Time & freshness
Parse source timestamps, account for configured time zones and assess observation age against source timing.
Data quality
A source can respond successfully and still contain an old observation. A sensor can report an unusual value without it representing the weather around it. Our processing is built to distinguish those cases.
Automated checks
Parse source timestamps, account for configured time zones and assess observation age against source timing.
Check values and relationships for realistic ranges, including missing or invalid fields.
Look for unexpected changes and rain signals that need further observations before entering the public picture.
Compare eligible observations where suitable nearby information is available. Local exposure differences still matter.
Track failed polls, delayed updates and recovery independently of the browser or app’s connection.
Use eligible readings for local products; do not turn a failed sensor into a zero measurement.
“Validated” means an observation passed the automated checks applied by DLW. It is not independent instrument certification or a guarantee that every sensor is correct.
Source setup, maintenance, location and exposure affect the meaning of a reading. Nearby stations can legitimately disagree, especially during a local shower or around an exposed coastline.
Questions about the data
No. One observation can contain several sensor values. The network counter counts qualifying measurements, not independent instruments agreeing with one another.
No. A short or localised shower can miss a rain gauge. A dry reading describes the available observation, not every street or field in an area.
Published network records describe the coverage and history available to DLW. They should not be presented as official county climate records.