Wind-Ramp-Forecast Sensitivity to Closure Parameters in a Boundary-Layer Parametrization Scheme
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Wind ramps are relatively large changes in wind speed over a period of a few hours and present a challenge for electric utilities to balance power generation and load. Failures of boundary-layer parametrization schemes to represent physical processes limit the ability of numerical models to forecast wind ramps, especially in a stable boundary layer. Herein, the eight “closure parameters” of a widely used boundary-layer parameterization scheme are subject to sensitivity tests for a set of wind-ramp cases. A marked sensitivity of forecast wind speed to closure-parameter values is observed primarily for three parameters that influence in the closure equations the depth of turbulent mixing, dissipation, and the transfer of kinetic energy from the mean to the turbulent flow. Reducing the value of these parameters independently by 25% or by 50% reduces the overall average in forecast wind-speed errors by at least 24% for the first two parameters and increases average forecast error by at least 63% for the third parameter. Doubling any of these three parameters increases average forecast error by at least 67%. Such forecast sensitivity to closure parameter values provides motivation to explore alternative values in the context of a stable boundary layer.
KeywordsBoundary-layer parametrization Wind-speed forecasts Wind ramps
The work reported herein was supported by the US National Science Foundation (NSF) through its Integrated Graduate Education and Research Traineeship (IGERT) Program, award 1069283. Partial support was provided by the NSF also under the State of Iowa EPSCoR Grant 1101284 and by funds through the Iowa State University Foundation associated with the Pioneer Hi-Bred Agronomy Professorship. Partial support was also provided by NSF Grant AGS1624947. The tall-tower meteorological observations were provided through the Tall Tower Wind Measurement Project that was conducted by AWS Truepower and funded by the Iowa Energy Center and the US Dept. of Energy. The tall-tower data from Germany were provided through the Hamburg Meteorological Institute associated with the University of Hamburg. The High Performance Center at Iowa State University provided the bulk of computing resources that were used to run WRF and WRF-LES models for the suite of experiments. Appreciation is given to the reviewers, who provided insightful and helpful comments.
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