Calculation of wind speed in the 300-meter lower layer of the atmosphere based on the meteorological observations taking account of temperature stratification and surface roughness

S.N. Stepanenko; V.G. Voloshin; V. Yu. Kuryshina

doi:10.31481/uhmj.17.2016.03

S.N. Stepanenko
V.G. Voloshin
V. Yu. Kuryshina

DOI: https://doi.org/10.31481/uhmj.17.2016.03

Keywords: wind profile power law, wind energy, stability criteria for surface layer, turbulent flows

Abstract

Introduction. Taking into account relationship of wind profile power-law exponent (m) from hydrostatic stability of the layer and surface roughness the calculation method of wind speed and direction in the lower 300-meter layer of the atmosphere based on the meteorological observations is proposed.

Problem. For many applied engineering problems, for example, for the design of high-rise construction and operation of wind power plants the wind and temperature profile data in the lower 300-meter layer are required. In the design, the main objective is to determine the peak wind loads and influences on objects.

Research methods. The calculations were carried out using the energy-balance model of the atmospheric surface layer, SLEB, based on standard meteorological information. The model is built on the basis of Monin-Obukhov similarity. To determine spatial variability of wind and temperature hydrostatic stability of the atmosphere and the dynamic properties of the underlying surface are taken into account.

Purpose. The aim of the study is to develop a method of calculation of changes in wind speed and direction in the lower 300-m layer of the atmosphere using the wind profile power law based on the standard surface meteorological information.

Results of the study. Relationships of non-dimensional wind profile power-law exponent from hydrostatic stability of the layer and surface roughness, obtained with the SLEB model, allowed building function graphics for different observation times and months. All calculated values agree with the known experimental and theoretical data very well.

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