Hurricane Florence (2018) was unique due to its slow storm motion during landfall, causing convective rainbands to produce high amounts of precipitation along the coast of North Carolina. This study focuses on the relationship between precipitation asymmetries and atmospheric stability surrounding the tropical cyclone (TC) during the landfall period of a nearly-stationary TC. Previous research with idealized hurricane simulations suggests that atmospheric stability may vary surrounding a TC during landfall, with the atmosphere destabilizing offshore and stabilizing onshore. However, this finding has not been studied using a realistic approach. Due to Hurricane Florence's slow motion, the storm was situated at the land-ocean boundary for multiple days, providing an ideal opportunity to examine the role of atmospheric stability in modifying hurricane precipitation during landfall. This study uses the Advanced Research Weather Research and Forecasting (WRF-ARW) version 3.6.1 to produce high-resolution simulations to examine the variations in precipitation and atmospheric stability surrounding Hurricane Florence. Precipitation accumulation at different temporal scales was used to determine that asymmetries existed during the landfall period. Observed and model-simulated Convective Available Potential Energy (CAPE) were used to measure stability surrounding the TC. Simulated CAPE indicates that there was a significant difference between stability right- and left-of-track. In addition to a control simulation, two experimental simulations were conducted by modifying the land surface to vary the heat and moisture exchange coefficient (HS) and hold the surface roughness (Z0) constant. By isolating the HS to be more moist or dry, the altered low-level moisture was hypothesized to cause the precipitation and convection distributions to become more symmetrical or asymmetrical, respectively. The results from the experimental simulations showed that the altered land surface affects the relative humidity from the surface to 950 mb, which has an immediate impact on stability off-shore left-of-track. Overall, the precipitation and stability asymmetries were not significantly impacted by the altered near-surface moisture, indicating other physical factors contribute to the asymmetries. The results of this study provide insight into the role of atmospheric instability in generating asymmetrical precipitation distributions in landfalling TCs, which may be particularly important in slow-moving TCs like Hurricane Florence. / Master of Science / Landfalling tropical weather systems such as hurricanes can significantly impact coastal communities due to severe flooding and damaging winds. Hurricane Florence (2018) affected coastal and inland communities in North Carolina and South Carolina when the storm produced a significant amount of precipitation over the coastal region. During landfall, the center of Hurricane Florence moved slowly parallel to the coastline, which creates a suitable time frame to isolate and study the influence of landfall on precipitation asymmetries. Precipitation asymmetry occurs when more rainfall falls on one side of the hurricane; for example, heavier precipitation tends to occur on the right side of a hurricane during the landfall period. Hurricane rainbands that are responsible for producing heavy precipitation form in areas where there is higher moisture near the surface while lighter precipitation forms in areas where there is drier air near the surface. This study focuses on the relationship between land surface moisture and spatial variations of precipitation during the hurricane landfall period by studying observations and model simulations of Hurricane Florence. The model simulation of Hurricane Florence found that more precipitation fell on the right side of the storm, indicating that there was precipitation asymmetry. In order to understand how the precipitation asymmetries form, the model simulation of Hurricane Florence was modified to create two experiments. In the first experiment, the land surface was altered to have a moister land surface, which should cause the hurricane precipitation to be more symmetrical. In the second experiment, the land surface was altered to have a drier land surface, which should cause stronger precipitation asymmetry. However, the results did not match this expectation. Instead, both experiments simulated asymmetrical precipitation with more precipitation falling on the right side of each storm during the landfall period. These results suggest that the modified land surface moisture did not have a significant impact on the formation of precipitation asymmetries. Other factors are therefore suggested to have a more dominant influence on the development of precipitation. Overall, this work can support future studies by ruling out the impact of land surface moisture on a hurricane's precipitation formation during the landfall period.

