Wavelet methods in interpolation of high-frequency spatial-temporal pressure

The location-scale and whitening properties of wavelets make them more favorable for interpolating high-frequency monitoring data than Fourier-based methods. In the past, wavelets have been used to simplify the dependence structure in multiple time or spatial series, but little has been done to apply wavelets as a modeling tool in a space-time setting, or, in particular, to take advantage of the localization of wavelets to capture the local dynamic characteristics of high-frequency meteorological data. This paper analyzes minute-by-minute atmospheric pressure data from the Atmospheric Radiation Measurement program using different wavelet coefficient structures at different scales and incorporating spatial structure into the model. This approach of modeling space-time processes using wavelets produces accurate point predictions with low uncertainty estimates, and also enables interpolation of available data from sparse monitoring stations to a high density grid and production of meteorological maps on large spatial and temporal scales. Published by Elsevier B.V.