  With increasing number of crowdsourced private automatic weather stations
(called TPAWS) established to fill the gap of official network and obtain local
weather information for various purposes, the data quality is a major concern
in promoting their usage. Proper quality control and assessment are necessary
to reach mutual agreement on the TPAWS observations. To derive near real-time
assessment for operational system, we propose a simple, scalable and
interpretable framework based on AI/Stats/ML models. The framework constructs
separate models for individual data from official sources and then provides the
final assessment by fusing the individual models. The performance of our
proposed framework is evaluated by synthetic data and demonstrated by applying
it to a re-al TPAWS network.
