In recent years there has been an increase in offshore wind energy, which poses the need for accurate wind speed estimates in the marine environment, especially in coastal areas where most wind turbines will be placed. This thesis is focused on the Baltic Sea, which is a small, semi-enclosed sea where land-sea interaction play an important role in explaining the wind patterns. Mesoscale model simulations can be used to study the marine environment, where observations are often scarce. In this thesis the Weather Research and Forecasting (WRF) model is used. In the first study simulations show that stable stratification over sea is very common in spring and summer and is associated with an increase in low-level jet occurrence and increased wind shear below 200 m, at heights where wind turbines are erected. The model performance in stable conditions is evaluated against aircraft measurements using several boundary layer parametrization schemes, and it is shown that the low-level jet height and strength is not accurately captured with any of the parametrizations. In the second study the advection of land features is investigated. From simulations, aircraft observations and satellite images it is shown that boundary layer rolls are created in the convective boundary layer over land, and advected several tens of kilometres out over sea surface, despite the stable stratification, where convective turbulence dissipates quickly. The occurrence of boundary layer rolls gives rise to horizontal wind speed variations of several meters per second over distances of kilometres, which can increase the uncertainty of short term wind speed forecasts in coastal areas with offshore flow. It is shown that mesoscale processes in and above the marine boundary layer are important in modifying the wind field in distances of at least 100 km from the coast and that models still need to be improved in order to capture these conditions. / Under de senaste decennierna har vindkraftsutbyggnaden ökat till havs, vilket innebär att det krävs tillförlitliga vindhastighetsuppskattningar över hav, särskilt i kustområden, där de flesta vindturbinerna kommer att placeras. Den här avhandlingen kommer att fokusera på Östersjön, vilket är ett relativt litet hav omgivet av landmassor, där land-hav-interaktion har en stor påverkan på vindmönstren över havet. Mesoskaliga modeller kan användas för att studera den lägre delen av den marina atmosfären. I den här avhandlingen används modellen "Weather Research and Forecasting" (WRF). I den första studien visar simuleringar att stabila förhållanden över havet är vanligt förekommande under sommar och vår, och sker i samband med en ökad förekomst av vindmaxima på låg höjd och ökad vindskjuvning under 200 m - alltså på höjder där vindkraftverk förekommer. Modellen, med flertalet gränskiktsparametriseringar, utvärderas för stabila fall mot flygplansmätningar, och resultaten visar att styrkan och höjden för vindmaxima är antingen över- eller underskattade oavsett parametrisering. I den andra studien undersöks advektiva fenomen. Simuleringar, flyplansobservationer och satellitbilder visar att avlånga rullvirvlar uppstår i det konvektiva gränsskiktet över land och advekteras flera tiotals kilometer över hav ut från kusten. Detta trots stabila förhållanden över havet, där den konvektiva turbulensen snabbt dör ut. Rullvirvlarna ger upphov till variationer i horisontell vindhastighet på flera meter per sekund över avstånd på några kilometer, vilket kan öka osäkerheten hos korttidsprognoser för vind när det är blåser från land. Sammanfattningsvis har det har visats att mesoskaliga processer i och ovanför det marina gränsskiktet har en stor inverkan på vindfältet åtminstone 100 km från kusten, och modeller behöver fortfarande förbättras för att kunna fånga dessa företeelser. / StandUp for Wind

In this work we apply data assimilation onto meteorological model WRF for local domain. We use bayesian statistics, namely Sequential Monte Carlo method combined with particle filtering. Only surface wind data are considered. An application written in Python programming language is also part of this work. This application forms interface with WRF, performs data assimilation and provides set of charts as output of data assimilation. In case of stable wind conditions, wind predictions of assimilated WRF are significantly closer to measured data than predictions of non-assimilated WRF. In this kind of conditions, this assimilated model can be used for more accurate short-term local weather predictions. Powered by TCPDF (www.tcpdf.org)

