Wind validation is a python package that makes it easy to validate wind measurements for wind resource applications. The data structures are time series, histograms and Weibull distributions and adopted from and defined in windkit,
The available validation options are shown in the figure above. There is an information reduction by going through the diagram from left to right. A time series is the most complete data structure to represent a wind climate and contains data series of wind speed and wind direction at one or many points. A histogram does not have a time dimension but instead represent the wind climate by describing frequency distributions for bins along the dimensions wind speed (wsbin) and wind direction (sector).
When measuring over a long period the frequency of occurence usually follows a Weibull distribution, particularly when looking at a single sector. It is therefore common practice in the wind energy industry to use the Weibull A and k parameters to denote the wind resource at a certain location. For computational efficiency wind resource assessment often operate on histograms or Weibull distributions. There is a filtering step, which is generally needed to make the two time series similar in space and time. Some examples of spatially aligning data are given in Examples.