Integrating and validating crowdsourced data for improved weather predictions in MET Nordic

This is the authors' abstract. We don't add key points for this paper.

The MET Nordic dataset, developed by the Norwegian Meteorological Institute (MET Norway), offers high-resolution (1 km) near-surface meteorological variables for Scandinavia, Finland, and the Baltic countries. Derived through statistical post-processing of numerical model outputs, MET Nordic serves two main purposes: historical weather reconstruction and real-time weather monitoring with short-term forecasts. This presentation focuses on the real-time stream (MET Nordic RT), which updates hourly with a 20-minute latency and maintains an operational archive dating back to 2012.The near-surface variables included in MET Nordic RT are: two-metre temperature, precipitation, air pressure at sea level, relative humidity, wind speed and direction, solar global radiation, long-wave downwelling radiation, cloud area fraction. The dataset combines data from the MetCoOp Ensemble Prediction System (MEPS) and diverse observational inputs, including -for temperature and precipitation- crowdsourced data from consumer-grade weather stations managed by citizens. The integration of such opportunistic data sources has enhanced the precision of reconstruction analysis and short-term forecasts, particularly temperature predictions in regions with sparse professional meteorological stations.This study describes the automatic quality control system employed to vet incoming data, ensuring reliability in statistical processing. The system uses a range of validation techniques—ranging from basic range checks to sophisticated spatial consistency tests via Bayesian inference—to mitigate the risks posed by the inherently variable quality of crowdsourced data. Our findings underscore the importance of treating such data as a network to capitalize on its dense, high-resolution coverage. The quality control software, Titanlib, is important to this process and it is freely available for use at https://github.com/metno/titanlib.The integration of data from Netatmo’s crowdsourced network into MET Nordic can be regarded as a success story. This now heavily influences MET Norway's work on upgrading our main quality control system through the internal project CONFIDENT.