Mean-preserving interpolation with splines for solar radiation modeling

Interpolation is a fundamental process in solar resource assessment that glues consecutive components of the modeling chain. Most interpolation techniques assume interpolating function must go through points. However, this assumption does not fit with averaged datasets or variables be conserved across interpolation. Here I present mean-preserving splines method for one-dimensional data conserves interpolated field and appropriate datasets. It uses second-order polynomial to minimize fluctuations field, restricts results user-provided limits prevent unphysical values, deals periodic boundary conditions can work non-uniform averaging grids. The validity performance are illustrated against regular second- third-order using relevant case examples realm.