The GAW-QC App: Improving Quality Control through Data Science and Numerical Forecasts

The Global Atmosphere Watch (GAW) Programme of the World Meteorological Organization coordinates a worldwide network of hundreds of ground-based in-situ monitoring stations that provide reliable scientific data on the chemical composition of the atmosphere. Within the framework of the GAW Programme, the Quality Assurance/Scientific Activity Centre Switzerland has developed a web app (GAW-QC, available at www.empa.ch/gaw, see also Brugnara et al., 2024) to support station operators in timely detecting issues in their in-situ measurements of various trace gases.

GAW-QC consists of a dashboard that highlights anomalous values using a mixture of purely data-driven and hybrid anomaly detection techniques. It exploits historical measurements made at the target station as well as the archive of gridded numerical forecasts by the Copernicus Atmosphere Monitoring Service (CAMS). The accuracy of the latter for the specific site is improved through machine learning using multiple predictors, including meteorological parameters and aerosol concentrations.

The app allows station operators to upload their latest measurements, visualize the data with different temporal aggregations, and detect anomalous values using just their internet browser. By combining the information gathered from the dashboard with logbook entries and local expertise, they can effectively flag problematic measurements and even detect instrumental issues that would remain unnoticed otherwise. First case studies indicate that this process can indeed facilitate the detection of malfunctions in the analytical setup and reduce the ingestion of erroneous data into international data repositories. Moreover, it has the potential to shorten data gaps if applied timely.

GAW-QC is publicly available and can be used to analyze historical time series of carbon dioxide, carbon monoxide, methane, and ozone made at 98 GAW stations worldwide. The applicability to a given station depends on whether historical data have been submitted to the GAW world data centers by the station operator. Additional gas species may be added in the future depending on user feedback.

 

Brugnara, Y., Steinbacher, M., Baffelli, S., and Emmenegger, L.: Technical note: An interactive dashboard to facilitate quality control of in-situ atmospheric composition measurements, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-3556, 2024.