Vertical simulations of ozone were made using a TAPM (The Air Pollution Model) at the Linyuan site in Kaohsiung County, southern Taiwan. Ozone was simulated at altitudes of 0, 100, 300, 500 and 1000 m from November 23 to 25 in 2005 and March 21 to 23 in 2006. The surface ozone concentrations that were predicted using TAPM were high (33.7−119 ppbv) in the daytime (10:00−16:00) and were low (10−40 ppbv) at other times, which predictions were consistent with the observations. The simulated surface ozone concentrations reveal that costal lands typically had higher ozone concentrations than those inland, because most industrial parks are located in or close to the boundaries of Kaohsiung City. Both measurements and simulations indicate that daytime ozone concentrations decreased quickly with increasing height at altitudes below 300 m; while nighttime ozone concentrations were lower at low altitudes (50 to 300 m) than at higher altitudes, partly because of dry deposition and titration of surface ozone by the near-surface nitrogen oxides (NOx) and partly because of the existence of the residual layer above the stable nocturnal boundary layer. The simulations show a good correlation between the maximum daytime surface ozone concentration and average nighttime ozone concentration above the nocturnal boundary layer.

Karst landscapes cover approximately 20% of the ice-free land area worldwide. The soluble nature of the bedrock within a karst landscape allows for the formation of caverns, joints, fissures, sinkholes, and underground streams, which affect the hydrological behavior of the region. Currently, the Noah Land-Surface Model (Noah- LSM), coupled with the Weather Research and Forecasting (WRF) model, does not provide a representation of the physical behavior of a karst terrain. Previous research has attempted to model karst behavior through soil moisture and land cover/land use changes to determine the influence this unique landscape may have on atmospheric phenomenon. This highlights the need to study the potential influence that karst landscapes may have on model simulations. For this study, several factors were taken into account while studying karst and meteorology: the verification of a current operational forecasting model against observational data over five years (2007 to 2011), the formation of a karstlike soil type for use within an operational forecasting model, and model behavior once this karst-like soil type was added to the operational forecasting model. The verification of a currently operational forecasting model, the North American Mesoscale (NAM), indicated that, overall, the karst regions may exhibit an influence on local winds (greater error) and precipitation (frequency and forecasting). When developing a realistic karst-like soil proxy for use in the Noah-LSM, hydraulic conductivity values show a variation ranging from around 10-7 and 10-5 m s-1 for the karst bedrock within Tennessee and Kentucky. Sandy loam and clay soils were used, along with bedrock parameters, to determine an average soil parameter type for the epikarst bedrock located within this region. The model study demonstrated that the addition of karst highlighted the potential influence on precipitation distribution and energy fluxes, through RMSD and R2 values taken at a 95% confidence interval.

FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / This paper analyzes the mesoscale model WRF (Weather Research And Forecast) to verify its reliability in use as a research tool in areas with potential for eolioeletric generation. The area chosen for study was a farm located in Maracanaà in the state of CearÃ. On the farm was installed an anemometer tower of 80 meters high with three anemometers, 1 windsock, 1 temperature sensor and a pyranometer, all sensors connected to a datalogger. The data collected in this tower were used for comparison with the data obtained through simulations in WRF. In the simulations the model was evaluated for two different climatic conditions in the region, the rainy and the dry seasons. The periods chosen to perform the simulations are: March/2012 (representing the rainy season) and November/2011 (representing the dry season). Was performed five sensitivity tests, which were exchanged in the parameterizations of the Planetary Boundary Layer (PBL), Surface Layer (CS) and Ground Surface Model (GSM). The simulation results were evaluated according to the Pearson's correlation method, that one has parameter values from -1 to 1 which presents an index of correlations ranging from bad (-1) to great (1). The simulation with the best performance in the dry and rainy periods presented values for correlations of 0.76 and 0.58, respectively, considered good and fair to the Pearson's parameters. The model was able to satisfactorily represent the local wind behavior for the dry season of the year, and more research is needed in the area to analyze how the model behaves in the representation of the rainy season. Thus, this model provides satisfactory results to be used as a tool for evaluate areas with potential for eolioeletric generation, more research is needed to fit better. / O presente trabalho analisa o modelo de mesoescala WRF (Weather Research and Forecast) para verificar a sua confiabilidade na utilizaÃÃo como ferramenta de investigaÃÃo de Ãreas com potencial para geraÃÃo eolioelÃtrica. A regiÃo escolhida para estudo foi uma fazenda localizada no municÃpio de MaracanaÃ, no estado do CearÃ. Na fazenda foi instalada uma torre anemomÃtrica de 80 metros de altura com 3 anemÃmetros, 1 biruta, 1 sensor de temperatura e um piranÃmetro, todos os sensores conectados a um datalogger. Os dados coletados nesta torre foram utilizados para comparaÃÃo com os dados obtidos atravÃs das simulaÃÃes no WRF. Nas simulaÃÃes o modelo foi avaliado para duas situaÃÃes climatolÃgicas distintas na regiÃo, o perÃodo chuvoso e o seco. Os perÃodos escolhidos para realizar as simulaÃÃes sÃo: marÃo/2012 (representando o perÃodo chuvoso) e novembro/2011 (representando o perÃodo seco). Foram realizados cinco testes de sensibilidade, nos quais foram permutadas as parametrizaÃÃes da Camada Limite PlanetÃria (CLP), Camada de SuperfÃcie (CS) e o Modelo de Solo SuperfÃcie (MSS). Os resultados das simulaÃÃes foram avaliados segundo o mÃtodo de correlaÃÃo de Pearson, mÃtodo este que possui parÃmetros de valores de -1 a 1 onde apresenta um indicativo de correlaÃÃes que vÃo de pÃssimas (-1) a Ãtimas (1). A simulaÃÃo com o melhor desempenho no perÃodo seco e chuvoso apresentaram valores de correlaÃÃes de 0,76 e 0,58, consideradas forte e moderada, para os parÃmetros de Pearson, respectivamente. O modelo conseguiu representar de forma satisfatÃria o regime de vento local para a estaÃÃo seca do ano, sendo necessÃrias mais pesquisas na Ãrea para analisar como o modelo se comporta na representaÃÃo do perÃodo chuvoso. Assim este modelo apresenta resultados satisfatÃrios para ser utilizado como ferramenta para avaliaÃÃo de regiÃes com potencial em geraÃÃo eolioelÃtrica, sendo necessÃrias mais pesquisas para ajustÃ-lo melhor.

The impacts of transported and locally-produced pollutants on western US air quality during summer 2008 are studied using the multi-scale Sulfur Transport and Deposition Modeling system. Transported background (TBG) is an indicator of the influences from extra-regional emissions or the lower stratosphere. The magnitude of TBG is expected to increase as the emissions from international sources grow. This trend is especially important in the context of US air quality standards, which tend to become more stringent to protect human health and ecosystems. Forward sensitivity simulations in which the model boundary conditions and emissions are perturbed show that TBG strongly and extensively affect western US surface ozone (more than half of the total), compared to other contributors to background ozone (North American, NA, biomass burning, BB and biogenic emissions), and the impacts differ among various geographical regions and land types. The stratospheric ozone impacts are weak. The TBG ozone contributes most to western US ozone among all TBG species, and TBG peroxyacetyl nitrate is the most important species among ozone precursors. Compared to monthly mean 8-hour daily maximum ozone, the secondary standard metric "W126 monthly index" shows larger responses to TBG perturbations and stronger non-linearity to the size of perturbations. Overall the model-estimated TBG impacts negatively correlate to the vertical resolution and positively correlate to the horizontal resolution. The estimated TBG impacts weakly depend on the magnitude of uncertainties in the US anthropogenic emissions. The transport/subsidence processes that link airmasses aloft with the surface pollution level are analyzed by trajectories, time-lag correlation and adjoint sensitivity analyses. Various types of observations are used to identify source regions and transport processes, and to improve model prediction using the four-dimensional variational data assimilation during a long-range transport episode. The sectoral and geographical contributions to summertime US black carbon (BC) distributions are studied. NA emissions heavily (>70%) affect the BC levels from the surface to 5 km, while non-NA plumes compose more than half of the BC above 5 km. NA and non-NA BB, NA transportation and non-NA residential emissions are the major contributing sectors. Aircraft measurements during the California phase of the Arctic Research of the Composition of the Troposphere from Aircraft andSatellites (ARCTAS-CARB) field campaign show that BC/(organic matter + nitrate + sulfate) mass ratios fairly well represent BC's warming potential over southern California, which can be approximated by BC/(organic matter + sulfate) and BC/sulfate for plumes affected and unaffected by fires, respectively. The responses of BC/(organic matter + sulfate) and BC/sulfate to removing each emission sector indicate that mitigating NA transportation emissions has the highest potential for regional air quality and climate co-benefits. Contributions from NA BB and extra-regional emissions differ for summer and spring (April 2008).

