Assessment of Land Surface Model Performance in WRF for Simulating Wind at Heights Relevant to the Wind Energy Community

Technical Report · Tue Sep 17 04:00:00 EDT 2013

DOI:https://doi.org/10.2172/1097768· OSTI ID:1097768

Wharton, Sonia ^[1]; Simpson, Matthew ^[1]; Osuna, Jessica ^[1]; Newman, Jennifer ^[2]; Biraud, Sebastian ^[3]

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1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
2. Univ. of Oklahoma, Norman, OK (United States)
3. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

The Weather Research and Forecasting (WRF) model was used to investigate the impact of land surface model (LSM) physics on the simulated surface energy balance and the near surface wind profile, including heights reached by a modern wind turbine. Simulations were made for a domain centered over the Department of Energy (DOE) Southern Great Plains (SGP) Atmospheric Radiation Measurement Program (ARM) Central Facility in northern Oklahoma. High-resolution measurements of surface fluxes and profiles of wind speed, direction and turbulence were available for model validation. We tested 10 common LSM configurations in WRF including Noah, Noah-MP, SSiB, Pleim-Xiu, RUC, and others to evaluate (1) the accuracy of simulated surface energy fluxes, (2) the accuracy of forecasted rotor-disk height wind speeds, and (3) the sensitivity of rotor disk wind speed to the choice of LSM. WRF was run for four, two-week periods covering different canopy, surface meteorology and soil moisture conditions. LSM performances varied by simulation period and errors were greatest during periods with high soil moisture and live crop cover, indicating highest LSM sensitivity when PBL behavior is most coupled to land-atmosphere exchange. Higher wind speed errors also occurred at night during the spring, possibly from the difficulty with simulating nocturnal low-level jets. We found that choice of land surface model led to a ~10% improvement in simulating hub-height wind speed. Errors in wind shear were also sensitive to the choice of LSM. Overall the best performing models were Noah and Noah-MP. The variability of LSM performance across different soil moisture and vegetation canopy conditions suggests LSM representation of surface energy exchange processes in WRF remains a large source of model uncertainty. Furthermore, our results indicate the choice of LSM impacts simulated wind fields in WRF at heights relevant to the wind industry, at least for the Southern Great Plains region.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Water Power Technologies Office; USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: W-7405-ENG-48; AC52-07NA27344
• OSTI ID: 1097768
• Report Number(s): LLNL--TR-643914
• Country of Publication: United States
• Language: English

Related Subjects

17 WIND ENERGY
60 APPLIED LIFE SCIENCES