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With increasing number of crowdsourced private automatic weather stations(called TPAWS) established to fill the gap of official network and obtain localweather information for various purposes, the data quality is a major concernin promoting their usage. Proper quality control and assessment are necessaryto reach mutual agreement on the TPAWS observations. To derive near real-timeassessment for operational system, we propose a simple, scalable andinterpretable framework based on AI/Stats/ML models. The framework constructsseparate models for individual data from official sources and then provides thefinal assessment by fusing the individual models. The performance of ourproposed framework is evaluated by synthetic data and demonstrated by applyingit to a re-al TPAWS network.

An operational framework to automatically evaluate the quality of weather observations from third-party stations