Principles of operation and use of SCAMP Gaspard Fourestier Supervised by Anne Petrenko and Andrea Dogliola

Plan Description SCAMP General description The different types of measures Operating Principle Upwards profiling Downwards profiling Signal Processing Determination of turbulent flow The spectrum of Batchelor Determination kb Determination Kz Aplication

SCAMP Self Contained Autonomous MicroProfiler Precision Measurement Engineering PME (Californie)

General description Measurements on a small scale (≈ 1mm) Frequency measures: 100Hz Light ≈ 6kg Deployment from small boats Move Free (fall and rise) Travel speed ≈ 10cm/s Maximum depth: 100m Two modes of acquisition are possible Sensor protection Main Sensors Float Brake Plate

The different types of measures For SCAMP basic measurements are made: Temperature (Quick / Precise) temperature gradient: mesure to bypass the speed with Conductivity (Quick! / Precise) → Salinity Pressure → Depth →Speed Optionally, you can make measurements of: Turbidity Fluorometer Photosynthetically Active Radiation (PAR) Oxygen Concentration dTdT dtdt dT dz

Different sensors Source: Hodges_TH_Deploying a microstructure profiler in Corpus Christi Bay.pdf (CRWR on-line report 06-07; edu/online.html)

Different sensors Image A. Rumyantseva SCAMP

Upwards profiling Allows measurements close to the surface Float high position Stone to dive Plate brake free Diving at 45 ° Measurements on undisturbed water Fond Surfac e Profiling Pebbl e

Downward profiling Allows measurements close to the bottom Float position 'low' Blocking the plate brake Ballast Surface Fond Ballast Floater Profiling

Determination of turbulent flow In turbulent flow: with i= v,T or S Need to determine K i z There are different methods to determine K v z For example Osborn's method(1980):, Determination N ρ =f(T,C) measured ε ≈ watt.kg -1 (Gregg, 1989) With SCAMP: estimating ε

The Batchelor Spectrum We have the two equations: K v z ≈ K T z χ: dissipation of temperature due to the molecular diffusivity ε: dissipation of turbulence due to Cin in the molecular viscosity Batchelor (1959): analytical solution equation for the advection- diffusion T Theoretical spectrum Gradt (Batchelor spectrum): S(k) = f(k, k b, χ) Relation between ε and kb (Batchelor wavenumber)::

Determination k b Measure Grad T s_getseg. m Spectrum calculated S exp (k) s_psd.m Theoretical Batchelor spectrum of S (k) k b parameter, χ fixed s_bspect.m Final Batchelor spectrum s_bspect.m kbkb Discrete Fourier transformation FFT method Estimation χ s_X.m Noise spectrum of SCAMP S n (k) s_snoise.m Maximizing the likelyhood of S exp (k) and S(k) s_c11.m [Ruddick, Barry, Anis, Thompson, Keith. 2000: Maximum Likelihood Spectral Fitting: The Batchelor Spectrum Journal of Atmospheric and Oceanic Technology: Vol. 17, № 11, pp ]

Determination k b T' energy, S(k) [(°C/m)²/cpm] ε, [w/kg] Wavenumber, k, [cpm] Calculated spectrum Theoretical spectrum

Determination K z Turbulence differs depending on the depth → segmentation water column Determination N ρ =f(T,C) measured Determination ε Osborn's method(1980):, To determine the flow: N – Brunt–Väisälä frequency Ri – Richardson number

Application Sharples et al. (2003): Determination of ε → Kz and flows dissolved O2 (Estuary south of Australia) MacIntyre et al. (1999): Determination of ε → flows and Kz ammonium (NH 4) (Mono Lake, California) Anis et al. (2006): Study of turbulence in a Mexican lake Determination of ε, χ and Kz and comparison with a model