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Title: Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model

Journal Article · · Wind Energy
DOI:https://doi.org/10.1002/we.1862· OSTI ID:1637582
 [1];  [1];  [2];  [2];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
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The accuracy of boundary-layer wind profiles occurring during nocturnal low-level jet (LLJ) events, and their sensitivities to variations of user-specifiable model configuration parameters within the Weather Research and Forecasting model, was investigated. Simulations were compared against data from a wind-profiling lidar, deployed to the Northern Great Plains during the U.S. Department of Energy-supported Weather Forecast Improvement Project. Two periods during the autumn of 2011 featuring LLJs of similar magnitudes and durations occurring during several consecutive nights were selected for analysis. Simulated wind speed and direction at 80 and 180 m above the surface, the former a typical wind turbine hub height, bulk vertical gradients between 40 and 120 m, a typical rotor span, and the maximum wind speeds occurring at 80 and 180 m, and their times of occurrence, were compared with the observations. Sensitivities of these parameters to the horizontal and vertical grid spacing, planetary boundary layer and land surface model physics options, and atmospheric forcing dataset, were assessed using ensembles encompassing changes of each of these configuration parameters. Furthermore, each simulation captured the diurnal cycle of wind speed and stratification, producing LLJs during each overnight period; however, large discrepancies in relation to the observations were frequently observed, with each ensemble producing a wide range of distributions, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error and bias values computed over the LLJ cycle (late evening through the following morning) revealed that, while some configurations performed better or worse in different aspects and at different times, none exhibited definitively superior performance. The considerable root mean square error and bias values, even among the ‘best’ performing simulations, underscore the need for improved simulation capabilities for the prediction of near-surface winds during LLJ conditions.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Grant/Contract Number:
AC52-07NA27344; AC06-76RL01830
OSTI ID:
1637582
Report Number(s):
LLNL-JRNL-641176; 760360
Journal Information:
Wind Energy, Vol. 19, Issue 4; ISSN 1095-4244
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

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Cited By (1)

Data assimilation impact of in situ and remote sensing meteorological observations on wind power forecasts during the first W ind F orecast I mprovement P roject (WFIP) journal March 2019

Figures / Tables (23)

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Related Subjects

17 WIND ENERGY
Mesoscale simulation
low-level jet
Weather Research and Forecasting model
Wind Forecast Improvement Project
lidar wind profiler