Study reveals slow wake recovery and fast turbulence decay in numerical models, indicating NWP-WFP improvements needed.
Numerical Weather Prediction (NWP) and climate models equipped with Wind Farm Parameterizations (WFPs) can simulate cluster wake effects affecting downstream wind farms in both onshore and offshore environments. This study evaluates the strengths and limitations of the NWP-WFP approach using the Weather Research and Forecasting (WRF) model with the Fitch WFP, benchmarked against large-eddy simulations (LES) of an idealized offshore wind farm under neutral atmospheric stability. Wake recovery is underestimated in NWP-WFP simulations because of two interconnected issues. First, the spatial gradients in the wind velocity field within the near-farm wake are necessarily under-resolved at mesoscale grid resolutions compared to the LES. Second, the faster decay of farm-added turbulence kinetic energy (TKE) in the mesoscale simulations is likely not due to excessive dissipation, but rather due to the underestimation of spatial gradients needed to sustain elevated TKE levels via shear production. A key insight is that the slow recovery in the near-farm wake, although confined to a short downstream distance, has lasting consequences for the far wake region. This fact underscores the need to address under-resolved spatial gradients to improve wake recovery and reduce far wake biases in NWP-WFP simulations.
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Radünz et al. (2025) studied this question.
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