Kevin Ruddick (MUMM/RBINS, Belgium)

1. Atmospheric correction of ocean colour data for extremely turbid waters:assumptions and uncertainties Kevin Ruddick (MUMM/RBINS, Belgium)

2. Objectives of presentation • Aerosol correction over turbid waters • Summarise approaches • Link algorithm assumptions to performance • Assess uncertainties theoretically • Scope of presentation • Just the extra problems of turbid waters

3. Approaches to aerosol correction • 1. Dark/bright pixel aerosols • estimated at long wavelength with zero/simple marine refl. • extrapolated to shorter wavelengths • e.g. [Gordon and Wang, 1994] • 2. Multispectral matching • best fit to coupled ocean/atmosphere model • e.g. [Doerffer and Fischer, 1994] • 3. Polynomial atmospheric path radiance (also for sunglint!) • atmospheric path radiance = Rayleigh + c0 + c1*λ-1 + c2*λ-4 • [Steinmetz, 2011]

4. Dark/bright pixel approaches - notation • Gordon and Wang [GW1994]: • Rayleigh and gas corrections => “Rayleigh-corr.” reflectance • Aerosol estimation in near infrared (NIR) • Extrapolate aerosol reflectance to blue (412nm-670nm) • Drop TOA and “0+” notation • For this presentation, approx. • If two wavelengths where is known then can estimate two aerosol properties, e.g.

5. Dark/bright pixel – A bit of history • [Gordon, 1978] assume dark red: • BUT for moderately turbid waters bright red • [Guan et al, 1985] propose • [GW1994] dark NIR: • BUT for turbid waters bright NIR • [Ruddick et al, 2000] propose • AND [Moore et al, 1999; Hu et al, 2000; Stumpf et al, 2003; ...] • [Wang/Shi, 2005] dark SWIR: • BUT for extremely turbid waters bright SWIR • [Shi and Wang, 2009] find • AND [Knaeps et al, 2012] measure in situ

6. In situ Pure water absorption and “similarity spectrum” • NIR/SWIR marine reflectance has simple form: • e.g. “similarity spectrum” model [Ruddick et al, 2006] « Constant » Spectral shape Magnitude Particle size/type … SWIR [SeaSWIR project]

7. Dark/Bright pixel – spatial homogeneity? • Assumption of spatial homogeneity of aerosol type (Angstrom coefficient,τa, “model”) from clear water pixels can replace marine assumption(s) e.g. [GW1994] and [Stumpf et al, 2003] have: • no assumptions for aerosol type • two assumptions for marine reflectance • [Ruddick et al, 2000 for NIR; Wang, 2007 for SWIR] has: • spatially fixed aerosol type • one assumption for marine reflectance • Variable/Fixed aerosol type approaches – which is best?

8. Dark/Bright pixel - classification • Propose to classify all (?) Dark/Bright pixel approaches as: • Variable or Fixed aerosol type • Two wavelengths used for aerosol • Marine reflectance model/assumptions

9. Dark/Bright pixel – from assumptions to uncertainty • [Ruddick et al, 2000] assumes • giving uncertainty for SeaWiFS band i (7=765nm, 8=865nm) Marine reflectance error Fixed aerosol error Marine model error Atmospheric reflectance Marine reflectance Extrapolation factor Marine/aerosol spectral diff. “Leverage” amplification

10. Conclusions For the dark/bright pixel algorithms we can estimate marine reflectance spectral error if we can estimate marine model error(s) at NIR/SWIR wavelengths • can theoretically compare different: Marine model assumptions Wavelength choices Fixed/Variable aerosol assumptions (also propagate impact of noise, digitisation, etc.)

11. The Challenges • Can we estimate marine model error(s) at NIR/SWIR wavelengths for all dark/bright pixel algorithms? • Can we estimate errors for other types of algorithm (multispectral fitting, polynomial)? • Do theoretical error estimates fit in situ validation results? • What are remaining unknowns for NIR/SWIR marine reflectance models? • particulate backscatter spectral slope • non-linear reflectance models for high bb/a • salinity/temperature variation of pure water absorption • … and NIR/SWIR aerosol models??

12. Acknowledgement and references • Belgian Science Policy Office for BELCOLOUR (2006-11) and BEL-AERONET (2012) funding • References