A systematic sectoral empirical orthogonal function (EOF) analysis of Southern Hemisphere (SH) extratropical tropospheric zonal-mean geopotential height (GH) is conducted in order to determine how EOF shapes and shape ordering is affected by a decrease in the width of the sector. Previous work (Kushner and Lee 2007) using surface pressure found that the two lead EOFs exchange shape as the sector width decreases below seventy degrees. In the present work, the 500hPa GH field is found to exhibit a similar feature. By fitting a idealized kinematic model, in the form of a Gaussian error function, to daily 500 hPa GH for each sector, the kinematic features of the shape reordering observed in the lead EOFs is shown to arise from the covariance structure of the fluctuating model parameters. The correlations between model parameters which are shown to influence the EOF shapes are further shown to be strongly influenced by statistical properties of daily mass and angular momentum fluctuations. / Graduate

Due to factors such as spatial discretization and the parameterization of certain processes, the presence of bias in models of the Earth's atmosphere is unavoidable. Whether we are selecting a model to explain past phenomenon, forecast weather patterns, or make inferences about the future, the target of any selection process is to minimize the discrepancies between model output and observations. Some discrepancies have a greater effect on the scatter of model predictions though. We exemplify this in the case of CO2 forced warming using multivariate empirical orthogonal functions (EOF), created using an ensemble of plausible parameter configurations of CAM3.1. When subjecting this ensemble to a doubling of atmospheric CO2, some EOFs exhibit significantly higher correlation than others with the resulting increase in mean global surface temperature. Therefore, there are discernible bias patterns that effect its predictive scatter. By targeting these patterns in the model evaluation process, it is plausible to use this information to constrain the resulting range of predictions. We take a first step towards showing this by creating a metric to evaluate model skill based on these EOFs and their correlation to a model's sensitivity to CO2 forcing. Using model output, for which we know the resulting temperature increase, as a surrogate for observations in this metric, the resulting distribution of skill scores indeed agreement in sensitivity to CO2 forcing. / text

Almost one-half of the annual precipitation in the southwestern United States occurs during the North American monsoon (NAM). Given favorable synoptic-scale conditions, organized monsoon thunderstorms may affect relatively large geographic areas. Through an objective analysis of atmospheric reanalysis and observational data, the dominant synoptic patterns associated with NAM extreme events are determined for the period from 1993 to 2010. Thermodynamically favorable extreme-weather-event days are selected on the basis of atmospheric instability and precipitable water vapor from Tucson, Arizona, rawinsonde data. The atmospheric circulation patterns at 500 hPa associated with the extreme events are objectively characterized using principal component analysis. The first two dominant modes of 500-hPa geopotential-height anomalies of the severe-weather-event days correspond to type-I and type-II severe-weather-event patterns previously subjectively identified by Maddox et al. These patterns reflect a positioning of the monsoon ridge to the north and east or north and west, respectively, from its position in the "Four Corners" region during the period of the climatological maximum of monsoon precipitation from mid-July to mid-August. An hourly radar gauge precipitation product shows evidence of organized, westward-propagating convection in Arizona during the type-I and type-II severe weather events. This new methodological approach for objectively identifying severe weather events may be easily adapted to inform operational forecasting or analysis of gridded climate data.

The main topic of this research is the simulation of internal wave interaction by a two-dimensional numerical model developed by Lynett & Liu (2002) of Cornell University, then modified by Cheng et al. (2005). The governing equation includes two-dimensional momentum and continuity equation. The model uses constant upper and lower layer densities; hence, these factors as well as the upper layer thickness. Should be determined before the simulation. This study discusses the interface depth and the density according to the buoyancy frequency distribution, the EOF, and the eigen-value based on the measured density profile. Besides, a method based on the two-layer KdV equation and the KdV of continuously-stratified fluid. By minimize the difference of linear celeriy, nonlinear and dispersion terms, the upper layer thicknes can also be determined. However, the interface will be much deeper than the depth of max temperature drop in the KdV method if the total water depth is bigger than 500 meters. Thus, the idealization buoyancy frequency formula proposed by Vlasenko et al. (2005) or Xie et al. (2010) are used to modify the buoyancy frequency. The internal wave in the Luzon Strait and the South China Sea are famous and deserves detailed study. We use the KdV method to find the parameters in the two fluid model to speed up the simulation of internal wave phenomena found in the satellite image.

