Advancements in floating offshore wind energy are unlocking the potential of the coastal waters of Portugal for the installation of wind farms. A thorough evaluation of coastal effects and variability across different time scales is crucial to ensure successful offshore wind farm investments. State-of-the-art atmospheric reanalysis datasets fall short in explaining the coastal effects due to their modest grid resolution. This study aims to fill this gap by simulating a 31-year wind dataset at a gray-zone resolution of 500 m using the Weather Research and Forecasting model, covering a significant portion of the Portugal coast. The gray-zone refers to grid scales of a few hundred meters, where turbulence is only partially resolved, traditional turbulence modeling breaks down, and large-eddy simulations are computationally prohibitive. The newly generated dataset has been validated with buoy observations and compared against reanalysis datasets, demonstrating improved performance and highlighting its higher fidelity in assessing wind resources. Two wind turbine power curves, the Leanwind 8 megawatt (MW) reference wind turbine (RWT), which has been commercialized, and the International Energy Agency (IEA) 15 MW RWT, which represents future commercialization, are considered in energy production calculations. In the simulated data, the Iberian Peninsula Coastal Jet (IPCJ) emerges as a crucial factor influencing wind maxima, especially during the summer months. The diurnal and annual variability of wind energy resources aligns with the occurrence of IPCJ, highlighting its impact on wind energy generation. The energy production capability of the 15 MW turbine model is demonstrated to be significantly higher, attributed not only to its increased capacity but also to the stronger jet winds near the turbine hub height. Interestingly, wind resources are not monotonically increasing with distance from the coastline, but a tongue-like resource maxima is observed, which is attributed to the IPCJ.

For free-space optical communication or ground-based optical astronomy, ample data of optical turbulence strength (C 2 n) are imperative but typically scarce. Turbulence conditions are strongly site dependent, so their accurate quantification requires in situ measurements or numerical weather simulations. If C 2 n is not measured directly (e.g., with a scintillometer), C 2 n parameterizations must be utilized to estimate it from meteorological observations or model output. Even though various parameterizations exist in the literature, their relative performance is unknown. We fill this knowledge gap by performing a systematic three-way comparison of a flux-, gradient-, and variance-based parameterization. Each parameterization is applied to both observed and simulated meteorological variables, and the resulting C 2 n estimates are compared against observed C 2 n from two scintillometers. The variance-based parameterization yields the overall best performance, and unlike other approaches, its application is not limited to the lowest part of the atmospheric boundary layer (i.e. the surface layer). We also show that C 2 n estimated from the output of the Weather Research and Forecasting model aligns well with observations, highlighting the value of mesoscale models for optical turbulence modeling.

In this chapter, we elaborate on several similarity theory-based and empirical wind speed profile formulations. We highlight their strengths and weaknesses through various examples from the literature. Some of these formulations are sometimes inappropriately used in various practical applications (e.g., offshore wind resource assessments). We provide guidance in their proper usage.

Free-Space Optical Communication (FSOC) links are considered a key technology to support the increasing needs of our connected, data-heavy world, but they are prone to disturbance through atmospheric processes such as optical turbulence. Since turbulence is highly dependent on local topographic and meteorological conditions, modeling optical turbulence strength (Cn 2) is challenging during the design phase of an optical link or network. Over the past 25 years, (see manuscript PDF for symbol) parameterizations of varying complexities have been combined with various numerical weather prediction models for the spatio-temporal estimation of (Cn 2). However, the outputs of these models can exhibit substantial variability based on the user-defined configuration that determines how atmospheric processes are represented. To address this concern, we propose to run not a single model configuration but multiple diverse ones to generate an ensemble estimate of (Cn 2). We employ the Weather Research and Forecasting model (WRF) with ten different Planetary Boundary Layer (PBL) physics schemes forming a diverse ensemble yielding a probabilistic (Cn 2) estimate. We demonstrate that this ensemble outperforms the individual runs when compared to scintillometer field measurements and show it to be robust against outliers. We believe that FSOC downstream tasks such as link budget estimations should also become more robust if based on a (Cn 2) ensemble estimate compared to single model runs.

