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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…