1. Characterization of the coupling between oceanic turbulence and Variability of coastal waters optical properties, using in-situ measurements and satellite data Renosh P.R. PhD. Student, University of Lille 1, Laboratoired’Oceanologie et de Geosciences, UMR LOG 8187 Arrival in France: 5 March 2012 Supervisors Prof.Francois G. Schmitt Prof. Hubert Loisel Funded by (CNES and CNRS)

2. Objective of the study • Coupling between turbulence and bio-optical properties. • Identify the scales corresponding to dominance of physics or biology in the spatial repartition of particulate matter. • Quantify these heterogeneities , coupling between passive and active scalars using spatial remote sensing of ocean color (MERIS, MODIS and GOCI) and sea surface temperature (MODIS,AATSR) under different physical forcing. • Methodology • Consider high spatial and temporal variability of bio-optical properties to study heterogeneity of oceanic scalars at different scales. • In-situ sampling at different meteorological conditions. • Satellite data will be using for analyse these heterogeneity. • Use of multi-scale approaches like Spectra and 2D structure functions.

3. Data collection North Sea 26-January-2010, 19-April-2010, 21-April-2010 and 7-July-2010 English Channel 28-March-2012 and 25-June-2012 (participate to data collection) • Instruments Used: • CTD • ACS • BB-9 • C-star • ECOFLRT • ECOFLCDRT • LISST 100x-type C • TROLL • ADV • ADCP North Sea UK English Channel France

4. Data Analysis North Sea data of bio-optical properties and optical constituents (26-January-2010). Power spectra of optical properties along with power spectra of passive scalars (T and S) Time series of physical, bio-optical and optical constituents from North Sea

5. Data Analysis North Sea data of bio-optical properties and optical constituents (19-April-2010). Power spectra of optical properties along with power spectra of passive scalars (T and S) Time series of physical, bio-optical and optical constituents from North Sea

6. Preliminary conclusions • Tidal intrusion of fresh water during the night time explains the dynamics optical constituents. • The value of bp-slope (ɣ) is relatively higher in mineral rich waters (mean 0.471 and % variance 20.29%) than in plankton rich waters (mean 0.242 and % variance 82.90%). • The optical parameters (bbp, bp-slope (ɣ), refractive index-n and cp) are influenced by turbulent and inherit some of turbulence characteristics; high frequency noise, scale of variability at lower frequencies.

7. Particles and Turbulence (in physics) • Turbulence effect on particles: • Influence of Turbulence on the particles are huge. • It may depend on particle size. • One way to characteristic this is to compute the stokes number. Where Turbulence communityresultscan help us here for thesefieldstudies

8. Data Analysis Dissipation rate Time Series of Dissipation Rate Intermittency of dissipation; mean value = 1.1787 x 10-6 Time Series of U, V and W components of velocity

9. Data Analysis Transition (time scale 1000 s; length scale = 215m) Typical Kolmogorov -5/3 power spectrum Power spectrum with slope -0.6 Transition Surf zone breaking waves (Schmitt et al. 2009) (time scales between 2-15 s) Power spectra of velocity components and dissipation

10. Data Analysis Selected 4 different size classes 5.72-6.76 µm 30.0-35.4 µm Power spectra of these 4 size classes 157-185 µm 359-424 µm Normalised Power spectra with larger size class

11. Data Analysis From epsilon value we can compute the Kolmogorov scale n= 1.1 mm Hence compute the Stokes number for different particle types (organic or mineral) Stokes number always small: particles are tracers mineral organic Particle diameter

12. Data Analysis PSD slope Cp -670 Turbulent power spectra of PSD-slope, Cp and Turbidity Turbidity Turbulence is one of the drivers of PSD slope, Cp and turbidityvariability Westillneed to understand the mechanism of this driver Time series of PSD slope, cp-670 and Turbidity

13. Conclusions • Interest in particles and turbulence: interplay • between optics and fluid dynamics. • We found Stokes numbers St between 0.01 and • 0.05: small values • Influence of turbulence on particle dynamics, • Turbidity, PSD-slope and cp -670.

14. Conference participation P.R. Renosh, F.G. Schmitt, H. Loisel, X. Meriaux and A. Sentchev. Analysis of a high frequency time series of bio-optical properties in complex coastal waters: couplings with turbulence. Time Series analysis in marine science and applications for Industry , 19-21 Sept. 2012, LogonnaDaoulas, Brest, France. (Poster Presentation). P.R. Renosh, H. Loisel, F.G. Schmitt, X. Meriaux, A. Sentchev and G. Lacroix. Origin of the high frequency variability of bio-optical properties in complex coastal environments. Ocean Optics Conference XXI, 8-12 Oct. 2012, Glasgow Scotland. (Poster Presentation). P.R. Renosh, F.G. Schmitt, H. Loisel, X. Meriaux and A. Sentchev. High frequency variability of particle size distributions and its dependency to turbulence in the optically complex coastal environment of the English Channel. Particles in Europe -2012, 17-19 Oct. 2012, Barcelona, Spain. (Oral Presentation).

15. Future Plan (2013) • Conduct more field campaigns to understand the coupling between bio-optical properties and Turbulence. • Preliminary results for the moments, need to confirm • Comparison with other sites • Understanding of -0.6 regimes and its influence on particles • Publish these results in peer reviewed journals

16. Thanks for your attention…