Only a few studies on the overall impact of climate change on offshore wind power production and wind power ramps in the North Sea region have been published. This study focuses on the characteristics of expected wind power production and wind power ramps in the future climate aided by the classification of circulations patterns using a self-organizing map (SOM). A SOM is used to cluster high-resolution CMIP5-CORDEX sea level pressure data into 30 European area weather patterns. These patterns are used to better understand wind power production trends and any potential changes. An increased frequency of occurrence and extended persistence of high pressure systems lasting at least 24 h is projected in the future. Whereas a contrasting reducing tendency for low-pressure systems is estimated. No significant evidence is seen for a change in wind power capacity factor over the North Sea, though tentative evidence is seen for a reduction in wind power ramps. Annual energy production is seen to be dominated by a small number of weather patterns with westerly, south-westerly or north-westerly winds. Future wind power production is projected to become less from westerly winds and more from south-westerly and north-westerly flows. Ramp up events are primarily associated with strong south-westerly winds or weather patterns with a weak pressure gradient. Ramp down events have a stronger association with more north-westerly flow. In a future climate, a reduction in ramp up events associated with weak pressure gradients is projected.

In this study, we utilize a novel approach to solve the Ekman equations for eddy-viscosity profiles in the stable boundary-layer. By doing so, a well-known expression for the stable boundary-layer height by Zilitinkevich (Boundary-Layer Meteorology, 1972, Vol. 3, 141–145) is rediscovered.

Recently, Basu and Holstlag (2021) proposed a unified framework for describing outer length scales (OLS). By utilizing this framework, we document various characteristics of OLS in nocturnal boundary layers over the US Great Plains.

In this paper, we revisit a well-known formulation of temperature structure parameter (CT2), originally proposed by V. I. Tatarskii. We point out its limitations and propose a revised formulation based on turbulence variance and flux budget equations. Our formulation includes a novel physically-based outer length scale which can be estimated from routine meteorological data.

In this study, the stability dependence of turbulent Prandtl number (Pr_t) is quantified via a novel and simple analytical approach. Based on the variance and flux budget equations, a hybrid length scale formulation is first proposed and its functional relationships to well-known length scales are established. Next, the ratios of these length scales are utilized to derive an explicit relationship between Pr_t and gradient Richardson number. In addition, theoretical predictions are made for several key turbulence variables (e.g., dissipation rates, normalized fluxes). The results from our proposed approach are compared against other competing formulations as well as published datasets. Overall, the agreement between the different approaches is rather good despite their different theoretical foundations and assumptions.

In the near future, wind and solar generation are projected to play an increasingly important role in Europe's energy sector. With such fast-growing renewable energy development, the presence of simultaneous calm wind and overcast conditions could cause significant shortfalls in production with potentially serious consequences for system operators. Such events are sometimes dubbed “Dunkelflaute” events and have occurred several times in recent history. The capabilities of contemporary mesoscale models to reliably simulate and/or forecast a Dunkelflaute event are not known in the literature. In this paper, a Dunkelflaute event near the coast of Belgium is simulated utilizing the Weather Research and Forecasting (WRF) model. Comprehensive validation using measured power production data and diverse sets of meteorological data (e.g., floating lidars, radiosondes, and weather stations) indicates the potential of WRF to reproduce and forecast the boundary layer evolution during the event. Extensive sensitivity experiments with respect to grid-size, wind farm parameterization, and forcing datasets provide further insights on the reliability of the WRF model in capturing the Dunkelflaute event.

Thunderstorm downbursts have been reported to cause damage or failure to wind turbine arrays. We extend a large-eddy simulation model used in previous work to generate downburst-related inflow fields with a view toward defining correlated wind fields that all turbines in an array would experience together during a downburst. We are also interested in establishing what role contrasting atmospheric stability conditions can play on the structural demands on the turbines. This interest is because the evening transition period, when thunderstorms are most common, is also when there is generally acknowledged time-varying stability in the atmospheric boundary layer. Our results reveal that the structure of a downburst’s ring vortices and dissipation of its outflow play important roles in the separate inflow fields for turbines located at different parts of the array; these effects vary with stability. Interacting with the ambient winds, the outflow of a downburst is found to have greater impacts in an “average” sense on structural loads for turbines farther from the touchdown center in the stable cases. Worst-case analyses show that the largest extreme loads, although somewhat dependent on the specific structural load variable considered, depend on the location of the turbine and on the prevailing atmospheric stability. The results of our calculations show the highest simulated foreaft tower bending moment to be 85.4 MN-m, which occurs at a unit sited in the array farther from touchdown center of the downburst initiated in a stable boundary layer.