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Boundary-Layer Meteorology

, Volume 170, Issue 3, pp 507–518 | Cite as

Sensitivity of Turbine-Height Wind Speeds to Parameters in the Planetary Boundary-Layer Parametrization Used in the Weather Research and Forecasting Model: Extension to Wintertime Conditions

  • Larry K. BergEmail author
  • Ying Liu
  • Ben Yang
  • Yun Qian
  • Joseph Olson
  • Mikhail Pekour
  • Po-Lun Ma
  • Zhangshuan Hou
Notes and Comments
  • 252 Downloads

Abstract

We extend the model sensitivity analysis of Yang et al. (Boundary-Layer Meteorol 162: 117–142, 2017) to include results for February 2011, in addition to May of the same year. We investigate the sensitivity of simulated hub-height wind speeds to the selection of 12 parameters applied in the Mellor–Yamada–Nakanishi–Niino planetary boundary-layer parametrization in the Weather Research and Forecasting model, including parameters used to represent the dissipation of turbulence kinetic energy (TKE), Prandtl number (Pr), and turbulence length scales. Differences in the sensitivity of the ensemble of simulated wind speed to the various parameters can largely be explained by changes in the static stability. The largest monthly differences are found during the day, while the sensitivity to many of the parameters during the night is similar regardless of the month. This finding is consistent with an increased frequency of daytime stable conditions in February compared to May. The spatial variability of the sensitivity to TKE dissipation and Pr can also be attributed to variability in the static stability across the domain at any point in time.

Keywords

Parametrization schemes Parametric sensitivity Planetary boundary layer Turbine-height wind speed Weather research and forecasting model 

Notes

Acknowledgements

This work has been supported by the U.S. Department of Energy’s Wind Power Program. The Pacific Northwest National Laboratory (PNNL) is operated for the US Department of Energy by Battelle Memorial Institute under contract DE-AC07-76RL01830. The PNNL Institutional Computing (PIC) provided computational resources. The NARR datasets were freely obtained from the CISL Research Data Archive at http://rda.ucar.edu/datasets/ds608.0/. WRF model output data used in this study are stored at PNNL and are available upon request from the corresponding author. Data from CBWES are available from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) data archive. Dr. Ben Kravitz (PNNL) is thanked for his comments on an earlier version of the manuscript.

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Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply  2018

Authors and Affiliations

  1. 1.Pacific Northwest National LaboratoryRichlandUSA
  2. 2.CMA-NJU Joint Laboratory for Climate Prediction Studies, Institute for Climate and Global Change Research, School of Atmospheric SciencesNanjing UniversityNanjingChina
  3. 3.University of Colorado/CIRESBoulderUSA

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