Towards an automated method for near-real-time exposure correction of wind measurements

The potential wind^[1] is the wind speed one would measure under ideal WMO conditions, i.e. on a 10-metre mast with only short grass and no hills or obstacles in the surroundings. The potential wind is computed using exposure correction factors (ECFs), which are determined from the wind-speed measurements themselves and depend on the wind direction. Climatology studies should be based on data that are representative of an area wider than the vicinity of the wind mast, so the data should exclude local effects (e.g. from trees or buildings) and sensor changesor measurement site re-locations. If the "disturbance" of the measurement is not extreme, ECFs can be used to correct the measurements (homogenisation). ECFs and potential wind are therefore used for meteorological measurement site inspection, atmospheric model validation, aviation applications and construction regulations for buildings and water works.

Essentially, there are two methods to compute ECFs: (1) the Gustiness method, based on the hourly maximum 3-second mean speed (gust) divided by the hourly mean speed and (2) the Sigma method based on 10-minute standard deviation divided by 10-minute mean wind speed. The latter method was proved to be superior in 2009, but because 10-minute wind measurements were not stored before 2003, KNMI kept using the Gustiness method. Now that KNMI has a substantial (and still growing) dataset, the Sigma method can be applied.  

We developed, fine-tuned, tested and verified an algorithm that can automatically provide 10-minute ECF and potential wind speed updates based on the Sigma method. These near-real time updates are of interest to a broader range of users, including forecasters.

[1] See also: https://www.knmi.nl/kennis-en-datacentrum/project/potential-wind