Preprints
https://doi.org/10.5194/egusphere-2026-2144
https://doi.org/10.5194/egusphere-2026-2144
22 Apr 2026
 | 22 Apr 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

A wind-farm wake-turbulence parameterization for the WRF model (EWP v2.0)

Oscar García-Santiago, Jake Badger, Andrea N. Hahmann, Patrick J. H. Volker, Søren Ott, M. Paul van der Laan, and Mark Kelly

Abstract. Wind farm parameterizations are essential components of mesoscale models used to assess the impact of wind farm operation on the atmospheric flow and surface climate. These models represent wind turbines as momentum sinks and sources of turbulence. We describe the theoretical basis and implementation of an improved model to enhance the Turbulent Kinetic Energy (TKE) treatment in wind farm parameterizations. The novel Latent Kinetic Energy (LKE) model integrates the tracer capabilities of the Weather Research and Forecasting (WRF) model to accurately account for wind turbine-generated TKE throughout the wakes in and downwind of wind farms. The formulation is compatible with multiple 1.5-order planetary boundary layer (PBL) schemes in the WRF model and is implemented within the explicit wake parameterization. We evaluate the LKE model against WRF large-eddy simulations with actuator-disc representations of wind turbines for an idealized 6×6 wind farm and for three 1.5-order PBL schemes. The LKE formulation improves the representation of wake turbulence, reducing normalized TKE differences relative to the large-eddy simulations to within 15 % over the wind farm region. In contrast, the Fitch wind farm parameterization with default parameter values shows 40 %. The results further show that PBL-specific calibration is required; with appropriate calibration, the LKE approach maintains normalized TKE differences within 15 % and reproduces the hub-height wind-speed deficit within 1 % of the reference.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Share
Oscar García-Santiago, Jake Badger, Andrea N. Hahmann, Patrick J. H. Volker, Søren Ott, M. Paul van der Laan, and Mark Kelly

Status: open (until 17 Jun 2026)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Oscar García-Santiago, Jake Badger, Andrea N. Hahmann, Patrick J. H. Volker, Søren Ott, M. Paul van der Laan, and Mark Kelly

Model code and software

Code and configuration files for: “The Explicit Wake Parameterization v2.0: an improved wind-farm wake-turbulence representation in the WRF Oscar Garcia-Santiago https://doi.org/10.11583/DTU.32015934

Oscar García-Santiago, Jake Badger, Andrea N. Hahmann, Patrick J. H. Volker, Søren Ott, M. Paul van der Laan, and Mark Kelly
Metrics will be available soon.
Latest update: 22 Apr 2026
Download
Short summary
We improve how weather models represent the turbulence generated by wind turbines within and behind wind farms. Rather than adding this turbulence only at grid squares with turbine locations, the new method transports it through the wake as it moves downwind. Tests against high-resolution simulations of an idealised wind farm showed better agreement in wake turbulence and more accurate reductions in wind speed, providing a more realistic picture of wake effects across the wind farm.
Share