The North American monsoon (NAM) is the principal driver of summer severe weather in the Southwest U.S. With sufficient atmospheric instability and moisture, monsoon convection initiates during daytime in the mountains and later may organize, principally into mesoscale convective systems (MCSs). Most monsoon-related severe weather occurs in association with organized convection, including microbursts, dust storms, flash flooding and lightning. The overarching theme of this dissertation research is to investigate simulation of monsoon severe weather due to organized convection within the use of regional atmospheric modeling. A commonly used cumulus parameterization scheme has been modified to better account for dynamic pressure effects, resulting in an improved representation of a simulated MCS during the North American monsoon experiment and the climatology of warm season precipitation in a long-term regional climate model simulation. The effect of urbanization on organized convection occurring in Phoenix is evaluated in model sensitivity experiments using an urban canopy model (UCM) and urban land cover compared to pre-settlement natural desert land cover. The presence of vegetation and irrigation makes Phoenix a "heat sink" in comparison to its surrounding desert, and as a result the modeled precipitation in response to urbanization decreases within the Phoenix urban area and increase on its periphery. Finally, analysis of how monsoon severe weather is changing in association with observed global climate change is considered within the context of a series of retrospectively simulated severe weather events during the period 1948-2010 in a numerical weather prediction paradigm. The individual severe weather events are identified by favorable thermodynamic conditions of instability and atmospheric moisture (precipitable water). Changes in precipitation extremes are evaluated with extreme value statistics. During the last several decades, there has been intensification of organized convective precipitation, but these events occur with less frequency. A more favorable thermodynamic environment for monsoon thunderstorms is the driver of these changes, which is consistent with the broader notion that anthropogenic climate change is presently intensifying weather extremes worldwide.

O potencial aumento da atividade convectiva e da severidade das tempestades proporcionada pela ilha de calor urbana das grandes cidades, já apontado por diversos autores, é verificado através de testes com o modelo BRAMS, em que o esquema TEB é ativado e desativado para dois casos de tempestade. Em seguida, cenários de crescimento da mancha urbana para o ano de 2030 e de aumento da área com construções altas foram utilizados para avaliar o possível aumento na quantidade de precipitação, nos índices de tempo severo e, consequentemente, na severidade das tempestades que podem ocorrer na região. Com os métodos de planejamento fatorial e separação de fatores, verificou-se que o aumento da mancha urbana é capaz de aumentar a quantidade de chuva sobre a RMSP, indicando que a mudança do uso do solo de rural para o urbano é determinante para este aumento. O aumento da área com construções altas possui uma tendência para causar supressão da chuva. O aumento da mancha urbana é o principal fator gerador de instabilidade e cisalhamento entre os ensaios. O fator de aumento da urbanização vertical causa diferentes impactos entre os dois casos de tempestade, um com aumento e outro com redução da instabilidade. Em ambos os casos a verticalização causa redução do cisalhamento. A interação entre os dois fatores, urbanização horizontal e vertical, gera um aumento da precipitação e um deslocamento maior da tempestade sobre a RMSP, em relação ao cenário atual, porém menor do que ocorreria para o cenário com apenas aumento da mancha urbana. / The potential increase in convective activity and severity, caused by urban heat island effect, is verified with tests using BRAMS model, between cases with and without TEB scheme for two storm cases. Scenarios of future urban area and increase of high buildings area was made to evaluate changes in rainfall, convective parameters, and consequently, in severe weather probability for the study region. Using factorial planning and factor separation methods, it was found that the urban area growth is capable to increase the amount of precipitation, mainly due to the land use change from rural to urban. In the scenario of building heights increasing, it was found a tendency for rainfall suppress. The urban area growth is the major factor contributing to increase atmospheric instability and wind shear. Vertical urban growth causes different impacts between two storm cases, one with an increase and other with a decrease in instability. In both cases there were reductions in wind shear. The interaction between two factors increases the amount of precipitation and the displacement of the storm over MASP, in relation to the current scenario, but less than would occur for the scenario with only urban area growth.