O presente estudo visa à obtenção de um modelo utilizando o acoplamento dos códigos WRF e CALPUFF com o objetivo de obter as características do campo meteorológico e da dispersão dos poluentes NO2 e SO2 de uma Usina Termelétrica localizada em Linhares. Foi utilizada uma grade de 100×100 células, com resolução de 1 km durante 90 h. Para vias de comparação, outra simulação foi feita sem a entrada do modelo WRF no CALMET, utilizando uma grade 15×15 sem modificar nenhum outro parâmetro. Os resultados obtidos foram comparados com dados do aeroporto de Vitória e com a legislação ambiental vigente. Para a camada limite planetária, o resultado obtido da simulação WRF/CALMET se encontra dentro da faixa encontrada na literatura. Os demais resultados, média de velocidade e direção do vento, para as duas simulações diferem entre si e dos dados do aeroporto, fato que já era esperado devido à distância e orografia entre a Usina e os dados da estação utilizados como entrada nos modelos. A concentração máxima obtida para os poluentes estudados se encontram dentro dos padrões de qualidade do ar. Devido à falta de dados observacionais, não foi possível uma genuína validação dos resultados, mas, sabendo a localização dos picos, foi possível sugerir locais de amostragem para futura comprovação dos resultados. / This study aims to create a model using the coupling of the WRF and CALPUFF codes in order to obtain characteristics of the meteorological field and the dispersion of pollutants NO2 and SO2 of a power plant located at the city of Linhares. The field consists of a grid of 100×100 cells resolution of 1 km for 90 h. Another simulation was made without using WRF as an input into CALMET, in the purpose of comparison, using a 15×15 grid and no change of other parameters. The results were compared to data from the airport of Vitória and against environmental legislation. For the planetary boundary layer the results of WRF/CALMET simulation are within the range found in the literature. The results of average wind speed and direction obtained by both simulations are different from each other and from the data of the airport,such as expected due to the distance and orography of the power plant and station data used as input into the models. The maximum concentrations of the pollutants are within air quality standards. Due to lack of observational data, genuine validation of the results is not feasible, but knowing the location of the concentration peak, it was possible to propose suitable sampling sites for future verification.

Submitted by Sandro Camargo (sandro.camargo@unipampa.edu.br) on 2015-05-09T19:22:56Z No. of bitstreams: 1 107110003.pdf: 5399700 bytes, checksum: 078f09d78c88ad07051ceb62107845c6 (MD5) / Made available in DSpace on 2015-05-09T19:22:56Z (GMT). No. of bitstreams: 1 107110003.pdf: 5399700 bytes, checksum: 078f09d78c88ad07051ceb62107845c6 (MD5) Previous issue date: 2012-08-06 / A dependência da energia elétrica exige a procura de formas alternativas para produção sustentável, como os parques eólicos. Conforme o Plano Decenal de Expansão de Energia (PDE), a geração proveniente de fontes de energia alternativas e sustentáveis como a de usinas eólicas deverá aumentar de 1% para 7%. Logo, a implantação de parques eólicos começará a afetar o planejamento e programação da operação energética, principalmente nos subsistemas sul e nordeste. No entanto, apesar do vento ser um recurso praticamente inesgotável, o problema reside na inconstância, não permitindo contar com a geração de energia elétrica que pode variar significativamente mesmo em um intervalo pequeno de tempo, o operador do sistema tem que estar preparado para atuar no despacho das demais usinas. Neste contexto, uma estimativa de curto prazo é fundamental. Essa operação não pode se basear nos mapas eólicos cujos valores de velocidade são uma média anual, no máximo de estações do ano, além de se limitarem a uma ou duas alturas o que não favorece dados confiáveis para a geração. A dificuldade em obter uma estimativa mais concreta sobre a energia disponível reside na falta de medições correlacionadas de variáveis climáticas, geração e um modelo eficiente de previsão de curto prazo, sendo um dos fatores que impede uma maior penetração deste tipo de fonte na matriz energética brasileira. Este trabalho apresenta uma metodologia para avaliar dados meteorológicos e geográficos que afere o campo de vento na altura do eixo de turbinas eólicas a fim de estimar o fluxo de ar, possibilitando calcular o potencial elétrico instantâneo produzido. Essa estimativa pode ser estendida para vários locais, a fim de acompanhar a variação de vento ocasionada pelos efeitos climáticos. O modelo meteorológico CALMET e WRF permite simular o campo de vento, criando um modelo de previsão probabilístico do vento, estimando a energia elétrica a ser produzida em determinados horários de acordo com o modelo das turbinas. O software ANAREDE analisa o comportamento da energia gerada que influenciara no fluxo de potência do sistema. Com este resultado o Operador Nacional do Sistema Elétrico (ONS) pode executar a coordenação mais precisa do despacho hidrotérmico de curto prazo, bem como o dimensionamento da reserva de potência operativa. / The dependence of the electrical energy demands the search for alternative ways to produce sustainable, such as wind farms. As stated in the Brazil’s Ten Year Plan for Expansion of Energy (PDE), the generation from alternative and sustainable energy sources such as the wind farms is expected to increase from 1% to 7%. Therefore, the deployment of wind farms begins to affect the planning and scheduling of energy operation, mainly in south and northeast Brazilian subsystems. However, despite the wind being a virtually inexhaustible resource, the problem is the inconsistency, not allowing rely on the generation of electrical energy that can vary significantly even in a small interval of time, the system operator must be prepared to act in order of other growers. This operation cannot be based on maps whose wind speed values are the average annual maximum of seasons, and are limited to one or two heights. This paper presents a methodology for assessing meteorological and geographical data to measure the wind field in the turbine hub height, allowing to calculate the instantaneous electric power produced. This estimate can be extended to various points and times of day in order to monitor the variation of wind caused by climatic effects. The CALMET meteorological model WRF and allows to simulate the wind field, creating a probabilistic model for predicting the wind, estimating the electricity to be produced at certain times according to the model of the turbines. ANAREDE The software analyzes the behavior of the energy generated that influenced the flow of power system. With this result the System Operator can perform a more precise coordination of the hydrothermal short term dispatch, as well as the operative power reserve dimensioning. / Wind Forecast / Operation Planning / Wind Generation

