Quality control of time-series seawater temperature and wave data adapted to the regional conditions of the Baltic Sea

Abstract

Marking outliers using available methods for identifying such observations should be a standard practice in the database management process. The research aimed to adapt universal data quality control tools and tests to their applicability in the southern Baltic Sea by setting new limit values, enabling the detection of erroneous or suspicious data, which can be subjected to expert verification at a later stage. This verification stage may include analysing current conditions and processes and determining the values measured at a given time and space. Our research has proven that using global algorithms requires adapting the limit values based on regional conditions. The global quality control tests, such as the spike test, Dixon’s 4(σ), Q-Dixon, Hampel, quartile, and gradient tests for oceanographic data, were examined, and their application in the research area was verified. As part of the task, a few tests were conducted in various areas of the Baltic Sea, and they were modified to adapt them to the research results of the southern Baltic Sea. Depending on the methodology adopted, verification tests result in the selection of suspicious observations, enabling their expert assessment and the final qualification of measurements that may be considered outliers.