In order to achieve UN’s (United Nations) Sustainable Development Goal 7 (affordable and clean energy for all); and in the increasing global transition towards renewable and carbon neutral energy; improving our understanding of wind power production is needed. Yet, it is not straightforward because of the underlying features of the involved geophysical fields, i.e. wind and rainfall. Indeed both are known to exhibit extreme variability over wide ranges of space-time scales. This extreme variability is then transferred to the wind turbine torque and ultimately to wind energy production. To understand better the correlation across scales between rainfall and wind fields and its impact on wind power production, the project RW-Turb (https://hmco.enpc.fr/portfolio-archive/rw-turb/; supported by the French National Research Agency, ANR-19-CE05-0022) was developed. A high resolution measurement campaign was set up between 12/2020 and 07/2023 with multiple 3D sonic anemometers (manufactured by Thies), mini meteorological stations (manufactured by Thies), and disdrometers (Parsivel2, manufactured by OTT) installed on a meteorological mast in the wind farm of Pays d’Othe (110 km south-east of Paris, France; operated by Boralex). First, fluctuations across scales of various fields (wind velocity, power available at the wind farm, power produced by wind turbines, air density, and rainfall) were studied using the framework of Universal Multifractals (UM). It is a powerful tool that allows to characterize and simulate the extreme variability of geophysical fields across scales with the help of only three parameters with physical interpretation. Event based analysis enabled to observe differences in UM parameters depending on whether it is raining or not. Joint multifractal analysis enabled to find an increase in correlation exponent of the various fields with increase in rain rate. Second, 3D space plus time vector fields which realistically reproduce observed spatial and temporal variability of wind fields are generated with multifractal tools, and used as input into three modeling chains of increasing complexity to simulate wind turbine torque. UM analysis on the simulated torque time series were performed to quantify the impact of small scale fluctuations on wind power production.