Determining the spatial representativeness of air-temperature records using variogram-nugget time series

In climatology, spatial representativeness can be measured as the degree to which an instrumental temperature record resolves the climatic variability across an area. Some station records may disproportionately resolve characteristics of their immediate surroundings and, therefore, have less utility in representing climate (or weather) over larger spatial scales. To evaluate spatial representativeness of historical air-temperature records, a modified geostatistical procedure was developed. The procedure measures the spatial representativeness of a station based on variogram parameter estimates-in this case the nugget. This application is novel for two reasons: (1) variogram models are fit to station-specific or "point-centered" semivariance and (2) variogram models are fit to semivariance computed at intervals in a time series. Fitting variograms to point-centered semivariance may be used to create time series of nuggets for each station in a network. Nugget time series may show subsets of a time series that are spatially unrepresentative. These periods could be omitted from climatological analyses without excluding the entire station record. Examples from the central-U.S. subset of the Daily Historical Climatology Network illustrate how anomalous nuggets or step changes in nuggets can be identified relative to station changes.