Losses for wake effects in offshore wind farms represent about 10% to 20% of the park annual energy production. Several analytical wake models have been developed and implemented to predict the power deficit of a wake-affected wind turbine. Validating and parameterizing the wake models available in the industry is essential to better predict the wake losses and thus maximize the energy yield of future offshore developments. In this study, a wake model validation is undertaken for the three models available in the commercial software WindSim. Data from Horns Rev wind farm is used to that purpose. Next, the models that show the best agreement with the observations are parameterized to better describe the power losses of a future offshore wind farm at Bockstigen. To finish with, an optimization sensitivity study is carried out and a final optimal layout is determined according to the seabed depth.

As tapping energy from wind expands rapidly worldwide, it is a common procedure to locate a practicable site to extract energy from abundant wind flow by building wind farms. Comprehensive understanding of wind resource at a site   is important to perform the main activities say, wind flow modeling, wind   turbines micro siting, annual energy yield calculation and cost of energy   estimation. Wind measuring campaigns involve using of measuring instruments   such as meteorological tower instrumented with anemometers, wind vanes and   temperature sensors; remote sensing devices such as SoDAR, LiDAR. These   meteorological devices provide detailed information on wind behavior with   respect to the height, time and temperature. These systems were proven in   providing promising wind measurements even though they are susceptible to   certain weather conditions. The   study progressed by focusing on the wind behavior at three locations to   investigate the possible factors that varies the wind character. A location   with one met mast and two AQ500 SoDAR systems was considered for this project   where one AQ500 is 800m away and other AQ500 is 5515m away from the point of   Met mast. The location is contemplated as a decent approach to the spatial   analysis of the wind resource as there is a large scope to analyze the wind   character between two nearby sites and two faraway sites. Monostatic 3-beam   SoDAR systems from AQ System, Sweden and 100m meteorological tower with   instruments are used in this project work for collecting the wind data.   One-year worth of wind data at standard 10min intervals has been collected   from the three systems. This report outlines the theoretical description of project location, AQ500 SoDAR and Met mast. A detailed explanation of the data quality control and filtering methods are discussed along with respective reasons. The conclusion is drawn after performing the statistical analysis between wind speed and other parameters such as turbulent intensity, wind direction, thermal stability and temperature. Mat lab is used for computing and analyzing the wind data from three systems.

Wind energy is rapidly expanding worldwide, and it is common practice to maximize production by selecting sites with higher wind potential. To perform critical operations such as wind flow modeling, wind turbine micro placement, annual energy yield calculation, and cost of energy estimation, a thorough understanding of a site's wind resource is required. The present study examines data from three independent wind measurement systems to see how measured data depends on the choice of the measurement system and how this might forecast the wind resource and, consequently, the energy output of a potential wind farm.  The present analysis uses three measurement units, one meteorological mast (met mast), and ground-based AQ510 Sound Detection And Ranging (SoDAR) & SoDAR and ZX 300 Light Detection And Ranging (LiDAR) devices to capture wind data for nearly a year. This study describes the operating concept of remote sensing devices such as AQ510 SoDAR and ZX 300 LiDAR, the linear regression relationship between wind speed measured on the Met Mast versus SoDAR, Met Mast versus LiDAR, and SoDAR versus LiDAR. Additionally, an understanding of stratification for this potential wind farm’s site is explored for specific days during spring, summer, and winter.  The results of the intercomparison study among Met Mast, SoDAR & LiDAR show quite a good relationship between the different measurement systems, being the correlation coefficient between the mast and the LiDAR measurements being slightly larger than between the mast and the SoDAR measurements. Comparison during the stability and instability regimes show a larger difference in some cases. Python and MS Excel are used to build data filtering procedures, the Richardson number, and comparison computations.