abstract: Understanding and predicting climate changes at the urban scale have been an important yet challenging problem in environmental engineering. The lack of reliable long-term observations at the urban scale makes it difficult to even assess past climate changes. Numerical modeling plays an important role in filling the gap of observation and predicting future changes. Numerical studies on the climatic effect of desert urbanization have focused on basic meteorological fields such as temperature and wind. For desert cities, urban expansion can lead to substantial changes in the local production of wind-blown dust, which have implications for air quality and public health. This study expands the existing framework of numerical simulation for desert urbanization to include the computation of dust generation related to urban land-use changes. This is accomplished by connecting a suite of numerical models, including a meso-scale meteorological model, a land-surface model, an urban canopy model, and a turbulence model, to produce the key parameters that control the surface fluxes of wind-blown dust. Those models generate the near-surface turbulence intensity, soil moisture, and land-surface properties, which are used to determine the dust fluxes from a set of laboratory-based empirical formulas. This framework is applied to a series of simulations for the desert city of Erbil across a period of rapid urbanization. The changes in surface dust fluxes associated with urbanization are quantified. An analysis of the model output further reveals the dependence of surface dust fluxes on local meteorological conditions. Future applications of the models to environmental prediction are discussed. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2019

Spatial distribution of diurnal variations of aerosol properties in South Korea, both long term and short term, is studied by using 9 AERONET sites from 1999 to 2017 for long-term averages and from an additional 10 sites during the KORUS-AQ field campaign. The extent to which WRF-Chem model and the GOCI satellite retrieval can describe these variations is also analyzed. In daily average, Aerosol Optical Depth (AOD) at 550 nm is 0.386 and shows a diurnal variation of +20 to -30% in inland sites, respectively larger than the counterparts of 0.308 and ± 20% in coastal sites. Both the inland and coastal sites have their diurnal variation peaks in the early morning and in the evening with noontime and early afternoon valleys. In contrast, Angstrom exponent values in all sites are between 1.2 and 1.4 with the exception of the inland rural sites having smaller values near 1.0 during the early morning hours. All inland sites experience a pronounced increase of Angström Exponent from morning to evening, reflecting overall decrease of particle size in daytime. To statistically obtain the climatology of diurnal variation of AOD, a minimum of requirement of ~2 years of observation is needed in coastal rural sites, twice more than the urban sites, which suggests that diurnal variation of AOD in urban setting is distinct and persistent. AERONET, GOCI, WRF-Chem, and observed PM2.5 data consistently show dual peaks for both AOD and PM2.5, one at ~ 10 KST and another ~14 KST. While Korean GOCI satellite is able to consistently capture the diurnal variation of AOD, WRF-Chem clearly has the deficiency to describe the relatively change of peaks and variations between the morning and afternoon, suggesting further studies for the diurnal profile of emissions. Overall, the relative small diurnal variation of PM2.5 is in high contrast with large AOD diurnal variation, which suggests the need to use AOD from geostationary satellites for constrain either modeling or analysis of surface PM2.5 for air quality application.

