Multifractal analysis of the time series of daily means of wind speed in complex regions

@article{Laib2017MultifractalAO,
  title={Multifractal analysis of the time series of daily means of wind speed in complex regions},
  author={Mohamed Laib and Jean Golay and Luciano Telesca and Mikhail F. Kanevski},
  journal={Chaos Solitons \& Fractals},
  year={2017},
  volume={109},
  pages={118-127}
}
View PDF on arXiv
43 Citations
Highly Influential Citations
2
Background Citations
11
Methods Citations
8

Figures and Tables from this paper

43 Citations

Multifractal detrended cross-correlation analysis of wind speed and solar radiation.

In this work, the multifractal properties of wind speed and solar radiation are studied in a small region in which a wide variety of micro-climates are concentrated. To achieve this, two years of…

Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method

Multiparametric statistical and dynamical analysis of angular high-frequency wind speed time series

Multifractality of meteorological time series for Poland on the base of MERRA-2 data

Multiscale entropy analysis of wind speed dynamics in Petrolina, Northeast Brazil

Purpose: In this paper, we analyzed the intra-annual variability of complexity of wind dynamics in Petrolina, Brazil and its relation with the wind potential. Methodology: We applied the Multiscale…

Wind speed persistence at the Fernando de Noronha archipelago, Brazil

The use of wind energy has been growing worldwide continuously over the last years due to global efforts to combat climate change. The modern turbines are becoming ever more cost effective and are…

Characterization of vertical wind velocity variability based on fractal dimension analysis

Fractal characteristics of tall tower wind speeds in Missouri

Mixture distribution and multifractal analysis applied to wind speed in the Brazilian Northeast region

Wind speed forecasting by the extraction of the multifractal patterns of time series through the multiplicative cascade technique

References

SHOWING 1-10 OF 51 REFERENCES

Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions

Analysis of the time dynamics in wind records by means of multifractal detrended fluctuation analysis and the Fisher–Shannon information plane

The time structure of more than 10 years of hourly wind data measured at one site in northern Italy from April 1996 to December 2007 is analysed. The data were recorded by the Sodar Rass system,…

Multifractal analysis of validated wind speed time series.

TLDR
Wind speed records have been validated, applying various quality control tests as a pre-requisite before their use, improving the reliability of the results due to the identification of incorrect values which have been discarded in the analysis.

A multifractal description of wind speed records

Daily wind gust speed probabilities over Switzerland according to three types of synoptic circulation

The nowcasting and prediction of strong winds are still far from adequate, using either statistical or numerical modelling approaches. During the last decade, Switzerland has been struck by two…

Spatial Predictions of Extreme Wind Speeds over Switzerland Using Generalized Additive Models

The purpose of this work is to present a methodology aimed at predicting extreme wind speeds over Switzerland. Generalized additive models are used to regionalize wind statistics for Swiss weather…

Fractal order evidences in wind speed time series

This paper describes some evidence of fractal order features in wind speed time series recorded at different observation stations both in USA and in Italy. Analysis were performed by using…

Climatology of near‐surface wind patterns over Switzerland

Over complex, mountainous terrain the near‐surface winds can form intricate patterns as large‐scale winds and locally forced wind systems interplay. Switzerland, with its mountainous topography and…

Multifractal analysis of wind velocity data

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

TLDR
This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed.
...