As wind turbines have grown, new installation areas become possible. Placing wind turbines in forested landscapes introduce uncertainties to the wind resource estimation. Even though close-to-canopy processes have been studied intensively during the last thirty years, the focus has mostly been on exchange processes and the height span of the studies has been below the rotor of a modern wind turbine. This thesis contains analysis of new measurements from a 138 m high tower in a forested landscape. The previous knowledge of near-canopy processes is extended to the region above the roughness sublayer. It is shown that above the roughness sublayer, the surface layer behaves as over low vegetation, and Monin-Obukhov similarity is shown to hold for several variables. However, in stable stratification, effects that could be linked to the boundary layer depth are shown to be present in the measurements. These include wind turning with height, the behaviour of the turbulence length scale and the curvature of the wind profile. Two new analytical models are presented in the thesis. One is a flux-profile expression in the roughness sublayer, which allows for analytical integration of the wind gradient. The model suggests that the roughness-sublayer effect depends on stratification and that the aerodynamic roughness length changes with stability. A decrease of roughness length in stable stratification is confirmed with a new method to determine the roughness length using measurements from the 138 m tower. The other model determines the spectral tensor in stable stratification using analytical solution to the rapid distortion equations for stratified shear flow, with homogeneous stratification and shear. By using a formulation for the integration time of the distortions of an isotropic spectrum, a model is derived which provides the cross spectra of velocity and temperature at any two given points in space. Finally the existence of waves in the wind over forests is investigated and it is concluded that the Kelvin-Helmholtz instability can create waves which are coherent in time and exist over the entire height span of wind turbine rotors. Linear wave theory is shown to be able to explain certain features of the waves. / Vindforsk III, Wind power in forests / Vindforsk IV, Forest wind

The objective of this work is to characterize the patterns of wind in the state of Alagoas, assessing whether conditions are favorable for electricity generation through aerogenerators, and relate these patterns with local parameters, observing the behavior of atmospheric stability through different methods. We sought for determine the seasonal pattern of wind speed and direction, air temperature, intensity of turbulence and squall factor of three distinct regions of the state: Sertão, Agreste and Litoral, and evaluate the behavior of atmospheric stability in its annual cycle through the calculation of stability parameters. Daily, monthly and annual means cycles of meteorological variables that could possibly describe the wind pattern in the state of Alagoas were examined. The founded patterns were rather different among the three regions, and the most satisfactory wind behavior for wind power production was found in the Agreste region (Girau do Ponciano). The Sertão region (Água Branca), demonstrated an influence of an usual annual Brazilian Northeast wind system known as Aracati. The Aracati leads the wind speeds to reach its maximum values during the night period, what is found to be an unusual behavior. There were positive associations between air temperature peaks and wind speed in many seasons, and positive associations among the prevalence between NE and SE (interval where the sea breeze effect is predominant) and the maximum values of wind speed, indicating a possible wind intensification due to the sea breeze. It was found a decrease of the wind speed in land breeze occurrences, indicating that the southern trade winds tend to reduce the wind speed in the coastal region, and sometimes bringing land breezes occurrences to vanish. The wind speed patterns were higher in stations placed inland(Girau Ponciano, Palmeira dos Índios and Água Branca) than the coastal stations (Feliz Deserto, Roteiro e Maragogi), possibly because the inland stations are placed in higher altitudes. The atmospheric turbulence recorded in the six stations showed relatively lower values than those found in the literature, which is a good indicator for wind power usage . The atmospheric stability in Feliz Deserto was greater during the summer, decreasing with the winter approaching, and the stability estimation by the Richardson number and Brunt-Vaisala frequency methods were quite consistent, showing a maximum variation of 5% between them. / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho teve o objetivo de caracterizar os padrões de vento no Estado de Alagoas, avaliando se existem condições propicias para a geração de energia elétrica através de aerogeradores no Estado, e relacionar os padrões de vento com parâmetros locais, observando o comportamento da estabilidade atmosférica através de diferentes métodos. Procurou-se determinar o padrão sazonal da velocidade e direção do vento, temperatura do ar, intensidade de turbulência e fator de rajadas em três regiões distintas do Estado: Litoral, Agreste e Sertão, e avaliar o comportamento da estabilidade atmosférica no seu ciclo anual através do cálculo de parâmetros de estabilidade. Foram analisados ciclos médios diários, mensais e anuais de variáveis meteorológicas que pudessem descrever o padrão de vento no Estado de Alagoas. O padrão evidenciado foi relativamente diferente entre as regiões, tendo seu comportamento para aproveitamento eólico se mostrado mais satisfatório na região do Agreste (Girau do Ponciano). A região do Sertão (Água Branca) evidenciou uma influência anual de um regime de ventos comum na região Nordeste Brasileira, conhecido como Aracati, que faz com que as velocidades do vento obtenham seus máximos no período noturno, o que é um fato fora do padrão. Houve associações positivas entre picos de temperatura do ar e de velocidade do vento em muitas estações, e associações positivas com as predominâncias entre NE e SE (intervalo onde se encontra a predominância do efeito de brisa marítima) e os máximos valores de velocidade do vento, indicando uma possível intensificação do vento através da brisa marítima. Foi observada uma frenagem da velocidade do vento em situações de brisa terrestre, indicando que os ventos alísios tendem a diminuir a velocidade do vento na região Litorânea, e por vezes desconfigurar a ocorrência da brisa terrestre. Os padrões de velocidade do vento foram maiores nas estações situadas no interior (Girau do Ponciano, Palmeira dos Índios e Água Branca) do que no Litoral (Feliz Deserto, Roteiro e Maragogi), possivelmente devido às estações localizadas no interior estarem em maiores altitudes. A turbulência atmosférica nas seis estações apresentou valores relativamente menores do que os encontrados na literatura, sendo um bom indicativo para aproveitamento eólico. A estabilidade atmosférica em Feliz Deserto se mostrou maior durante o Verão, diminuindo à medida que se aproxima o Inverno, sendo que a estimativa da estabilidade pelos métodos do número de Richardson e da freqüência de Brunt- Vaisala foram bastante coerentes, apresentando no máximo 5% de diferença entre eles.

