Quality-controlled meteorological datasets from SIGMA automatic weather stations in northwest Greenland

In situ meteorological data are essential for a better understanding of the ongoing environmental changes in the Arctic. In order to increase the scientific value of discussions on understanding the actual state of environmental change in a given area, it is necessary to appropriately remove the anomalous values recorded due to external factors resulting from low temperature and icing. Here we present methods for quality control (QC) of meteorological observation datasets from two automatic weather stations in northwest Greenland, where drastic glaciological and meteorological environmental changes have occurred. The stations were installed in the accumulation area of the Greenland Ice Sheet (SIGMA-A site, 1490 m a.s.l.) and near the equilibrium line of the Qaanaaq Ice Cap (SIGMA-B site, 944 m a.s.l.). We describe the two-step sequence of QC procedures we used to produce increasingly reliable data sets by masking erroneous records. This method was developed for the climatic conditions of Greenland, however, it is designed to be as universally applicable as possible, with a basis in meteorology and glaciology, and with the intention of removing the subjectivity of the person performing the QC. The QC is divided into two processes: Initial Control and Secondary Control. Initial Control removes values that violate physical laws and also serves as a preliminary process to improve the accuracy of Secondary Control. Secondary Control removes abnormal values using stricter statistical criteria than Initial Control. As a result of this two-step process, controlled by scientifically objective criteria, we were able to successfully remove erroneous data sets and greatly reduce the time required for QC. In addition, by using a generally applicable process, we were able to successfully establish an algorithm that could be applied to multiple sites. The data sets from both the SIGMA-A and SIGMA-B sites were classified into three levels (Level 1.1 to Level 1.3) according to the stage of data processing. Level 1.1 is the so-called raw data, in which the data for the period when the logger was stopped are masked (processed to flag them as missing or abnormal), the so-called raw data. Level 1.2 and Level 1.3 are datasets to which Initial Control and Secondary Control have been applied to the Level 1.1 and Level 1.2 datasets, respectively, and the Level 1.3 dataset is a dataset from which all abnormal values have been removed. These datasets have been archived in the Arctic Data Archive System (ADS) operated by the National Institute of Polar Research in Japan (e.g., Level 1.3 dataset: SIGMA-A - https://doi.org/10.17592/001.2022041303 and SIGMA-B - https://doi.org/10.17592/001.2022041306).