This WP will bring together global leaders in NWP models as applied to the wind industry to exchange information and recommendations regarding most promising areas to improve both the physics of these models and data assimilation methods, and the influence of various data types, such as data from drones, masts, lidars and turbines in data-sparse areas, e.g. offshore for wind energy forecasting.
The emphasis will be on improvements of the wind-related forecast performance of these models especially in typical rotor heights. There, the effects of changing stability, complex terrain, the influence of the surface and phenomena such as low-level jets still are only poorly modeled. Forecasting time horizons of 0-3 hours, 3-12 hours, day ahead, 2 weeks ahead, and seasonal are the relevant time scales for the power system, and will be the focus of separate investigations. This can include artificial intelligence techniques or Rapid Update Cycles.