Introduction One of the major concerns with detecting global climate change is the quality of the data.
Climate data are extremely sensitive to errant values and outliers.
Prior to the analysis of these time series it is important to remove outliers in a methodical manner. At the present time very few long term climate datasets with global coverage used to detect climate change can provide reproducible results starting with originally reported values. In this paper an objective quality control analysis scheme examines global climate data for outliers temporally and spatially. Each station selected from the GHCN must have had at least 20 years of record within the 1951- 1980 period. A temporal check and a spatial check for outliers are described in the next section.