Journal
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
Volume 61, Issue 9, Pages 1623-1640Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2015.1085988
Keywords
isotropic-stationary turbulence; hydro-meteorological processes; stochastic modelling; climacogram; power spectrum; uncertainty bias
Categories
Funding
- Greek General Secretariat for Research and Technology through research project Combined REnewable Systems for Sustainable Energy DevelOpment (CRESSENDO) [5145]
Ask authors/readers for more resources
Turbulence is considered to generate and drive most geophysical processes. The simplest case is isotropic turbulence. In this paper, the most common three-dimensional power-spectrum-based models of isotropic turbulence are studied in terms of their stochastic properties. Such models often have a high order of complexity, lack stochastic interpretation and violate basic stochastic asymptotic properties, such as the theoretical limits of the Hurst coefficient, when Hurst-Kolmogorov behaviour is observed. A simpler and robust model (which incorporates self-similarity structures, e.g. fractal dimension and Hurst coefficient) is proposed using a climacogram-based stochastic framework and tested over high-resolution observational data of laboratory scale as well as hydro-meteorological observations of wind speed and precipitation intensities. Expressions of other stochastic tools such as the autocovariance and power spectrum are also produced from the model and show agreement with data. Finally, uncertainty, discretization and bias related errors are estimated for each stochastic tool, showing lower errors for the climacogram-based ones and larger for power spectrum ones.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available