Hi @peter The Continuous Learning system will evaluate known good data sources in your immediate area and automatically tune the raw sensor data on your Smart Weather Station to ensure all data from the network is sound. Status as of 29 November 2018:
UV: in production for all stations. Explained here.
Humidity: in production for all stations
Temp: in production for all stations, values out of QC range are flagged but no dynamic tuning is currently applied, variability depends on micro-siting.
Pressure: in production for all. Explained here.
Rain: currently in development, not yet deployed.
Wind: this is a different beast as wind fields vary massively and it is quite impossible to benchmark trusted known good data sources for comparison unless co-located within a couple feet. Instead of using a CL process as noted above, WF has deployed a sophisticated algorithm that dynamically inspects and governs the wind data coming off your SKY. The algorithm looks for anomalies in the raw data and rejects suspect data points. Development of this algorithm is ongoing…making it better and better with more data collected from the field. The tuning of the sonic anemometer is actually accomplished during setup whereas your SKY will automatically time the interval of sonic signals between the 4 transducers and balance the signal setup. Once set, the sonic has proven to be highly accurate at measuring instantaneous wind.