Neste trabalho foram estudadas as linhas de instabilidade (LI) que atingiram a RMSP, o desenvolvimento de tempo severo associados a estas e a possibilidade de utilizar alguns parâmetros de tempo severo na identificação destes eventos. Foram identificadas 185 linhas no período de 2002 a 2009 através da observação de imagens de satélite. Estas ocorrem durante todos os períodos do ano, embora a frequência seja maior nos meses de verão, em função da maior atividade convectiva nessa estação do ano. Foi identificado que 94 % das LI se deslocaram para leste enquanto apenas 6 % tiveram seu deslocamento para oeste. Testes sobre configurações mais adequadas para a simulação de LI com o modelo BRAMS indicaram que as parametrizações de convecção disponíveis no modelo não são capazes de representar os eventos de forma adequada, havendo a necessidade de aumento na resolução das simulações e forte dependência da parametrização de microfísica. Foi constatado que espaçamentos de grade de oito quilômetros são suficientes para uma boa representação dos eventos. Os testes também indicaram que, dentre as opções disponíveis no modelo, o uso da deformação Anisotrópica para o tratamento dos processos turbulentos é o mais indicado para a simulação de casos de LI. Os parâmetros convectivos mostraram-se bons indicadores de tempo severo na presença de sistemas de origem baroclínica, apresentando valores similares aos encontrados para o HN. Porém, em tempestades onde o efeito termodinâmico é o fator mais importante, como nas tempestades isoladas ou na presença de ZCAS os índices cinemáticos nem sempre são bons preditores de tempo severo. A análise dos parâmetros convectivos obtidos das radiosondagens lançadas na RMSP mostra que, em muitos casos observados de LI, não há valores indicativos de ocorrência de tempo severo, ressaltando a importância do uso de perfis obtidos da modelagem numérica, numa região de abrangência maior, para a obtenção desses índices. / A study about the squall lines that reached Metropolitan Area of São Paulo (MASP), the development of severe weather associated with these and the possibility of using some parameters in the identification of severe weather are presented. It was identified a total of 185 squall lines between 2002 and 2009 through the analysis of satellite images. These lines occur during all periods of the year, although the frequency of squall lines is higher in summer months, due to increased convective activity in this season. Also, it was identified that 94 % of the squall lines moved eastward while only 6% of then moved westward. Tests about the most appropriate configuration to the squall lines simulation with BRAMS model indicated that the convective parameterizations available in the model are not able to represent the events in an adequate manner, being necessary to use higher resolutions in the simulations, which creates a stronger dependence on microphysics parameterization. We note that grid spacing as low as eight kilometers are enough for a fair representation of the events. The tests also indicated that, among all the options available in the model for turbulent process the anisotropic deformation is the one that works better in simulating squall lines. The convective parameters proved to be good indicators of severe weather in the presence of baroclinic systems, with similar values to those found for the Northern Hemisphere. However in storms where the thermodynamic effect is the most important factor, as in isolated storms and in the presence of the Southern Atlantic Convergence Zone (SACZ), kinematics indices are not always good predictors of severe weather. The analysis of convective indices, obtained through radiosondes variables launched in the MASP, shows that in many squall line observed cases there is no indication of severe weather occurrence. This fact increases the importance of using the profiles provided by numerical modeling over a larger region to obtain such indices.

abstract: Severe weather affects many regions of the United States, and has potential to greatly impact many facets of society. This study provides a climatological spatial analysis by county of severe weather warnings issued by the National Weather Service (NWS) between January 1st, 1986 to December 31st, 2017 for the contiguous United States. The severe weather warnings were issued for county-based flash flood, severe thunderstorm, and tornado phenomena issued through the study period and region. Post 2002 severe weather warnings issued by storm warning area were included in this study in the form of county-based warnings simultaneously issued for each affected county. Past studies have researched severe weather warnings issued by the NWS, however these studies are limited in geographic representation, study period, and focused on population bias. A spatial analysis of severe weather warning occurrences by county identify that (a) highest occurrences of flash flood warnings are located in the desert Southwest and Texas, (b) severe thunderstorm warning occurrence is more frequent in Arizona, portions of the Midwest, the South, and the Mid and South Atlantic states, (c) the tornado activity regions of Tornado Alley and Dixie Alley (i.e. Colorado, Kansas, Oklahoma, Arkansas, Texas, Louisiana, Mississippi, Alabama, Tennessee, and Illinois) contained the highest occurrences of tornado warnings, and (d) the highest instances of aggregate warning occurrences are found in the desert Southwest, the Midwest, and the Southern regions of the United States. Generally, severe weather warning “hot spots” tend to be located in those same regions, with greater coverage. This study concludes with a comparison of local maxima and general hot spot regions to expected regions for each phenomenon. Implications of this study are far reaching, including emergency management, and has potential to reduce risk of life. / Dissertation/Thesis / Masters Thesis Geography 2019

Tornadoes are one of Mother Nature’s deadliest phenomena. They affect a large region of the United States. The risk of tornadoes is contingent on dynamic atmospheric conditions that are most likely during spring but which can occur anytime of the year, making the storms challenging to forecast. Using geographical information systems (GIS), a web-based spatial decision support system (SDSS) was created to help understand the spatial dimension of tornado risk assessment. The risk values are calculated using Tornado Days rather than taking a crude density measurement. The SDSS hosts GIS web services that are displayed on an Adobe Flex application. The web application allows users to view, research, query and extract information from the attributes of the GIS files. There is also a dynamic risk tool which gives users the ability to click anywhere inside the study area and get the percentage of risk that a tornado will occur within 25 miles of that very point. The web application eliminates users and viewers from conducting their own research and GIS work. In addition, automated updating models and macros were created to update the tornado database on an annual basis.