The work presented in this dissertation informs on river network modeling at large scales using geographic information systems, parallel computing and the latest advancements of atmospheric and land surface modeling. This work is motivated by the availability of a vector-based Geographic Information System dataset that describes the networks of streams and rivers in the United States, and how they are connected. A land surface model called Noah-distributed is used to provide lateral inflow to an NHDPlus river network in the Guadalupe River Basin in Texas. Challenges related to the projection of gridded hydrographic data from a coordinate system to another are investigated. The different representations of the shape of the Earth used in atmospheric science (spherical) and hydrology (spheroidal) can lead to a significant North-South shift on the order of 20 km at mid latitudes. A river network model called RAPID is developed and applied in a four-year study of the Guadalupe and San Antonio River Basins in Texas using the river network of NHDPlus. Gage measurements are used to estimate flow wave celerities in a river network and to assess the quality of RAPID flow computations. The performance of RAPID in a massively-parallel computing environment is tested and further investigation of its scalability is needed before using RAPID at the state or federal level. The replacement by RAPID of the river routing scheme used in SIM-France -- a hydro-meteorological model -- is investigated in a ten-year study of river flow in France. While the formulation of RAPID improves the functionality of SIM-France, the flow simulations are comparable in accuracy to those previously obtained by SIM-France. Sub-basin parameterization was found to improve model results. A single criterion for quantifying the quality of river flow simulations using several river gages globally in a river network is developed that normalizes the square error of modeled flow to allow equal treatment of all gaging stations regardless of the magnitude of flow. The use of this criterion as the cost function for parameter estimation in RAPID allows better results than by increasing the degree of spatial variability in model parameters. / text

Knowledge of NOx (NO2 + NO) emissions is useful to understand processes affecting air quality and climate change. Emission inventories of surface NOx have high uncertainties. Satellite remote sensing has enabled measurements of trace gases in the atmosphere over a large regional and temporal scale. Inverse modeling of NO2 observations from satellites can be used to improve existing emissions inventories. This study seeks to understand the difference in two methods of inverse modeling: the mass balance approach and the adjoint approach using the GEOS-Chem chemical transport model and its adjoint. Using both synthetic satellite observations and those derived from the SCIAMACHY satellite instrument, this paper found that the performance of these two inversions was affected by pixel smearing and observational error. Smearing reduced the accuracy of the mass balance approach, while high observational error reduced the accuracy of the adjoint approach. However, both approaches improved the a priori emissions estimate.