In the wind resource and wind turbine suitability industry Computational Fluid Dynamics has gained widespread use to model the airflow at proposed wind farm locations. These models typically focus on the neutrally stratified surface layer and ignore physical process such as buoyancy and the Coriolis force. These physical processes are integral to the accurate description of the atmospheric boundary layer and reductions in uncertainties of turbine suitability and power production calculations can be achieved if these processes are included. The present work focuses on atmospheric flows in which atmospheric stability and the Coriolis force are included. The study uses Monin-Obukhov Similarity Theory to analyse time series data output from a proposed wind farm location to determine the prevalence and impact of stability at the location. The output provides the necessary site data required for the CFD model as well as stability-dependent wind profiles from measurements. The results show non-neutral stratification to be the dominant condition onsite with impactful windfield changes between stability conditions. The wind flows considered in this work are classified as high Reynolds number flows and are based on numerical solutions of the Reynolds-Averaged Navier-Stokes equations. A two-equation closure method for turbulence based on the k __ turbulence model is utilized. Modifications are introduced to standard CFD model equations to account for the impact of atmospheric stability and ground roughness effects. The modifications are introduced by User Defined Functions that describe the profiles, source terms and wall functions required for the ABL CFD model. Two MOST models and two wall-function methods are investigated. The modifications are successfully validated using the horizontal homogeneity test in which the modifications are proved to be in equilibrium by the model�s ability to maintain inlet profiles of velocity and turbulence in an empty domain. The ABL model is applied to the complex terrain of the proposed wind farm location used in the data analysis study. The inputs required for the stability modifications are generated using the available measured data. Mesoscale data are used to describe the inlet boundary conditions. The model is successfully validated by cross prediction of the stabilitydependent wind velocity profiles between the two onsite masts. The advantage of the developed model is the applicability into standard wind industry loading and power production calculations using outputs from typical onsite measurement campaigns. The model is tuning-free and the site-specific modifications are input directly into the developed User Defined Functions. In summary, the results show that the implemented modifications and developed methods are applicable and reproduce the main wind flow characteristics in neutral and non-neutral flows over complex wind farm terrains. In additions, the developed method reduce modelling uncertainties compared against models and measurements that neglect non-neutral stratification. / Dissertation (MEng)--University of Pretoria, 2018. / Mechanical and Aeronautical Engineering / MEng / Unrestricted

