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Title: Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)

Abstract

Abstract. Wind farms affect local weather and microclimates;hence, parameterizations of their effects have been developed for numerical weather prediction models.While most wind farm parameterizations (WFPs) include drag effects of wind farms, models differ on whether or not an additionalturbulent kinetic energy (TKE) source should be included in theseparameterizations to simulate the impact of wind farms on the boundary layer.Therefore, we use aircraft measurements above large offshore wind farms in stable conditions to evaluateWFP choices. Of the three case studies we examine, we find the simulated ambient backgroundflow to agree with observations of temperature stratification and winds. This agreement allows us toexplore the sensitivity of simulated wind farm effects with respect to modeling choicessuch as whether or not to include a TKE source, horizontal resolution, vertical resolutionand advection of TKE. For a stably stratified marine atmospheric boundary layer (MABL), a TKE source and a horizontal resolutionon the order of 5 km or finer are necessary to represent the impact of offshore wind farms on the MABL.Additionally, TKE advection results in excessively reduced TKE over the wind farms, which in turn causesan underestimation of the wind speed deficit above the wind farm. Furthermore, using fine verticalresolution increases the agreement of the simulatedmore » wind speed with satellite observations of surface wind speed.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3];  [4];  [5];  [5];  [6];  [4]; ORCiD logo [2];  [6]; ORCiD logo [1]
  1. Karlsruhe Inst. of Technology (KIT) Garmisch-Partenkirchen (Germany). IMK-IFU
  2. Univ. of Tübingen (Germany)
  3. Univ. of Colorado, Boulder, CO (United States). Dept. of Atmospheric and Oceanic Sciences; National Renewable Energy Lab. (NREL), Golden, CO (United States)
  4. Inst. of Coastal Research, Geesthacht (Germany)
  5. Technische Univ. Braunschweig (Germany)
  6. UL-DEWI Gmbh, Oldenburg (Germany)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1606121
Report Number(s):
NREL-JA-5000-75874
Journal ID: ISSN 1991-9603
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Geoscientific Model Development (Online)
Additional Journal Information:
Journal Name: Geoscientific Model Development (Online); Journal Volume: 13; Journal Issue: 1; Journal ID: ISSN 1991-9603
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; offshore wind farms; wind farm parameterizations; weather predication models; turbulent kinetic energy

Citation Formats

Siedersleben, Simon K., Platis, Andreas, Lundquist, Julie K., Djath, Bughsin, Lampert, Astrid, Bärfuss, Konrad, Cañadillas, Beatriz, Schulz-Stellenfleth, Johannes, Bange, Jens, Neumann, Tom, and Emeis, Stefan. Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1). United States: N. p., 2020. Web. https://doi.org/10.5194/gmd-13-249-2020.
Siedersleben, Simon K., Platis, Andreas, Lundquist, Julie K., Djath, Bughsin, Lampert, Astrid, Bärfuss, Konrad, Cañadillas, Beatriz, Schulz-Stellenfleth, Johannes, Bange, Jens, Neumann, Tom, & Emeis, Stefan. Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1). United States. https://doi.org/10.5194/gmd-13-249-2020
Siedersleben, Simon K., Platis, Andreas, Lundquist, Julie K., Djath, Bughsin, Lampert, Astrid, Bärfuss, Konrad, Cañadillas, Beatriz, Schulz-Stellenfleth, Johannes, Bange, Jens, Neumann, Tom, and Emeis, Stefan. Wed . "Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)". United States. https://doi.org/10.5194/gmd-13-249-2020. https://www.osti.gov/servlets/purl/1606121.
@article{osti_1606121,
title = {Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)},
author = {Siedersleben, Simon K. and Platis, Andreas and Lundquist, Julie K. and Djath, Bughsin and Lampert, Astrid and Bärfuss, Konrad and Cañadillas, Beatriz and Schulz-Stellenfleth, Johannes and Bange, Jens and Neumann, Tom and Emeis, Stefan},
abstractNote = {Abstract. Wind farms affect local weather and microclimates;hence, parameterizations of their effects have been developed for numerical weather prediction models.While most wind farm parameterizations (WFPs) include drag effects of wind farms, models differ on whether or not an additionalturbulent kinetic energy (TKE) source should be included in theseparameterizations to simulate the impact of wind farms on the boundary layer.Therefore, we use aircraft measurements above large offshore wind farms in stable conditions to evaluateWFP choices. Of the three case studies we examine, we find the simulated ambient backgroundflow to agree with observations of temperature stratification and winds. This agreement allows us toexplore the sensitivity of simulated wind farm effects with respect to modeling choicessuch as whether or not to include a TKE source, horizontal resolution, vertical resolutionand advection of TKE. For a stably stratified marine atmospheric boundary layer (MABL), a TKE source and a horizontal resolutionon the order of 5 km or finer are necessary to represent the impact of offshore wind farms on the MABL.Additionally, TKE advection results in excessively reduced TKE over the wind farms, which in turn causesan underestimation of the wind speed deficit above the wind farm. Furthermore, using fine verticalresolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed.},
doi = {10.5194/gmd-13-249-2020},
journal = {Geoscientific Model Development (Online)},
number = 1,
volume = 13,
place = {United States},
year = {2020},
month = {1}
}

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