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

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) English Channel North Sea UK France Instruments Used:  CTD  ACS  BB-9  C-star  ECOFLRT  ECOFLCDRT  LISST 100x-type C  TROLL  ADV  ADCP

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. 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 North Sea data of bio-optical properties and optical constituents (19-April-2010). Data Analysis

6. Preliminary conclusions  Tidal intrusion of fresh water during the night time explains the dynamics optical constituents.  The value of b p -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 (b bp, b p -slope (ɣ), refractive index-n and c p ) are influenced by turbulent and inherit some of turbulence characteristics; high frequency noise, scale of variability at lower frequencies.

7. 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. Particles and Turbulence (in physics) Turbulence community results can help us here for these field studies

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

9. Power spectra of velocity components and dissipation 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) Transition (time scale 1000 s; length scale = 215m) Data Analysis

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

11. organic mineral Particle diameter 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 Data Analysis

12. Time series of PSD slope, c p -670 and Turbidity PSD slope C p -670 Turbidity Turbulent power spectra of PSD-slope, Cp and Turbidity Data Analysis Turbulence is one of the drivers of PSD slope, Cp and turbidity variability We still need to understand the mechanism of this driver

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 c p -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, Logonna Daoulas, 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…