Submitted by Lucienne Costa (lucienneferreira@ufcg.edu.br) on 2018-08-13T16:48:52Z No. of bitstreams: 1 THAÍS REGINA BENEVIDES TRIGUEIRO ARANHA – DISSERTAÇÃO (PPGMET) 2016.pdf: 1566781 bytes, checksum: 416f76ec2bd82ddca22b8e30392097f9 (MD5) / Made available in DSpace on 2018-08-13T16:48:52Z (GMT). No. of bitstreams: 1 THAÍS REGINA BENEVIDES TRIGUEIRO ARANHA – DISSERTAÇÃO (PPGMET) 2016.pdf: 1566781 bytes, checksum: 416f76ec2bd82ddca22b8e30392097f9 (MD5) Previous issue date: 2016-03-04 / CNPq / Neste estudo utilizou-se o esquema TEB - Town Energy Budget acoplado ao modelo numérico BRAMS - Brazilian Developments on the Regional Atmospheric Modeling System para analisar as variáveis atmosféricas influenciadas pela urbanização da cidade de Campina Grande - PB no período seco. Esta região, no que diz respeito ao contexto econômico-político, embora seja compreendida como uma cidade média apresenta indicadores semelhantes aos que caracterizam as metrópoles. Foram realizados dois experimentos, um com o TEB ativado para a representação das superfícies urbanizadas e outro com o TEB desativado, denominado de STEB, em que desconsidera a dinâmica urbana, para atestar a influência da cidade nas variáveis meteorológicas. Os resultados mostraram que a cidade de Campina Grande é grande o suficiente para influenciar o próprio microclima. A urbanização aumenta a temperatura durante a tarde e início da noite. O albedo da superfície é fortemente influenciado pela dinâmica da cidade, com impacto no saldo de radiação. O fluxo de calor sensível aumenta e o de calor latente diminui devido ao efeito da cidade. Observa-se algum impacto na temperatura, umidade e fluxos nos arredores da cidade. / In this study we used the TEB scheme - Town Energy Budget coupled to the numerical model BRAMS - Brazilian Developments on the Regional Atmospheric Modeling System to analyze atmospheric variables influenced by the urbanization of the city of Campina Grande - PB in the dry season. This city presents indicators similar to those that characterize the metropolis in economic and political context, although it is considered as an average city. Two experiments were conducted, one with the TEB activated for the representation of urban surfaces and other with the TEB disabled, namely STEB, which disregards the urban dynamics, in order to attest to the influence of the city in weather variables. The results showed the city of Campina Grande is large enough to influence its own microclimate. Urbanization increases the temperature during the afternoon and early evening. The surface albedo is strongly influenced by the dynamics of the city, with impact on the radiation balance. The sensible heat flux increases and the latent heat decreases due to the effect of the city. We also observed an impact on temperature, humidity and flows around the city.

Title: Atmospheric Rendering Author: Mgr. Lukáš Hošek Department: Department of Software and Computer Science Education Supervisor: doc. Dr. Alexander Wilkie, Department of Software and Computer Sci- ence Education Abstract: The sky is an important feature of all outdoor scenes. This thesis explores the topic of skydome models - an approach to getting the sky and atmospheric effects integrated into a renderer. We discuss the physics of atmospheric scattering and de- scribe in detail the construction of a first-principles path tracer atmospheric simulator implementation. The presented path tracer is fully spectral and produces polarization data. Finally, we present two different analytic skydome models. These analytic mod- els are highly practical because they can be integrated even into real-time renderers and provide an excellent combination of fidelity and low computational cost. The first model is a simpler version, providing just the skydome spectral radiance. The second model also provides polarization data, after-sunset skies with an accurate modeling of Earth's shadow, aerial perspective and full sphere data. Keywords: computer graphics, rendering, skylight models, atmospheric modeling

