Data from Aims weather stations are subjected to two quality control processes.

The first quality control process involves applying automatic rules to the level0 data to flag data points that are unlikely to be correct. These rules flag:

• Values frequently associated with sensors which are faulty, in need of a service or are not working properly.
• Values outside believable ranges.
• Values that are out of range compared to other nearby stations.

The second quality control process involves manual visualisation of all data. Data from all sensors are individually graphed and compared to sensors on the same station (e.g. water temperature 1 and water temperature 2), calibrated temperature loggers, predicted values (e.g. PAR) or compared to sensors from nearby stations (incl. BOM stations, esp. barometric pressure, wind speed and direction).

After these processes have been applied the data can be categorised in the following three levels.

Level 0 Data

Raw unprocessed data as received from the AWS. These data points have had no quality control process applied to them.

Level 1 Data

Level 1 data has had all suspect data points removed but no suspect data points are corrected.

Level 2 Data

Level 2 data has had all suspect data points that were removed in Level 1 corrected where possible.