On the Algorithms Used to Compute the Standard Deviation of Wind Direction

Abstract

Abstract The standard deviation of wind direction is a very important quantity in meteorology because in addition to being used to determine the dry deposition rate and the atmospheric stability class, it is also employed in the determination of the rate of horizontal diffusion, which in turn determines transport and dispersion of air pollutants. However, the computation of this quantity is rendered difficult by the fact that the horizontal wind direction is a circular variable having a discontinuity at 2π radians, beyond which the wind direction starts again from zero, thus preventing angular subtraction from being a straightforward procedure. In view of such a limitation, this work is meant to provide new mathematical expressions that simplify both the computational and analytical work involved in handling the standard deviation of wind direction. This is achieved by deriving a number of Fourier series and Taylor expansions that can represent the minimum angular distance and its powers. Using these expressions, the relation between two algorithms commonly used to determine the standard deviation of wind direction is analyzed. Furthermore, given that these trigonometric expansions effectively reduce the mathematical complexity involved when dealing with circular statistics, their potential application to solve other problems is discussed.