Complexos Convectivos de Mesoescala (CCM) são eventos meteorológicos de difícil previsão, que resultam em tempestades severas e desastres. O objetivo deste trabalho é indicar as características em grande escala do ambiente atmosférico favorável para a formação de CCM no Sul do Brasil, entre 1998 e 2007. Fez-se uso da base de dados de CCM de Durkee e Mote (2009), assim como das variáveis de Potencial de Energia Convectiva Disponível (CAPE), ponto de orvalho, temperatura, altura geopotencial, componentes de vento u e v e umidade relativa da reanálise do National Center for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), coletadas entre 2,5 e 5,5 horas antes do desenvolvimento dos CCM. Com o método de Análise das Componentes Principais (ACP), geraram-se as composições do ambiente atmosférico médio favorável ao desenvolvimento dos CCM, para comparar o grupo dos que ocorreram no Sul do Brasil ao dos que atuaram em outras regiões da AS. Usando como dado de entrada as variáveis de altura geopotencial e temperatura (em 850 hPa), foram encontradas quatro componentes principais para cada um dos grupos de CCM. Com base nas componentes principais, nas variáveis atmosféricas e nas cartas sinóticas, foram reconstruídos os ambientes atmosféricos médios para identificar o comportamento das características atmosféricas prévias aos CCM para cada conjunto de eventos. Os resultados identificaram 303 CCM, 96 no Sul do Brasil, 168 em outras regiões da AS e 39 oceânicos. O ambiente atmosférico médio dos 168 CCM não apresentou características homogêneas, pois 75% das componentes não possuíam jatos de baixos níveis (JBN) dentro dos critérios adotados, mas a presença de um escoamento meridional. Esse fluxo, ao encontrar com a região de divergência dos jatos de altos níveis (JAN), foi um dos fatores favoráveis para a convecção, já que seus valores de CAPE (≥ 450 J kg-1) eram menores que a média esperada para formação de tempestades e só uma das componentes teve frentes frias associadas. Por outro lado, o grupo dos 96 CCM que atuaram no Sul do Brasil mostrou-se cerca de 50.000 km² maior em extensão que os das outras regiões da AS e dos EUA e com duração de pelo menos 3 h a mais. Além disso, as características atmosféricas do grupo de CCM do Sul do Brasil mostraram padrões homogêneos, podendo indicar a formação de CCM nessa região quando: o campo de ventos médios em 850 e 200 hPa, se encontrarem em posição ortogonal, indicando acoplamento entre os jatos de baixos e altos níveis; os valores de CAPE forem ≥ 600 J kg-1 e o cisalhamento vertical estiver entre 7 e 12 m s-1; houver atuação das frentes frias no sul da AS; a umidade relativa disponível estiver concentrada próxima à região Sul do Brasil, com valores maiores que 80%; a altura geopotencial (850 hPa) apresentar um cavado na região gênese dos CCM e a temperatura (850 hPa) estiver mais elevada próxima e ao norte da região de formação. / Mesoscale Convective Complexes (MCCs) are meteorological events difficult to forecast, which result in severe storms and other natural hazards. This study’s objective is to indicate the large-scale atmospheric environment favorable to develop MCCs in Southern Brazil during the 1998–2007 period. The MCCs database used was from Durkee and Mote (2009) and the variables selected include CAPE (Convective Available Potential Energy), dewpoint temperature, temperature, geopotential height, and relative humidity from National Center for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), collected from 2,5 to 5,5 hours before the MCCs’ development. Principal component analysis (PCA) method was used to construct the average atmospheric environments of MCCs group that occurred in Southern Brazil to compare with MCCs that occurred in other regions of South America. Temperature and geopotential height were the variables used for the PCA, resulting in four principal components to each MCCs group. Based on these principal components, meteorological variables and synoptic charts, average atmospheric environments were built to understand the atmospheric parameters that indicate the development of MCCs in each group. Results show 303 MMCs, 96 were located in Southern Brazil, 168 in South America and 39 in the South Atlantic Ocean. The average atmospheric environment from the group of 168 MCCs did not indicate homogeneous characteristics, as 75% of its principal components cannot be characterized as having a low-level jet (LLJ) in the wind field, instead only a meridional flux of humid and warm air at 850 hPa. This air coupled with the upperlevel jet (ULJ) was found to be responsible for convection developing MCCs, as CAPE (≥ 450 J kg-1) was below the average to produce storms and only one component was associated with a cold front. On the other hand, the MCCs’ group of Southern Brazil is on the order of 50.000 km² larger and 3 hours longer than MCCs from other regions of South America and from the United States. Furthermore, the atmospheric characteristics of the Southern Brazil MCCs’ group revealed homogenous patterns, which suggest that the development of MCCs in this region starts when: the mean wind field indicate a coupled LLJ (jet streak between 10 and 12 m s-1) and ULJ (jet streak ≥ 32 m s-1), CAPE value is ≥ 600 J kg-1 and the vertical wind shear is from 7 to 12 m s-1, cold fronts are active in Southern South America, the relative humidity is concentrated in Southern Brazil and above 80%, the geopotential height (850 hPa) indicate a trough in the genesis region of MCCs and the temperature (850 hPa) is higher near and northern the genesis region.

