Challenging problems of quality assurance and quality control (QA/QC) of meteorological time series data

Abstract Representativeness and quality of collected meteorological data impact accuracy precision climate, hydrological, biogeochemical analyses predictions. We developed a comprehensive Quality Assurance (QA) Control (QC) statistical framework, consisting three major phases: Phase I—Preliminary exploration, i.e., processing raw datasets, with the challenging problems time formatting combining datasets different lengths intervals; II—QA including detecting flagging duplicates, outliers, extreme data; III—the development series desired frequency, imputation missing values, visualization final summary. The paper includes two use cases based on at Billy Barr station (East River Watershed, Colorado), Barro Colorado Island (BCI, Panama) station. framework is suitable for both real-time post-data-collection QA/QC analysis datasets.