Comparison of Deterministic and Stochastic Spatiotemporal Interpolation Methods for Ozone in the Conterminous U.S.

This paper discusses and compares two spatiotemporal interpolation methods for a set of data with annual ozone concentration measurements in the conterminous United States: i) 3D shape function-based spatiotemporal interpolation method - a deterministic method, and ii) 3D kriging-based spatiotemporal interpolation method - a stochastic method. The comparison results show that the kriging-based method yields a better MAPE (Mean Absolute Percentage Error) value than the shape function-based method based on the leave-one-out cross-validation, especially in the beginning and ending years. However, the 3D shape function-based method has other advantages over the kriging-based method such as its invariance to coordinate scales and efficiency.