Complexos Convectivos de Mesoescala (CCM) são eventos meteorológicos de difícil previsão, que resultam em tempestades severas e desastres. O objetivo deste trabalho é indicar as características em grande escala do ambiente atmosférico favorável para a formação de CCM no Sul do Brasil, entre 1998 e 2007. Fez-se uso da base de dados de CCM de Durkee e Mote (2009), assim como das variáveis de Potencial de Energia Convectiva Disponível (CAPE), ponto de orvalho, temperatura, altura geopotencial, componentes de vento u e v e umidade relativa da reanálise do National Center for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), coletadas entre 2,5 e 5,5 horas antes do desenvolvimento dos CCM. Com o método de Análise das Componentes Principais (ACP), geraram-se as composições do ambiente atmosférico médio favorável ao desenvolvimento dos CCM, para comparar o grupo dos que ocorreram no Sul do Brasil ao dos que atuaram em outras regiões da AS. Usando como dado de entrada as variáveis de altura geopotencial e temperatura (em 850 hPa), foram encontradas quatro componentes principais para cada um dos grupos de CCM. Com base nas componentes principais, nas variáveis atmosféricas e nas cartas sinóticas, foram reconstruídos os ambientes atmosféricos médios para identificar o comportamento das características atmosféricas prévias aos CCM para cada conjunto de eventos. Os resultados identificaram 303 CCM, 96 no Sul do Brasil, 168 em outras regiões da AS e 39 oceânicos. O ambiente atmosférico médio dos 168 CCM não apresentou características homogêneas, pois 75% das componentes não possuíam jatos de baixos níveis (JBN) dentro dos critérios adotados, mas a presença de um escoamento meridional. Esse fluxo, ao encontrar com a região de divergência dos jatos de altos níveis (JAN), foi um dos fatores favoráveis para a convecção, já que seus valores de CAPE (≥ 450 J kg-1) eram menores que a média esperada para formação de tempestades e só uma das componentes teve frentes frias associadas. Por outro lado, o grupo dos 96 CCM que atuaram no Sul do Brasil mostrou-se cerca de 50.000 km² maior em extensão que os das outras regiões da AS e dos EUA e com duração de pelo menos 3 h a mais. Além disso, as características atmosféricas do grupo de CCM do Sul do Brasil mostraram padrões homogêneos, podendo indicar a formação de CCM nessa região quando: o campo de ventos médios em 850 e 200 hPa, se encontrarem em posição ortogonal, indicando acoplamento entre os jatos de baixos e altos níveis; os valores de CAPE forem ≥ 600 J kg-1 e o cisalhamento vertical estiver entre 7 e 12 m s-1; houver atuação das frentes frias no sul da AS; a umidade relativa disponível estiver concentrada próxima à região Sul do Brasil, com valores maiores que 80%; a altura geopotencial (850 hPa) apresentar um cavado na região gênese dos CCM e a temperatura (850 hPa) estiver mais elevada próxima e ao norte da região de formação. / Mesoscale Convective Complexes (MCCs) are meteorological events difficult to forecast, which result in severe storms and other natural hazards. This study’s objective is to indicate the large-scale atmospheric environment favorable to develop MCCs in Southern Brazil during the 1998–2007 period. The MCCs database used was from Durkee and Mote (2009) and the variables selected include CAPE (Convective Available Potential Energy), dewpoint temperature, temperature, geopotential height, and relative humidity from National Center for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), collected from 2,5 to 5,5 hours before the MCCs’ development. Principal component analysis (PCA) method was used to construct the average atmospheric environments of MCCs group that occurred in Southern Brazil to compare with