Wind velocity data interpolation using a weighted cubic spline

Abstract

To predict meteorological conditions, it is essential to construct interpolating functions considering the nature of the data. The paper addresses an algorithm for constructing a weighted cubic spline that preserves the monotonicity of the data. The implementation of this algorithm is shown through the example of wind velocity data interpolation when it is required to maintain the positivity of the values. Wind velocity always takes positive values, and its minimum value can be very close to zero. The paper shows that in such a case the construction of an ordinary cubic spline can result in negative values. It presents several numerical examples for the implementation of the proposed algorithm at different sets of initial parameters and makes it possible to draw comparison with the construction of a simple cubic spline and the construction of a spline in MATLAB.