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

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.

Data collectionNorth Sea

26-January-2010, 19-April-2010, 21-April-2010 and 7-July-2010

English Channel28-March-2012 and 25-June-2012

(participate to data collection)

Engl

ish

Chan

nel

North Sea

UK

France

Instruments Used: CTD ACS BB-9 C-star ECOFLRT ECOFLCDRT LISST 100x-type C TROLL ADV ADCP

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

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

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.

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.

𝑺𝒕𝒐𝒌𝒆𝒔𝑵𝒖𝒎𝒃𝒆𝒓 𝑺𝒕=𝜷𝟏𝟖 (𝝈𝜼 )

𝟐

Where

𝑺𝒕𝒐𝒌𝒆𝒔𝑵𝒖𝒎𝒃𝒆𝒓 𝑺𝒕=𝝉𝒑

𝝉 𝒇

𝑺𝒕𝒐𝒌𝒆𝒔𝑵𝒖𝒎𝒃𝒆𝒓 𝑺𝒕=𝝉𝒗

𝝉𝜼

Particles and Turbulence (in physics)

Turbulence community results can help us here for these field studies

Time Series of U, V and W components of velocity

Time Series of Dissipation Rate

Dissipation rate

Intermittency of dissipation; mean value = 1.1787 x 10 -6

𝛆=𝐂×𝛎×((𝐝𝐔𝐝𝐭 )𝟐

+(𝐝𝐕𝐝 𝐭 )𝟐

+(𝐝𝐖𝐝𝐭 )𝟐)÷ (𝐔𝟐+𝐕𝟐+𝐖𝟐 )

Data Analysis

Power spectra of velocity components and dissipation

Typical Kolmogorov -5/3 power spectrumPower 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

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

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

Time series of PSD slope, cp-670 and Turbidity

PSD slope

Cp -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 variabilityWe still need to understand the mechanism of this driver

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.

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).

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

Thanks for your attention…