MCCs that occurred in other regions of South America. Temperature and geopotential height were the variables used for the PCA, resulting in four principal components to each MCCs group. Based on these principal components, meteorological variables and synoptic charts, average atmospheric environments were built to understand the atmospheric parameters that indicate the development of MCCs in each group. Results show 303 MMCs, 96 were located in Southern Brazil, 168 in South America and 39 in the South Atlantic Ocean. The average atmospheric environment from the group of 168 MCCs did not indicate homogeneous characteristics, as 75% of its principal components cannot be characterized as having a low-level jet (LLJ) in the wind field, instead only a meridional flux of humid and warm air at 850 hPa. This air coupled with the upperlevel jet (ULJ) was found to be responsible for convection developing MCCs, as CAPE (≥ 450 J kg-1) was below the average to produce storms and only one component was associated with a cold front. On the other hand, the MCCs’ group of Southern Brazil is on the order of 50.000 km² larger and 3 hours longer than MCCs from other regions of South America and from the United States. Furthermore, the atmospheric characteristics of the Southern Brazil MCCs’ group revealed homogenous patterns, which suggest that the development of MCCs in this region starts when: the mean wind field indicate a coupled LLJ (jet streak between 10 and 12 m s-1) and ULJ (jet streak ≥ 32 m s-1), CAPE value is ≥ 600 J kg-1 and the vertical wind shear is from 7 to 12 m s-1, cold fronts are active in Southern South America, the relative humidity is concentrated in Southern Brazil and above 80%, the geopotential height (850 hPa) indicate a trough in the genesis region of MCCs and the temperature (850 hPa) is higher near and northern the genesis region.

Complexos Convectivos de Mesoescala (CCM) são eventos meteorológicos de difícil previsão, que resultam em tempestades severas e desastres. O objetivo deste trabalho é indicar as características em grande escala do ambiente atmosférico favorável para a formação de CCM no Sul do Brasil, entre 1998 e 2007. Fez-se uso da base de dados de CCM de Durkee e Mote (2009), assim como das variáveis de Potencial de Energia Convectiva Disponível (CAPE), ponto de orvalho, temperatura, altura geopotencial, componentes de vento u e v e umidade relativa da reanálise do National Center for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), coletadas entre 2,5 e 5,5 horas antes do desenvolvimento dos CCM. Com o método de Análise das Componentes Principais (ACP), geraram-se as composições do ambiente atmosférico médio favorável ao desenvolvimento dos CCM, para comparar o grupo dos que ocorreram no Sul do Brasil ao dos que atuaram em outras regiões da AS. Usando como dado de entrada as variáveis de altura geopotencial e temperatura (em 850 hPa), foram encontradas quatro componentes principais para cada um dos grupos de CCM. Com base nas componentes principais, nas variáveis atmosféricas e nas cartas sinóticas, foram reconstruídos os ambientes atmosféricos médios para identificar o comportamento das características atmosféricas prévias aos CCM para cada conjunto de eventos. Os resultados identificaram 303 CCM, 96 no Sul do Brasil, 168 em outras regiões da AS e 39 oceânicos. O ambiente atmosférico médio dos 168 CCM não apresentou características homogêneas, pois 75% das componentes não possuíam jatos de baixos níveis (JBN) dentro dos critérios adotados, mas a presença de um escoamento meridional. Esse fluxo, ao encontrar com a região de divergência dos jatos de altos níveis (JAN), foi um dos fatores favoráveis para a convecção, já que seus valores de CAPE (≥ 450 J kg-1) eram menores que a média esperada para formação de tempestades e só uma das componentes teve frentes frias associadas. Por outro lado, o grupo dos 96 CCM que atuaram no Sul do Brasil mostrou-se cerca de 50.000 km² maior em extensão que os das outras regiões da AS e dos EUA e com duração de pelo menos 3 h a mais. Além disso, as características atmosféricas do grupo de CCM do Sul do Brasil mostraram padrões homogêneos, podendo indicar a formação de CCM nessa região quando: o campo de ventos médios em 850 e 200 hPa, se encontrarem em posição ortogonal, indicando acoplamento entre os jatos de baixos e altos níveis; os valores de CAPE forem ≥ 600 J kg-1 e o cisalhamento vertical estiver entre 7 e 12 m s-1; houver atuação das frentes frias no sul da AS; a umidade relativa disponível estiver concentrada próxima à região Sul do Brasil, com valores maiores que 80%; a altura geopotencial (850 hPa) apresentar um cavado na região gênese dos CCM e a temperatura (850 hPa) estiver mais elevada próxima e ao norte da região de formação. / Mesoscale Convective Complexes (MCCs) are meteorological events difficult to forecast, which result in severe storms and other natural hazards. This study’s objective is to indicate the large-scale atmospheric environment favorable to develop MCCs in Southern Brazil during the 1998–2007 period. The MCCs database used was from Durkee and Mote (2009) and the variables selected include CAPE (Convective Available Potential Energy), dewpoint temperature, temperature, geopotential height, and relative humidity from National Center for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), collected from 2,5 to 5,5 hours before the MCCs’ development. Principal component analysis (PCA) method was used to construct the average atmospheric environments of MCCs group that occurred in Southern Brazil to compare with MCCs that occurred in other regions of South America. Temperature and geopotential height were the variables used for the PCA, resulting in four principal components to each MCCs group. Based on these principal components, meteorological variables and synoptic charts, average atmospheric environments were built to understand the atmospheric parameters that indicate the development of MCCs in each group. Results show 303 MMCs, 96 were located in Southern Brazil, 168 in South America and 39 in the South Atlantic Ocean. The average atmospheric environment from the group of 168 MCCs did not indicate homogeneous characteristics, as 75% of its principal components cannot be characterized as having a low-level jet (LLJ) in the wind field, instead only a meridional flux of humid and warm air at 850 hPa. This air coupled with the upperlevel jet (ULJ) was found to be responsible for convection developing MCCs, as CAPE (≥ 450 J kg-1) was below the average to produce storms and only one component was associated with a cold front. On the other hand, the MCCs’ group of Southern Brazil is on the order of 50.000 km² larger and 3 hours longer than MCCs from other regions of South America and from the United States. Furthermore, the atmospheric characteristics of the Southern Brazil MCCs’ group revealed homogenous patterns, which suggest that the development of MCCs in this region starts when: the mean wind field indicate a coupled LLJ (jet streak between 10 and 12 m s-1) and ULJ (jet streak ≥ 32 m s-1), CAPE value is ≥ 600 J kg-1 and the vertical wind shear is from 7 to 12 m s-1, cold fronts are active in Southern South America, the relative humidity is concentrated in Southern Brazil and above 80%, the geopotential height (850 hPa) indicate a trough in the genesis region of MCCs and the temperature (850 hPa) is higher near and northern the genesis region.