Uncertainty in the emission estimates is one the main reasons for shortcomings in the Chemistry Transport Models (CTMs) which can reduce the confidence level of impact assessment of anthropogenic activities on air quality and climate. This dissertation focuses on understating the uncertainties within the CTMs and reducing these uncertainties by improving emission estimates The first part of this dissertation focuses on reducing the uncertainties around the emission estimates from oil and Natural Gas (NG) operations by using various observations and high-resolution CTMs. To achieve this goal, we used Weather Research and Forecasting with Chemistry (WRF-Chem) model in conjunction with extensive measurements from two major field campaigns in Colorado. Ethane was used as the indicator of oil and NG emissions to explore the sensitivity of ethane to different physical parametrizations and simulation set-ups in the WRF-Chem model using the U.S. EPA National Emission Inventory (NEI-2011). The sensitivity analysis shows up to 57.3% variability in the modeled ethane normalized mean bias (NMB) across the simulations, which highlights the important role of model configurations on the model performance. Comparison between airborne measurements and the sensitivity simulations shows a model-measurement bias of ethane up to -15ppb (NMB of -80%) in regions close to oil and NG activities. Under-prediction of ethane concentration in all sensitivity runs suggests an actual under-estimation of the oil and NG emissions in the NEI-2011 in Colorado. To reduce the error in the emission inventory, we developed a three-dimensional variational inversion technique. Through this method, optimal scaling factors up to 6 for ethane emission rates were calculated. Overall, the inversion method estimated between 11% to 15% higher ethane emission rates in the Denver-Julesburg basin compared to the NEI-201. This method can be extended to constrain oil and NG emissions in other regions in the US using the available measurement datasets. The second part of the dissertation discusses the University of Iowa high-resolution chemical weather forecast framework using WRF-Chem designed for the Lake Michigan Ozone Study (LMOS-2017). LMOS field campaign took place during summer 2017 to address high ozone episodes in coastal communities surrounding Lake Michigan. The model performance for clouds, on-shore flows, and surface and aircraft sampled ozone and NOx concentrations found that the model successfully captured much of the observed synoptic variability of onshore flows. Selection of High-Resolution Rapid Refresh (HRRR) model as initial and boundary condition, and the Noah land surface model, significantly improved comparison of meteorology variables to both ground-based and aircraft data. Model consistently underestimated the daily maximum concentration of ozone. Emission sensitivity analysis suggests that increase in Hydrocarbon (HC). Variational inversion method and measurements by GeoTAS and TROPOMI instruments and airborne and ground-based measurements can be used to constrain NOx emissions in the region.

