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It is widely known that the TD3200 (Summary of the Day Cooperative Network) database held by the National Climatic Data Center contains tens of thousands of erroneous daily values resulting from data-entry, data-recording, and data-reformatting errors. TD3200 serves as a major baseline dataset for detecting global climate change. It is of paramount importance to the climate community that these data be as error-free as possible. Many of these errors are systematic in nature. If a deterministic approach is taken, using empirically developed criteria, many if not most of these errors can be corrected or removed. A computer program utilizing Backus Normal Form structure design and a series of chain-linked tests in the form of encoded rules has been developed as a means of modeling the human subjective process of inductive data review. This objective automated correction process has proven extremely effective. A manual review and validation of 138 stations of a 1300-station subset of TD3200 data closely matched the automated correction process. Applications of this technique are expected to be utilized in the production of a nearly error-free TD3200 dataset.
Reek et al. (Mon,) studied this question.