Ocean wind waves represent the atmosphere-ocean boundary, playing a central role in the air-sea exchanging processes. Heat, mass and momentum are transferred across this boundary, with waves mediating the exchange of principally the momentum between the winds and the ocean surface. During the generation process waves are called wind sea. When they leave their generation area or outrun their generating wind they are called swell. The wave field can be said to be dominated either by wind sea or swell. Depending on the wave regime the momentum and energy exchanging processes and the degree of coupling between the waves and the wind is different. During the growing process, waves act as a drag on the surface wind and the momentum flux is directed downward. When swell dominates the wave field a reverse momentum flux mechanism occurs triggered by swell waves traveling considerably faster than the surface winds. The momentum transfer is now directed from the waves to the atmosphere, and takes place because swell waves perform work on the atmosphere as part of their attenuation process. This upward momentum transfer has an impact on the lower atmosphere dynamics, and on the overall turbulence structure of the boundary layer. A detailed qualitative climatology of the global wind sea and swell fields from wave reanalysis data, is presented, revealing a very strong swell dominance of the World Ocean. The areas of larger potential impact of swell on the atmosphere, from a climatological point of view, are also studied. A model that reproduces the swell impact on the lower atmosphere dynamics, conceptually based on the energy transfer from the waves to the atmosphere, is presented – a  new parameterization for the wave-induced stress is also proposed. The model results are compared with field observations. A modeling simulation, using a coupled wave-atmosphere model system, is used to study the impact of swell in a regional climate model, by using different formulations on how to introduce the wave state effect in the modeling system. / Gränsen mellan hav och atmosfär beskrivs av vågor, dessa spelar en central roll i utbytesprocesser mellan hav och atmosfär. Värme, massa och rörelsemängd överförs vid ytan och utbytet av rörelsemängd mellan vind och havsyta styrs i stor utsträckning av vågorna. Då vågor skapas kallas de för vinddrivna vågor. När vågorna sedan lämnar området där de genererats eller rör sig fortare än den vind som genererat dem kallas de dyning. Ett vågfält kan sägas vara dominerat av antingen vinddrivna vågor eller dyningsvågor. Beroende på vilken vågregim som råder så är kopplingen mellan vågor och vind olika och därmed också utbytesprocesserna för rörelsemängd och energi. Då vågorna genereras fungerar de som en bromsande kraft för vinden och impulsutbytet är nedåtriktat. När dyning dominerar vågfältet inträffar en mekanism för omvänt impulsutbyte som sätts igång av dyningsvågor som färdas avsevärt snabbare än vinden. Rörelsemängd överförs då från vågorna till atmosfären, eftersom dyningsvågorna utför arbete på atmosfären då de dämpas. Den uppåtriktade transporten av rörelsemängd har en stor effekt på dynamiken och turbulensstrukturen i lägre delen av atmosfären. En detaljerad kvalitativ klimatologi av globala vågfält (vinddrivna och dyning) från återanalysdata presenteras och visar att dyning dominerar vågfältet på världshaven. Områden där man kan förvänta sig störst effekt av dyning på atmosfären har identifierats. En konceptuellt baserad modell som reproducerar effekten av dyning på dynamiken i lägre delen av atmosfären presenteras. Modellen styrs av överföring av energi från vågor till atmosfären. I modellen föreslås även en ny parameterisering för våginducerad kraft på havsytan. Modellresultaten är utvärderade mot fältmätningar. En regional klimatmodell, med ett kopplat våg-atmosfärssystem, har använts för att studera den långtida effekten av dyning vid klimatsimulering. Olika formuleringar för beskrivningen av vågornas effekt på atmosfären har använts, beroende på om vinddrivna vågor eller dyning dominerar vågfältet.

This thesis addresses spatial interpolation and temporal prediction using air pollution data by several space-time modelling approaches. Firstly, we implement the dynamic linear modelling (DLM) approach in spatial interpolation and find various potential problems with that approach. We develop software to implement our approach. Secondly, we implement a Bayesian spatial prediction (BSP) approach to model spatio-temporal ground-level ozone fields and compare the accuracy of that approach with that of the DLM. Thirdly, we develop a Bayesian version empirical orthogonal function (EOF) method to incorporate the uncertainties due to temporally varying spatial process, and the spatial variations at broad- and fine- scale. Finally, we extend the BSP into the DLM framework to develop a unified Bayesian spatio-temporal model for univariate and multivariate responses. The result generalizes a number of current approaches in this field.

This thesis addresses spatial interpolation and temporal prediction using air pollution data by several space-time modelling approaches. Firstly, we implement the dynamic linear modelling (DLM) approach in spatial interpolation and find various potential problems with that approach. We develop software to implement our approach. Secondly, we implement a Bayesian spatial prediction (BSP) approach to model spatio-temporal ground-level ozone fields and compare the accuracy of that approach with that of the DLM. Thirdly, we develop a Bayesian version empirical orthogonal function (EOF) method to incorporate the uncertainties due to temporally varying spatial process, and the spatial variations at broad- and fine- scale. Finally, we extend the BSP into the DLM framework to develop a unified Bayesian spatio-temporal model for univariate and multivariate responses. The result generalizes a number of current approaches in this field.