Wavelet methods: application to the study of the stable atmospheric boundary layer under non-stationary conditions

Terradellas, Enric; Morales, Guillermo A.; Cuxart, Joan; Yagüe, Carlos

doi:10.1016/s0377-0265(01)00069-0

Cited by 60 publications

(71 citation statements)

References 20 publications

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“…Based on the WT presented in [18], the CWT has been applied to analyze the data from Figure 1 by customizing a widely accessible software tool developed by Torrence and Compo (http://paos.colorado.edu/research/wavelets/). Similar analyses of the time series have been used for numerous studies in various science areas; see [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32] for examples.…”

Section: Wavelet Analysis Resultsmentioning

confidence: 99%

Wavelet Multiscale Analysis of a Power System Load Variance

Avdaković¹,

Nuhanovic²,

Kusljugic³

2013

Turk J Elec Eng & Comp Sci

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Wavelet transform (WT) represents a very attractive mathematical area for just more than 15 years of its research in applications in electrical engineering. This is mainly due to its advantages over other processing techniques and signal analysis, which is reflected in the time-frequency analysis, and so it has an important application in the processing and analysis of time series. In this paper, for example, the analysis of the hourly load of a real power system over the past few years was performed by applying the continuous WT and using the Morlet wavelet function. The resultsshow that this approach of data analysis can give a better insight into the basic characteristics of the consumption and identify the characteristic periods of the power system load variances over the past years, which can be very interesting for power system planners.

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Section: Wavelet Analysis Resultsmentioning

confidence: 99%

Wavelet Multiscale Analysis of a Power System Load Variance

Avdaković¹,

Nuhanovic²,

Kusljugic³

2013

Turk J Elec Eng & Comp Sci

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“…This is obtained by using wavelet functions that are finite in time, as opposed to the infinite sines and cosines used in the Fourier analysis. This tool has been used in many geophysical studies and it is especially useful in the analysis of the turbulent motions over plant canopies, which are not always periodic and stationary (Farge, 1992;Collineau and Brunet, 1993b;Turner et al, 1994;Terradellas et al, 2001;Krusche and De Oliveira, 2004;Bolzan and Vieira, 2006). In this work, a package of Matlab scripts called Wavelab 2 was used to decompose the time series using orthogonal wavelets.…”

Section: Methodsmentioning

confidence: 99%

Scale dependence of coherent structures' contribution to the daytime buoyancy heat flux over the Pantanal wetland, Brazil

Zeri

Sá

2011

Atmospheric Science Letters

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The contribution of organized motions to buoyancy heat flux was determined for several time scales by applying wavelet decomposition to signals of vertical velocity and air temperature. Measurements were performed using an eddy covariance system installed over the Pantanal wetland, in Brazil, during two campaigns (1998 and 1999). The signals were decomposed in several time scales and then used in the quadrant analysis. Overall, coherent structures were responsible for ∼40% of the buoyancy heat flux, if the contributions of ejections and sweeps are summed over the range of 10-100 s, which excludes the contribution of stochastic high-frequency turbulence and low-frequency mesoscale motions.

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“…Moreover, wave parameters (wavelength, phase speed and direction of propagation) have been evaluated using phase differences analysis (Terradellas et al, 2001;Viana et al, 2009). This method is based on the time differences observed in the wavelet spectral energy peaks of an atmospheric variable measured at least at three different sites at the surface.…”

Section: Wavelet and Phase Differences Analysesmentioning

confidence: 99%

“…2.2.1), knowing the exact position of each microbarometer (Terradellas et al, 2001;Viana et al, 2009). This method is based on the differences between wave phases of the three filtered pressure records (one for each microbarometer).…”

Section: Wave Event 1 (19:00 To 20:25 Utc Sdf)mentioning

confidence: 99%

Interactions among drainage flows, gravity waves and turbulence: a BLLAST case study

et al. 2015

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Abstract. The interactions among several stable-boundarylayer (SBL) processes occurring just after the evening transition of 2 July 2011 have been analysed using data from instruments deployed over the area of Lannemezan (France) during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The near-calm situation of the afternoon was followed by the formation of local shallow drainage flows (SDFs) of less than 10 m depth at different locations. The SDF stage ended with the arrival of a stronger wind over a deeper layer more associated with the mountain-plain circulation, which caused mixing and destruction of the SDFs. Several gravity-wave-related oscillations were also observed on different time series. Wavelet analyses and wave parameters were calculated from high resolution and accurate surface pressure data of an array of microbarometers. These waves propagated relatively long distances within the SBL. The effects of these phenomena on turbulent parameters (friction velocity and kinematic heat flux) have been studied through multi-resolution flux decomposition methods performed on high frequency data from sonic anemometers deployed at different heights and locations. With this method, we were able to detect the different time-scales involved in each turbulent parameter and separate them from wave contributions, which becomes very important when choosing averaging-windows for surface flux computations using eddy covariance methods. The extensive instrumentation allowed us to highlight in detail the peculiarities of the surface turbulent parameters in the SBL, where several of the noted processes were interacting and producing important variations in turbulence with height and between sites along the sloping terrain.

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Wavelet methods: application to the study of the stable atmospheric boundary layer under non-stationary conditions

Cited by 60 publications

References 20 publications

Wavelet Multiscale Analysis of a Power System Load Variance

Wavelet Multiscale Analysis of a Power System Load Variance

Scale dependence of coherent structures' contribution to the daytime buoyancy heat flux over the Pantanal wetland, Brazil

Interactions among drainage flows, gravity waves and turbulence: a BLLAST case study

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