Comparison of Approaches for Estimating Time-Averaged Precipitation Using Data From the Usa

Spatial and temporal sampling errors inherent in large- scale, weather-station (raingauge) climatologies of precipitation are evaluated. A primary goal is to assess whether more representative large-scale precipi- tation climatologies emerge when (i) more station means are included, even when they are based on unequal periods of record, or (ii) fewer station means are included but all are derived from the same period of record. Observations drawn from the Historical Climatology Network (HCN) are used to estimate temporally averaged precipitation over 10-, 20-, and 30-year intervals at 457 stations within the USA. Two strategies for estimating these ‘observed’ means are examined, one based on temporal ‘substitution’ within each station record, and the other based on spatial interpolation from surrounding stations. Temporally estimated m-year means were obtained by substituting other m-year means, from within the same station record, for each ‘observed’ m-year mean, where m is the length of the averaging period of interest. Spatially interpolated m-year means were estimated from m-year means associated with nearby stations. Climatologies containing a greater number of station averages, even if they are computed over unequal averaging periods, appear to better represent the space–time variability in mean precipitation than climatologies containing fewer, but temporally commensurate, station means. Our results (for precipitation-station networks on the order of 50–60 stations per 106 km2) indicate that the within-station- record substitution of means is about 1ċ3 to 2ċ5 times more accurate than is interpolation from surrounding station means. Within-station substitu tion errors—associated with estimating any 10-year mean precipitation from any other 10-year mean—for example, were about 8 per cent of the long-term spatial precipitation mean for the USA, or 67ċ6 mm. Spatially interpolated 10-year means, from nearby stations, were in error by more than 10 per cent, or 88ċ8 mm on average. Much of the space–time variability in mean precipitation was not resolved adequately by the 457 HCN stations, especially high-frequency spatial variability caused by orographic and convective mechanisms. For many regions of the world, temporally homogeneous precipitation station networks are considerably more sparse than in the USA, further degrading the reliability of interpolated and spatially integrated mean precipitation fields derived solely from those networks.