In the increasing global transition towards renewable and carbon-neutral energy, understanding the uncertainties associated with wind power production is extremely important. In addition to the widely acknowledged uncertainties from turbulence and wind intermittency, further complexity arises from the influence of rainfall, which only a limited number of studies have addressed so far. To understand this, multiple 3D sonic anemometers, mini meteorological stations, and optical disdrometers were employed on a meteorological mast on the Pays d'Othe wind farm (110 km south-east of Paris, France) in the framework of the Rainfall Wind Turbine or Turbulence (RW-Turb) project (https://hmco.enpc.fr/portfolio-archive/rw-turb/, last access: 26 November 2024). With these simultaneously measured data, wind power and its associated atmospheric fields were studied under various rainy conditions.

Variations of the wind velocity, power available on the wind farm, power produced by wind turbines, and air density are examined here, under rainy and dry conditions, using the scale-invariant framework of universal multifractals (UM). Since rated power acts like an upper threshold in statistical analysis of turbine power (discussed in Part 1), theoretically available power was used as a proxy. From an event-based analysis, differences in UM parameters were observed between rainy and dry conditions for the fields. This is explored further using joint multifractal analysis, which revealed an increase in the correlation exponent between various fields with the rain rate. Here we also examine the possibility of variation in power production by rainy conditions (convective or stratiform) as well as by regimes of wind velocity. While examining time steps according to wind velocity, turbine power curves showed different regions of departure from the state curve according to the rain rate.