Mesoscale Modeling of Low-Level Jets over the North Sea

Abstract

Contemporary onshore and offshore wind resource assessment frameworks incorporate diverse multi-scale weather predictionmodels (commonly known as mesoscale models) to dynamically downscale global-scale atmospheric fields to regional-scale (i.e., spatial and temporal resolutions of a few kilometers and a few minutes, respectively). These high resolution mesoscale models aim at depicting the expected wind behavior (e.g., wind shear, wind turning, topographically induced flow accelerations) at a particular location or region. Over the years, numerous model sensitivity and intercomparison studies have investigated the strengths and weaknesses of the models’ parameterizations (including, but not limited to, planetary boundary layer turbulence) in capturing realistic flows over land. In contrast, only a handful of modeling studies have focused on coastal and offshore flows (e.g., coastal fronts, internal boundary layers, land breeze - sea breeze circulations, low level jets); thus, our understanding and predictive capability of these flows remain less than desirable. This impairment, in combination with the recent world-wide surge in offshore wind energy development, provides the rationale for this study.We are currently evaluating the performance of the Weather Research and Forecasting (WRF) model, a new-generation mesoscale model, in simulating some of the aforementioned coastal and offshore flow phenomena. In this paper, we focus on low-level jets and compare the WRF model-simulated results against the observational data from the FINO1 meteorological mast in the North Sea.We also discuss the sensitivities of the WRF model-generated offshore wind fields with respect to several planetary boundary layer turbulence schemes.KeywordsWind SpeedOffshore WindInternal Boundary LayerPlanetary Boundary Layer SchemeLand BreezeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.