Neste trabalho foram estudadas as linhas de instabilidade (LI) que atingiram a RMSP, o desenvolvimento de tempo severo associados a estas e a possibilidade de utilizar alguns parâmetros de tempo severo na identificação destes eventos. Foram identificadas 185 linhas no período de 2002 a 2009 através da observação de imagens de satélite. Estas ocorrem durante todos os períodos do ano, embora a frequência seja maior nos meses de verão, em função da maior atividade convectiva nessa estação do ano. Foi identificado que 94 % das LI se deslocaram para leste enquanto apenas 6 % tiveram seu deslocamento para oeste. Testes sobre configurações mais adequadas para a simulação de LI com o modelo BRAMS indicaram que as parametrizações de convecção disponíveis no modelo não são capazes de representar os eventos de forma adequada, havendo a necessidade de aumento na resolução das simulações e forte dependência da parametrização de microfísica. Foi constatado que espaçamentos de grade de oito quilômetros são suficientes para uma boa representação dos eventos. Os testes também indicaram que, dentre as opções disponíveis no modelo, o uso da deformação Anisotrópica para o tratamento dos processos turbulentos é o mais indicado para a simulação de casos de LI. Os parâmetros convectivos mostraram-se bons indicadores de tempo severo na presença de sistemas de origem baroclínica, apresentando valores similares aos encontrados para o HN. Porém, em tempestades onde o efeito termodinâmico é o fator mais importante, como nas tempestades isoladas ou na presença de ZCAS os índices cinemáticos nem sempre são bons preditores de tempo severo. A análise dos parâmetros convectivos obtidos das radiosondagens lançadas na RMSP mostra que, em muitos casos observados de LI, não há valores indicativos de ocorrência de tempo severo, ressaltando a importância do uso de perfis obtidos da modelagem numérica, numa região de abrangência maior, para a obtenção desses índices. / A study about the squall lines that reached Metropolitan Area of São Paulo (MASP), the development of severe weather associated with these and the possibility of using some parameters in the identification of severe weather are presented. It was identified a total of 185 squall lines between 2002 and 2009 through the analysis of satellite images. These lines occur during all periods of the year, although the frequency of squall lines is higher in summer months, due to increased convective activity in this season. Also, it was identified that 94 % of the squall lines moved eastward while only 6% of then moved westward. Tests about the most appropriate configuration to the squall lines simulation with BRAMS model indicated that the convective parameterizations available in the model are not able to represent the events in an adequate manner, being necessary to use higher resolutions in the simulations, which creates a stronger dependence on microphysics parameterization. We note that grid spacing as low as eight kilometers are enough for a fair representation of the events. The tests also indicated that, among all the options available in the model for turbulent process the anisotropic deformation is the one that works better in simulating squall lines. The convective parameters proved to be good indicators of severe weather in the presence of baroclinic systems, with similar values to those found for the Northern Hemisphere. However in storms where the thermodynamic effect is the most important factor, as in isolated storms and in the presence of the Southern Atlantic Convergence Zone (SACZ), kinematics indices are not always good predictors of severe weather. The analysis of convective indices, obtained through radiosondes variables launched in the MASP, shows that in many squall line observed cases there is no indication of severe weather occurrence. This fact increases the importance of using the profiles provided by numerical modeling over a larger region to obtain such indices.

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ropical cyclone-induced tornadoes (TCIT) exacerbate the devastation that landfalling tropical cyclones have on the United States. This research applied machine learning techniques in conjunction with midlatitude severe weather parameters to create an artificial intelligence (AI) capable of predicting TCIT occurrence. Severe weather diagnostic variables were collected at thousands of gridpoints from the North American Regional Reanalysis (NARR) to characterize the environments within tropical cyclones between 1991 and 2011. A support vector machine (SVM) was generated in various configurations to obtain the most effective AI. This approach revealed many parameters that were ineffective at predicting TCITs (primarily those utilizing the effective inflow layer). In addition, the most highly configured AI were capable of predicting TCIT occurrence with a Heidke Skill Score around 0.48.

Because extreme weather events are relatively common in the Southeastern U.S., and the current treatments for phobias can be time-consuming and costly, it is important to find an effective early intervention program for those individuals who are at risk of developing severe weather phobia (SWP). Participants (N = 12) were randomly assigned to the experimental or modified control condition. Participants from both conditions participated in the therapist-aided self-help early intervention program. However, the modified control condition completed posttest measures approximately 3 weeks after baseline, before beginning the intervention. The intervention was most effective at reducing subjective fear and avoidance behavior related to severe weather events. Additionally, participants’ subjective views of their fears were no longer categorized as excessive, or unreasonable, nor did they avoid or endure severe weather with intense anxiety or distress after the three-week early intervention.