J. Piera, R. Quesada, A. Manuel-Lazaro, R. J. Del, S. Shariat Panahi, G. Olivar
{"title":"Wavelet denoising technique for high-resolution CTD data. Characterization of turbulent oceanic flow","authors":"J. Piera, R. Quesada, A. Manuel-Lazaro, R. J. Del, S. Shariat Panahi, G. Olivar","doi":"10.1109/ICSENS.2004.1426464","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":20476,"journal":{"name":"Proceedings of IEEE Sensors, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE Sensors, 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENS.2004.1426464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
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.