R. Quesada

Wavelet denoising technique for high-resolution CTD data. Characterization of turbulent oceanic flow

The analysis of high-resolution CTD vertical profiles (conductivity, temperature and depth) is a common method for characterizing environmental turbulent fluid dynamics. One of the objectives in analyzing high-resolution CTD profiles is to identify turbulent regions (patches) within the flow. Due to the instrumental noise of CTD measurements, the previous methods for turbulent patch identification, reported in the literature, are usually unable to identify patches at low-density gradient. Here we proposed a new method that significantly improves patch detection at low-density gradients. The method is based on a wavelet-denoising procedure and a theoretical analysis of the error in data obtained from the CTD sensors. The high percentage of validating patches, obtained in numerical and field tests, indicates that the method is a powerful tool for fluid dynamics characterization, and can be applied in a wide range of environmental monitoring applications.

Estimation of nonlocal turbulent mixing parameters derived from microstructure profiles

The present study proposes a new method for estimating nonlocal mixing parameters from microstructure data processing. The method could be particularly useful in studies of biologicalphysical interactions at small scale because it overcomes some of the limitations of the eddy diffusivity concept when dealing with the complex vertical pattern of biological and chemical tracers. The proposed method obtains empirically the coefficients of the transilient matrix, this being the discrete descriptor used in nonlocal mixing closure. The estimation is based on microstructure data analysis, in particular Thorpe displacement profiles, and includes three main steps: turbulent patch identification within each profile, turbulent patch characterization and multi-profile data averaging. A field case study is included to show how the estimated transilient coefficients, and the mixing parameters derived from them, are in accordance with what can be expected from the background external forcing and the observed thermal structure.

Characterization of turbulent regimes derived from high resolution CTD profiles. potential application to continuous profiling systems

The present study proposes a new method for estimating mixing parameters from continuous CTD profiling data processing. The method is mainly oriented to the continuous profiling systems that can be installed in permanent observatories. The method could be particularly useful in studies of biologicalphysical interactions at small scale, because it overcomes some of the limitations of the eddy diffusivity concept when dealing with the complex vertical pattern of biological and chemical tracers. The proposed method obtains empirically the coefficients of the transilient matrix, this being the discrete descriptor used in non-local mixing closure.

Wavelet Denoising Technique: Non white Gaussian noise reduction on oceanic microstructure data

Analysis of microstructure vertical profiles CTD (conductivity, temperature and depth) is a common method for characterizing environmental turbulent fluid dynamics. One of the objectives in analyzing high-resolution CTD profiles is to identify turbulent regions (patches) within the flow. Due to the instrumental noise of CTD measurements and the environmental characteristics, it is necessary a denoising process before the data analysis. The approaches presented in the literature for turbulent patch identification are usually unable to identify patches at low-density gradient. A new method was proposed in [1] to improve patch detection at low-density gradients. The method, pointed out the influence of wavelet mother selection and the noise characterization on the final denoising results. This article introduces a procedure to obtain the optimal wavelet filters selection to reduce noise effects. In the literature the studies based in wavelet denoising are focused on reduce the effects of white Gaussian noise. In turn, in this study, the signal representing the noise is synthetically created and modelled by both flicker and white Gaussian noise. Numerical results indicate that the selected wavelet optimize the denoising method presented in [1] and show the importance of optimizing the denoising process to identify patches in a wide range of density gradients.

Characterizing the Response of Aquatic Systems to Wind Burst Forcing by Using High-Resolution Spatial Sensors.

The characterization of the turbulent environmental flow is an important research topic to improve the overall knowledge of ocean dynamics. In this paper we analyze different methodologies to characterize the event processes (turbulent patches) associated to the environmental turbulent flow. The analysis of the transient response from a wind burst has been used as a framework for determining the best method of turbulent characterization based on different measurement systems