Development of Spatial Quality Control Method for Temperature Observation Data using Cluster Analysis

In the National Climate Data Center of Korea Meteorological Administration, quality control methods of meteorological observations are applied to identify erroneous observation values. The type of quality control methods we have been using is to check the value from one station, either instantly or temporally. The spatial checking methods that find errors by comparing values of several stations at a time are difficult to apply because calculating the threshold using a large amount of observations is time consuming and various conditions for applying are required. In this study, we develop a new spatial checking method for temperature observation data using cluster analysis for meteorological observations that can be performed fast and effective in clarifying errors that have not been discovered.