Wind power is seen as one of the most effective means available to combat the twin crises of global climate change and energy security. The annual market growth has established wind power as the leading renewable energy technology. Due to the availability of sparsely populated and flat open terrain, the Yucatán Peninsula located in eastern México is a promising region from the perspective of wind energy development but no comprehensive assessment of wind resource has been previously published. A basic requirement when developing wind power projects is to study the main characteristic parameters of wind in relation to its geographical and temporal distribution. The analysis of diurnal and seasonal wind patterns are an important stage in the move towards commercial exploitation of wind power. The research developed during the PhD has comprehensively assessed the wind behaviour over the Yucatán Peninsula region covering long term patterns at three sites, a spatial study using short term data for nine sites, a vertical profile study on one inland site and an offshore study made on a pier at 6.65km from the North shore. Monthly trends, directional behaviours and frequency distributions were identified and discussed. The characteristics of the wind speed variation reflected their proximity to the coast and whether they were influenced by wind coming predominantly from over the land or predominantly from over the sea. The atmospheric stability over the eastern seas was also analysed to assess thermal effects for different wind directions. Diurnal wind speed variations are shown to be affected in particular by the differing wind conditions associated with fetches over two distinct offshore regions. Seasonal behaviour suggests some departure from the oscillations expected from temperature variation. The offshore wind is thermally driven suggesting largely unstable conditions and the potential development of a shallow Stable Internal Boundary Layer.

I have decided to deal with the issue of "Risk Sources of Ammonia Cooling Systems and Their Eventual Accidental Impacts" as the risk of leakage from the cooling systems using ammonia as a coolant still prevails these days. Eventual accidental leakage simulation models were applied to several winter stadiums using ammonia as a coolant. Based on these results, it has been assessed how dangerous these sources for the citizens living in their surroundings are and measures to increase safety were suggested, too.

Two post processing methods for quantifying the shadow effect of the offshore wind farm Princes Amalia (PA) onto Egmond aan Zee (OWEZ) wind farm are analyzed and benchmarked. The first method is the author’s proposed shadow effect determination method (SEDM), which quantifies an offshore wind farm’s shadow effect based on mesoscale WRF (Weather Research Forecast) idealized modeling and the observed frequency of the analyzed site’s wind conditions. The Fitch turbine parametrization scheme and Mellor-Yamada-Nakanishi-Niino (MYNN) surface layer and planetary boundary layer (PBL) schemes were used to simulate the wind farm’s interactions, based on site conditions. The proposed physical downscaling method (SEDM) uses filtered simulated atmospheric stability and wind speed conditions, in order to calculate the percent wind speed deficit downstream of PA, with regard, first, to observed wind speed frequency and, secondly, to wind speed and corresponding atmospheric stability regimes. Then a statistical downscaling method, based on the established Analog Ensemble (AnEn) technique, developed by Luca Delle Monache et al. (2011) was employed to verify the results from the first method. This method runs a post processing algorithm using the weighted average of the observations that were verified when the 15 best analogs were valid. Observed wind speed data at 10 m and 50 m height was used as Numerical Weather Prediction (NWP) input data and fit to observed time series data. From this, wind speeds at 116 m were extrapolated, in order to estimate the reconstructed atmospheric stability. The two methods were benchmarked and shadow effects were quantified in the range of 7.53% - 22.92% for the SEDM and within an 80% confidence interval of 0.23% -1.83% for the statistical downscaling method. Given the physical method’s exceedance of this confidence interval, WRF idealized modeling proves itself as a consistent means of quantifying an offshore wind farm’s wake, as demonstrated by comparable studies, however inaccurate when benchmarked to statistical modelling methods that use observed wind speed data to recreate atmospheric conditions. / Wake Research Group