A serially complete simulated observation time metadata file for U.S. daily historical climatology network stations

Abstract

A procedure to infer time of observation based on day-to-day temperature variations is refined and applied to the 1060-station daily Historical Climatology Network (HCN), creating a set of ersatz observation time metadata. Testing of the observation time inference procedure on the HCN data, as well as a set of U.S. normals stations at which no reported observation time changes occur from 1951 to 1991, indicates that, on average, the correct observation time category is identified in nearly 90% of the station years. Classification success decreases, however, at stations at which average annual interdiurnal temperature range falls below 1.9°C. At these stations, which represent only 4% of the HCN daily station years, the percentage of correctly classified years falls to 78%. Application of the observation time inference procedure yields a set of annual observation times for stations in the HCN. Primarily, this surrogate dataset provides a means of identifying observation time during years when documented observation times are absent. Such metadata are currently unavailable for approximately one-quarter of the daily HCN station years, limiting their use for analyzing time-dependent climate variations. In addition, the inferred observation times can be used to assess the veracity of the reported observation time data. Although quantifying the accuracy of the HCN observation time metadata is difficult, on average 6% of the station years are misclassified at stations having the highest potential for correct classification. Therefore, overall, these metadata seem reasonably accurate. At individual stations, however, erroneous observation time metadata are identified by the procedure and confirmed using temperature data from adjacent stations.