Vertical mixing is an important process that relates surface fluxes to concentrations of pollutants and other chemical species in the atmosphere. Errors in vertical mixing have been identified as a major source of uncertainties in various atmospheric modeling efforts including tracer transport, weather forecasting, and regional climate simulation. This thesis aims to quantify uncertainties in model-derived mixed layer heights (zi) over North America through direct comparisons between radiosonde observations and four models at different months of the year 2004 through the bulk Richardson number method. Results of this study suggest that considerable errors in zi exist throughout the region with the spatial and temporal variations of the errors differ significantly among the selected models. Over all, errors in zi were larger in global models than in the limited area mesoscale models, and the magnitude of the random error was two times larger than the bias. Notably, spatial regions of with extremely large positive biases correspond to those with especially large random errors. The biases and random errors, however, were not correlated linearly nor can be easily used to predict each other. Uncertainties in model-derived zi were attributed, through errors in the bulk Richardson number, to temperature and horizontal winds. Errors in both horizontal winds and temperatures were found contributing more or less the same to uncertainties in zi, with relative errors in both variables being the greatest in the lowest part of the troposphere. Lastly, independent observations from the cooperative profiler network suggest that data assimilation did not add qualitative advantages for the comparisons presented in this study. The mixed layer height uncertainties demonstrated in this study may provide a guide for selecting a model to simulate regional scale atmospheric transport and for interpreting flux estimation and inversions studies.

Air quality in the Mexico City Metropolitan Area (MCMA) is the subject of many studies due to concerns from high emissions and their adverse effects on public health and the environment. In this study, a high resolution simulation is performed with the Community Multi-scale Air Quality modeling system (CMAQ) using meteorology generated by the Weather Research Forecasting system (WRF). The boundary conditions for CMAQ are provided by the Goddard Earth Observing System-CHEMistry model (GEOS-Chem). The simulation period was March 2-7, 2006. Hourly species concentrations of O3, NOx, CO, SO2, PM10, and PM2.5 for the period were provided by the Automatic Air Quality Monitoring Network (labeled as RAMA). Preliminary evaluation showed GEOS-Chem and CMAQ being in good agreement with their predicted concentrations. In comparison with the base case boundary conditions, the GEOS-Chem case performs better and predicts closer to the observed values of O3, NOx, PM10, PM2.5, and SO2. Particle trajectory analysis was performed using the HYbrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) to ascertain the major sources of SO2 emitters and their impact on the MCMA.

The atmospheric concentration of methane \((CH_4)\) - the most significant non-\(CO_2\) anthropogenic long-lived greenhouse gas - stabilized between 1999 and 2006 and then began to rise again. Explanations for this behavior differ but studies agree that more measurements and better modeling are needed to reliably explain the model-data discrepancies and predict future change. This dissertation focuses on measurements of \(CH_4\) and inverse modeling of atmospheric \(CH_4\) fluxes using field measurements at a variety of spatial scales. We first present a new fast-response instrument to measure the isotopic composition of \(CH_4\) in ambient air. The instrument was used to characterize mass fluxes and isofluxes (a isotopically-weighted mass flux) from a well-studied research fen in New Hampshire. Eddy-covariance and automatic chamber techniques produced consistent estimates of both the \(CH_4\) fluxes and their isotopic composition at sub-hourly resolution. We then characterize fluxes of \(CH_4\) from aircraft engines using measurements made with the same instrument during the Alternative Aviation Fuel Experiment (AAFEX), a study that aimed to determine the atmospheric impacts of alternative fuel use in the growing aviation industry. Emissions of \(CO_2\), \(CH_4\), and \(N_2O\) from different synthetic fuels were statistically indistinguishable from those of the widely used JP-8 jet fuel. We then present airborne observations of the long-lived greenhouse gas suite – \(CO_2\), \(CH_4\), \(N_2O\), and CO – during two aircraft campaigns, HIPPO and CalNex, made using a similar instrument built specifically for the NCAR HIAPER GV aircraft. These measurements are compared to data from other onboard sensors and show excellent agreement. We discuss the details of the end-to-end calibration procedures and the data quality-assurance and quality-control (QA/QC). Lastly, we quantify a top-down estimate of California’s \(CH_4\) emission inventory using the CalNex \(CH_4\) observations. Observed \(CH_4\) enhancements above background concentrations are simulated using a lagrangian transport model driven by validated meteorology. A priori source-specific emission inventories are optimized in a Bayesian inversion framework to show that California’s \(CH_4\) budget is 1.6 ± 0.34 times larger than the current estimate of California’s Air Resources Board (CARB), the body charged with enforcing the California Global Solutions Act and tracking emission changes over time. Findings highlight large underestimates of emissions from cattle and natural gas infrastructure. / Earth and Planetary Sciences