Wind fields are extremely variable in space and time over a wide range of scales. These properties are transferred to the wind turbine torque and ultimately to wind energy production. The Universal Multifractal (UM) is a common framework that allows characterising and simulating the extreme variability of geophysical fields across scales with the help of 3 parameters (α , C1 and H) with physical interpretation; while the 4th, the power a of a conservative flux, is absorbed by the empirical estimation of the mean singularity over a non-conservative field. In this work we investigate the effect of small-scale wind variability on wind turbine torque using three different modelling chains with increasing complexity. The first one computes the torque averaging the wind field and considering it at hub height. The second one uses the definition of the angular moment as the product of the aerodynamic forces at each blade point and the distance to the hub integrating it along the blades. The third one is based on the realistic OpenFAST software developed by the US National Renewable Energy Laboratory (NREL). In order to be able to account for small scale wind extreme variability, 3D vector wind fields are simulated. Retrieving expected multifractal properties, which is the main challenge, is achieved by combining two broad classes of stochastic processes such as stable Levy processes and Clifford algebra. Multifractal analysis of the data collected by two high resolution 3D sonic anemometers, located on a meteorological mast in a wind farm situated approximately 110 km south-east of Paris, with approx. 33 m vertical distance, is used to tune the characteristic parameters. The data is gathered in the framework of the RW-Turb measurement campaign (https://hmco.enpc.fr/portfolio-archive/rw- turb/); supported by the French National Research Agency (ANR-19-CE05-0022). A comparison between torque obtained with the help of the three modelling chains using simulated 3D vector fields and UM analysis of the outputs was performed to analyse and physically interpret the differences focusing on the small scales.