Smart interpolation of annually averaged air temperature in the United States

Abstract

Two "smart' interpolation procedures are presented and assessed with respect to their ability to estimate annual-average air temperatures at unsampled points in space from available station averages. Smart approaches exmained here improve upon commonly used procedures in that they incorporate spatially high-resolution digital elevation information, an average environmental lapse rate, and/or another higher-resolution longer-term average temperature field. Two other straightforward or commonly used interpolation methods also are presented and evaluated as benchmarks to which the smart interpolators can be compared. Smart approaches are significantly more accurate than either traditional methods or estimates spatially interpolated from a high-resolution climatology alone. A smart interpolation method that makes combined use of a digital elevation model (DEM) and traditional interpolation was nearly 24% more accurate than traditional interpolation by itself. -from Authors