Quality Assessment of Meteorological Data for the Beaufort and Chukchi Sea Coastal Region using Automated Routines

• Published in: ARCTIC
• Main Authors: Shulski, Martha D., You, Jinsheng, Krieger, Jeremy R., Baule, William, Zhang, Jing, Zhang, Xiangdong, Horowitz, Warren
• Format: Article in Journal/Newspaper
• Language: English
• Published: The Arctic Institute of North America 2014
• Subjects: western Arctic; meteorological observations; data quality; automated quality control; Beaufort Sea; Chukchi Sea; Alaska; Arctique de l’Ouest; observations météorologiques; qualité des données; contrôle de la qualité automatisé; mer de Beaufort; mer des Tchouktches; Arctic; Mer de Beaufort; Arctique*; Chukchi; Mer des Tchouktches; Tchouktche*
• Online Access: https://journalhosting.ucalgary.ca/index.php/arctic/article/view/67412

Meteorological observations from more than 250 stations in the Beaufort and Chukchi Sea coastal, interior, and offshore regions were gathered and quality-controlled for the period 1979 through 2009. These stations represent many different observing networks that operate in the region for the purposes of aviation, fire weather, coastal weather, climate, surface radiation, and hydrology and report data hourly or sub-hourly. A unified data quality control (QC) has been applied to these multi-resource data, incorporating three main QC procedures: the threshold test (identifying instances of an observation falling outside of a normal range); the step change test (identifying consecutive values that are excessively different); and the persistence test (flagging instances of excessively high or low variability in the observations). Methods previously developed for daily data QC do not work well for hourly data because they flag too many data entries. Improvements were developed to obtain the proper limits for hourly data QC. These QC procedures are able to identify the suspect data while producing far fewer Type I errors (the erroneous flagging of valid data). The fraction of flagged data for the entire database illustrates that the persistence test was failed the most often (1.34%), followed by the threshold (0.99%) and step change tests (0.02%). Comparisons based on neighboring stations were not performed for the database; however, correlations between nearby stations show promise, indicating that this type of check may be a viable option in such cases. This integrated high temporal resolution dataset will be invaluable for weather and climate analysis, as well as regional modeling applications, in an area that is undergoing significant climatic change. Des observations météorologiques provenant de plus de 250 stations des régions côtières, intérieures et extracôtières de la mer de Beaufort et de la mer des Tchouktches ont été recueillies pendant la période allant de 1979 à 2009, puis elles ont fait l’objet d’un ...