Spatial variability in correlation decay distance and influence on angular-distance weighting interpolation of daily precipitation over Europe

Angular-distance weighting (ADW) is a common approach for interpolation of an irregular network of meteorological observations to a regular grid. A widely used version of ADW employs the correlation decay distance (CDD) to (1) select stations that should contribute to each grid-point estimate and (2) define the distance component of the station weights. We show, for Europe, that the CDD of daily precipitation varies spatially, as well as by season and synoptic state, and is also anisotropic. However, ADW interpolation using CDDs that varies spatially by season or synoptic state yield only small improvements in interpolation skill, relative to the use of a fixed CDD across the entire domain. If CDDs are optimized through cross validation, a larger improvement in interpolation skill is achieved. Improvements are larger for the determination of the state of precipitation (wet/dry) than for the magnitude. These or other attempts to improve interpolation skill appear to be fundamentally limited by the available station network