Few studies showed that the effects of rainfall (rain rate and drop size distribution –DSD-) on wind turbine efficiency are significant, but have surprisingly received little attention. The main goal of WR-Turb is to overcome the current lack of knowledge on this topic through a genuine collaboration between an academic institution (the Hydrology, Meteorology and Complexity laboratory of Ecole des Ponts ParisTech) and a wind power production firm (Boralex). Literature review shows that: (i) wind turbulence is a complex feature requiring appropriate framework such as Universal Multifractals (UM, a parsimonious framework that enables to quantify the variability across scales of fields extremely variable across wide range of scales) for analysis and simulations; and intermittency of the input power is further propagating to the wind turbine and power output; (ii) Rainfall also exhibits scale invariant multifractal features. WR-Turb will combine the existing knowledge on wind turbulence and rainfall fields to create a coupled framework enabling to tackle its objectives. Two distinct aspects will be studied: first the rainfall effect on the wind energy resources notably taking into account its non Gaussian extreme small spatio-temporal scale fluctuations and second the rainfall effect on the conversion process of wind power to electric power by the wind turbine. A scientific programme to be primarily implemented through two PhD projects was designed: - WP 1: Experimental set-up and data collection. An observatory for combined high resolution measurements of wind (speed, direction, shear and turbulence), rainfall (DSD, and fall velocities) and power production will be installed for 2 years on a wind farm operated by Boralex and having a 86 m meteo mast. A user friendly data base will be created and data carefully validated. - WP 2: Analysis and simulation of rainfall effects on the wind power available. It aims at analysing mainly with UM tools the collected data to quantify the influence of rainfall conditions on wind turbulence and air density. A classification of rainfall events will be designed for this purpose. Interpretation will require the development of innovative models. A new 3+1D model of drop fields in a 3D turbulent wind at wind turbine scale will be also developed. Scalar and vector spatio-temporal wind fields for scales ranging from few cm and to wind turbine size over few tens of seconds will be simulated by improving existing tools based on continuous UM cascades - WP 3: Analysis and simulation of rainfall effects on energy conversion by wind turbine. The transfer of wind intermittency to power production will be analysed from the collected data (WP1). Then, two numerical modelling chains with increasing complexity will be developed to simulate and quantify the effect of wind turbulence on power production. The wind fields simulated in WP2 will be used (i) to compute available torque fluctuations, and (2) as input in a multi-disciplinary model for numerical simulation of wind turbine behaviour (existing to be customized). Ensembles of possible inputs will be used to quantify the sensitivity of the modelling chains to various input parameters corresponding to the different rainfall conditions. The share of renewable energy is rapidly growing in France and Europe. Hence it is highly relevant to understand the uncertainty affecting the electricity production by such resources, notably because its intermittent nature raises complex challenges in terms of grid management. WR-Turb will have a strong impact on this field by providing a quantification of rainfall effects of wind power production and opening perspectives for improving nowcasts. Results will be up-scalable to other site because they will mainly be event-based. The novel findings of WR-Turb, which will be disseminated to both the scientific and professional community, will also open the path for future investigations.

High resolution space-time rainfall estimation remains an open challenge for hydro-meteorologists. The overall purpose of this project is to improve the quality of radar rainfall estimation at high spatial and temporal resolutions and their applicability to urban storm water management. More specifically, the project will take advantage of two unique and innovative ground rainfall monitoring networks from two teams in France and Taiwan, respectively, to envisage the impacts of the following issues, which are seldom addressed in their whole complexity, in radar rainfall estimation: 1. The variability of rainfall drop size distributions (DSDs): the variability of DSDs will be characterised in both space and time at fine scales, and its impact on radar measurements will be quantified. 2. Wind drift effect: the advection of rain drops throughout their fall from radar observation elevations to the ground will be investigated, and its impact on radar rainfall estimation will be quantified. The investigation of the above two aspects will eventually contribute to the improvement of a 3D+1 (3D in space + 1D in time) model for rain drops fields. The subsequent impact of both aspects on storm water management will be quantified through urban hydro-dynamic modelling. Existing case studies with already calibrated models will be used with a focus on rainfall modelling. In addition to the ground rainfall networks, this project will utilise the complementary research strengths from each team. That is, the spatial and temporal rainfall modelling within a universal multifractal framework from the French team, and the rainfall object tracking using 3D+1 radar data from the Taiwan team. This cooperation will enable an in-depth research on the proposed work, and the diverse weather conditions from the two countries will enable development of a 'scale-able' tools that can provide robust solution to radar rainfall estimation.