behaviour when fed with satellite Rrs, which includes additional errors from atmospheric correction


Data sets (1/2)

BOUSSOLE: Med. Sea clear waters, Chl from ~0.05-5 mg m-3, bbp(555): 0.0005-0.005

m-1

PnB Stations 2-6: More coastal, still Case 1, Chl from ~0.5-10 mg m-3, bbp(555): 0.0007-0.01

m-1

BIOSOPE: SE Pacific gyre, the most oligotrophic waters in the World oceanChl from ~0.02-5 mg m-3, bbp(555): 0.0002-0.005 m-1


Data sets (2/2)

Data from Hobilabs Hydroscat-4 (BOUSSOLE), Hydroscat-6 (PNB) sensors (Maffione and Dana,1997. Appl. Opt. 36: 6057–6067), Wetlabs EcoBB3 (BIOSOPE)Measurements & data analysis protocols:

Antoine et al. (2011) L&O, 56(3), 955–973 for BOUSSOLEKostadinov et al., 2007, J. Geophys. Res. 112 for PNBTwardowski et al. 2007, Biogeosciences 4, 1041-1058 for BIOSOPE


Algorithms

The GSM Model (Garver & Siegel, 1997; Maritorena et al., 2002)

Non-water components of absorption and scattering are expressed as

known shape functions with unknown magnitudes

New version of the Loisel and Stramski method (Loisel and Stramski, 2000; Loisel et al., 2001). No assumptions about spectral shapes for absorption and scattering (“No Spectral Assumption Algorithm” or “NSAA”)

LOV: (Morel et al., 2006, Deep-Sea Res. I, 53, 1439-1559) Just based on 2 equations:

Kd(l) = 1.0395 [a(l) + bb(l)] / md (Gordon, 1989, L&O 34)

R(l) = f' bb(l) / [a(l) + bb(l)]

LUTs are used for md and f’ (Morel & Gentili, 2004, J. Geophys. Res.)

For the 3 algorithms, bbw(l) is computed following Zhang et al. (2009, Opt. Exp. 17: 5698-5710) andZhang and Hu (2009, Opt. Exp. 17: 1671-1678), as a function of temperature and salinity


The test steps

1st step (ideal case):For algorithms using R and Kd as inputs: both R and Kd are

independently derived from field radiometry measurementsFor algorithms using Rrs as input: Rrs derived from field radiometry measurements

2nd step (algorithms using R and Kd as inputs):R is still derived from field radiometry measurements, but Kd is now modelled (either from Rrs or Chl)

3rd step :satellite Rrs are used for all algorithms (for algorithms using R and Kd

as inputs: both R and Kd are derived from satellite Rrs)


Results using R-Kd when feasible, and Rrs otherwise

PNBBOUSSOLEBIOSOPE

1 10-4

2 10-2


PNBBOUSSOLEBIOSOPE

Results using R-Kd but with Kd=f(Chl) and Rrs otherwise


Results using SeaWiFS Rrs

PNBBOUSSOLE


Results using SeaWiFS Rrs

All bands pooled together

PNBBOUSSOLE


Respective importance of seawater / particlesIn determining total bb (solid lines) and a (dashed lines)

443 nm550 nm

Using Morel & Maritorena (2001)


Getting accurate bbp in the field for clear waters

Effect of accounting for field determinations of dark currents on the bbp spectral slope (g)

(blue: with dark records included)

BOUSSOLE data (Hydroscat-IV measurements)


to conclude

Still very difficult to get accurate bbp from radiometry in clear waters

Still difficult as well to get accurate bbp field measurements in clear waters. The bbp values < ~0.001 m-1 determined in situ using currently available instrumentation have to be carefully considered

Overall the best results are obtained in the green, around l=550 nm

Seems illusory (at least difficult) to get bbp in the blue (l~440nm) by using only blue bands. Need methods that constrain to some extent the bbp derivation using more bands (e.g., GSM)

Degradation of results when using a modelled Kd instead of the measured one is not so dramatic

Which Kd is to be used? Field determination or modelled value from Rrs or Chl ? Using a model could actually decrease the noise of the inversion. The best thing to do might be to improve our determination of Kd from field radiometry.


Thank you for your attention

Questions?


Algorithms (1/3)

The GSM Model(Garver & Siegel, 1997; Maritorena et al., 2002)

Gordon et al. (1988)

Non-water components of absorption and scattering are expressed as known shape functions with unknown magnitudes (=unknowns):

• aph(λ) = Chl aph*(λ)

• acdm(λ) = acdm(443) exp(-S(λ -443))

• bbp(λ) = bbp(443) (λ /443)-η

aph*(λ), S and η were optimized for global applications using a large in situ data set.

Unknowns and their confidence intervals are retrieved by fitting the model to the observed Rrs using a non-linear least-square technique.


Algorithms (2/3)

New version of the Loisel and Stramski method (Loisel and Stramski, 2000; Loisel et al., 2001). No assumptions about spectral shapes for absorption and scattering (“No Spectral Assumption Algorithm” or “NSAA”)

Rrs is used as input parameter instead of R(0-) New formulation between : bb and (Rrs, Kd, mw, h) Kd(l) is retrieved from NN (Jamet et al., 2011) More realistic h and b/a combinations

How ?Radiative transfer simulations with no spectral assumptions (a=1, b/a [0.02 to 30], h[0.01-0.20 %]

Performance using the synthetic (error free)

IOCCG data set with the true Kd


Algorithms (3/3)

LOV: (Morel et al., 2006, Deep-Sea Res. I, 53, 1439-1559)

Just based on 2 equations:Kd(l) = 1.0395 [a(l) + bb(l)] / md (Gordon, 1989, Limnol. Oceanogr. 34:

1389-1409)

R(l) = f' bb(l) / [a(l) + bb(l)]from which

a(l) = 0.962 Kd(l) md(l, qs, Chl) x [1 – R(l) / f'(l, qs, Chl)]bb(l) = 0.962 Kd(l) md(l, qs, Chl) x [R(l) / f'(l, qs, Chl)]

LUTs are used for md and f’ (Morel & Gentili, 2004, J. Geophys. Res., 109, C6)

For the 3 algorithms, bbw(l) is computed following Zhang et al. (2009, Opt. Exp. 17: 5698-5710) andZhang and Hu (2009, Opt. Exp. 17: 1671-1678),

as a function of temperature and salinity

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David Antoine; André Morel