What method can be used to ensure sensor accuracy in RAWS?

Ensuring sensor accuracy in Remote Automated Weather Stations (RAWS) is crucial for the reliable collection of meteorological data. The method of comparative testing against known standards is the most effective approach because it involves taking the output from the sensor being tested and comparing it to outputs from calibrated, reliable reference instruments. This process can identify any discrepancies that may exist due to sensor drift or malfunction, essentially validating the data being collected.

By utilizing known standards, you can determine if the sensor is providing accurate readings or if calibration is necessary. This approach allows for quantitative assessments, which is essential for maintaining the integrity of weather data used for various applications, including environmental monitoring and research. Regular comparative testing contributes to long-term reliability, helps in maintaining compliance with industry standards, and fosters confidence in the data provided by the sensors.

While options like physical cleaning of sensors, periodic visual inspections, and sensor report reviews are important for maintenance and operational checks, they do not directly address the accuracy of the readings provided by the sensors. Cleaning may help remove dirt that can affect performance, and inspections can identify visible issues, but neither offers the rigorous assessment offered by comparative testing against established standards. Reports can help monitor trends over time, but they do not provide the immediate accuracy validation that comparative testing