Ce travail de thèse propose de nouveaux concepts et outils pour des activités de simulation stochastique du temps ciblant les besoins spécifiques de l'hydrologie. Nous avons utilisé une zone climatique contrastée dans le sud-est de la France, les Cévennes-Vivarais, qui est très attractive pour les aléas hydrologiques et les changements climatiques.Notre point de vue est que les caractéristiques physiques (humidité du sol, débit) liées aux préoccupations quotidiennes sont directement liées à la variabilité atmosphérique à l'échelle des bassins. Pour la modélisation de multi-variable, la covariabilité avec les précipitations est d'abord considérée.La première étape du thèse est dédiée à la prise en compte de l'hétérogénéité de la précipitation au sein du simulateur de pluie SAMPO [Leblois et Creutin, 2013]. Nous regroupons les pas de temps dans les types de pluie qui sont organisés dans le temps. Deux approches sont testées pour la simulation: un modèle semi-markovienne et un modèle de ré-échantillonnage pour la séquence des types de pluie historiques. Grâce au regroupement, toutes sortes de précipitations sont desservies par un type de pluie spécifique. Dans une zone plus vaste, où l'hypothèse d'homogénéité climatique n'est plus valide, une coordination doit être introduite entre les séquences de types de pluie sur les sous-zones délimitées, en formant à plus grande échelle.Nous avons d'abord étudié une coordination de modèle de Markov, en appliquant des durées de séjour observées par un algorithme glouton. Cet approche respecte les accumulations de longue durée et la variabilité interannuelle, mais les valeurs extrêmes de précipitation sont trop faibles. En revanche, le ré-échantillonnage est plus facile à mettre en œuvre et donne un comportement satisfaisant pour la variabilité à court terme. Cependant, il manque une variabilité inter-annuelle. Les deux accès souffrent de la délimitation stricte des zones homogènes et des types de précipitations homogènes.Pour ces raisons, une approche complètement différente est également envisagée, où les pluies totales sont modélisées conjointement en utilisant la copule, puis désagrégés sur la petite échelle en utilisant une simulation conditionnelle géostatistique.Enfin, la technique de la copule est utilisée pour relier les autres variables météorologiques (température, rayonnement solaire, humidité, vitesse du vent) aux précipitations. Puisque la modélisation multivariée vise à être pilotée par la simulation des précipitations, la copule doit être exécutée en mode conditionnel. La boîte à outils réalisée a déjà été utilisée dans des explorations scientifiques, elle est maintenant disponible pour tester aux applications réelles. En tant qu'approche pilotée par les données, elle est également adaptable à d'autres conditions climatiques. / This PhD work proposes new concepts and tools for stochastic weather simulation activities targeting the specific needs of hydrology. We used, as a demonstration, a climatically contrasted area in the South-East of France, Cévennes-Vivarais, which is highly attractive to hydrological hazards and climate change.Our perspective is that physical features (soil moisture, discharge) relevant to everyday concerns (water resources assessment and/or hydrological hazard) are directly linked to the atmospheric variability at the basins scale, meaning firstly that relevant time and space scales ranges must be respected in the rainfall simulation technique. Since hydrological purposes are the target, other near-surface variates must be also considered. They may exhibit a less striking variability, but it does exist. To build the multi-variable modeling, co-variability with rainfall is first considered.The first step of the PhD work is dedicated to take into account the heterogeneity of the precipitation within the rainfall simulator SAMPO [Leblois and Creutin, 2013]. We cluster time steps into rainfall types organized in time. Two approaches are tested for simulation: a semi-Markov simulation and a resampling of the historical rainfall types sequence. Thanks to clustering, all kind of rainfall is served by some specific rainfall type. In a larger area, where the assumption of climatic homogeneity is not considered valid, a coordination must be introduced between the rainfall type sequences over delineated sub-areas, forming rainy patterns at the larger scale.We first investigated a coordination of Markov models, enforcing observed lengths-of-stay by a greedy algorithm. This approach respects long duration aggregates and inter-annual variability, but the high values of rainfall are too low. As contrast, the joint resampling of historically observed sequences is easier to implement and gives a satisfactory behavior for short term variability. However it lacks inter-annual variability.Both approaches suffer from the strict delineation of homogeneous zones and homogeneous rainfall types.For these reasons, a completely different approach is also considered, where the areal rainfall totals are jointly modeled using a spatio-temporal copula approach, then disaggregated to the user grid using a non-deterministic, geostatistically-based conditional simulation technique. In the copula approach, the well-known problem of rainfall having atom at zero is handled in replacing historical rainfall by an appropriated atmospheric based rainfall index having a continuous distribution. Simulated values of this index can be turned to rainfall by quantile-quantile mapping.Finally, the copula technique is used to link other meteorological variables (i.e. temperature, solar radiation, humidity, wind speed) to rainfall. Since the multivariate simulation aims to be driven by the rainfall simulation, the copula needs to be run in conditional mode. The achieved toolbox has already been used in scientific explorations, it is now available for testing in real-size application. As a data-driven approach, it is also adaptable to other climatic conditions. The presence of atmospheric precursors a large scale values in some key steps may enable the simulation tools to be converted into a climate simulation disaggregation.

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