Utilizing wind in spatial covariance

TL;DR

This paper introduces an anisotropic covariance function that models stronger spatial correlations along wind directions and weaker correlations perpendicular to wind, by stretching the spatial domain along wind axes.

Contribution

It develops a simple, explicit covariance function that captures wind-influenced anisotropy through space stretching along wind axes.

Findings

The covariance function explicitly models wind-driven anisotropy.

The function is derived by stretching space along wind axes.

It demonstrates how to incorporate wind direction into spatial covariance modeling.

Abstract

This work develops a covariance function which allows for a stronger spatial correlation for pairs of points in the direction of a vector such as wind and weaker for pairs which are perpendicular to it. It derives a simple covariance function by stretching the space along the wind axes (upwind and across wind axes). It is shown that this covariance function is anisotropy in the original space and the functions is explicitly calculated.