Scanning strategies for research and operational applications were developed for meteorological measurements with an experimental PAR, the MWR-05XP. A tornadic storm sampling strategy was developed with a 502.26 ms volumetric update and a resolution of 1.8 Az x 2 El x 150 m range. A sampling strategy for severe thunderstorm clusters was developed with a 10 second volumetric update and a resolution of 1.8 Az x 2 El x 300 m range. An operational weather scanning strategy was developed with an 81 second volumetric update and a resolution of 1.8 Az x 2 El x 150 m range. In general, for the acquisition of weather data, single frequency phased array radars offer only a slight sampling advantage over conventional scanning radars. This research verified that for meteorological sampling with the MWR-05XP, frequency diversity, coupled with electronic elevation scanning, offers a significant sampling advantage over conventional radars. The combination of electronic beam steering and frequency diversity produces a synergistic reduction in sampling time that increases the overall volumetric update rate. This research has also shown that, based on assumptions about the MWR-05XP operating parameters, it is possible to incorporate operational weather scanning into the radar's multifunction capability.

Severe weather events that accompany climatic changes have been the main focus of many studies that want to highlight the large processes that surround us every day. These studies are based on years of data collection and other studies to help aid their pursuits. An area of major focus is identifying proxies and supplementary materials that help refine climate records of the geologic past. This study aims to identify reliable proxies for obtaining a record of severe weather events. The research consists of studying a coral species Pseudodiploria strigosa colonies with the goal to document, interpret, and describe the burial and re-exposure of massive coral colonies by severe storm or hurricane events, as recorded in coral growth patterns through density patterns and the analysis of CT-scanned coral specimens. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

Thesis (M.A.)--Baylor University, 2008. / Includes bibliographical references (p. 121-126).

Thesis (M.S. in Meteorology)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): Jeffrey B. Knorr, Carlyle H. Wash. Includes bibliographical references (p. 75-77). Also available online.

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.

A região amazônica desempenha papel fundamental na regulação do clima, tanto em escala regional quanto em escala global. A precipitação na região é bastante heterogênea, sobretudo devido à vasta extensão territorial da Amazônia. Dentre os sistemas responsáveis pela precipitação, alguns se destacam como eventos extremos de tempestades, como pode ser verificado em diversos estudos anteriores. Contudo, diferentemente das latitudes médias, na região tropical não há um conjunto de definições amplamente conhecido e difundido para identificação de tempo severo. O presente estudo busca identificar um critério para identificação de tempo severo na região amazônica a partir da base de dados Precipitation Features (PF) 1998 a 2012 - gerados e armazenados pela Universidade de Utah, com base nos dados do satélite TRMM. Além disso, identificar características sinóticas associadas ao ambiente de ocorrência destes eventos, através de composições com dados da reanálise CFSR-NCEP, bem como parâmetros importantes na identificação de tempestades. Utilizando o subconjunto PCTF do Nível 2 da base de dados PF, o critério estabelecido para identificação de casos severos compreende sistemas com: 80 pixels ou mais PCT85 GHz <250 K; 1 pixel ou mais com PCT85 GHz < 100 K; volume de chuva convectiva maior do que 1000 mm/h km2 e pelo menos um registro de raio. Comparando os sistemas selecionados pelo critério com os Sistemas Convectivos de Mesoescala já catalogados é possível notar que a distribuição sazonal é semelhante, embora as estações com maior número de casos sejam as estações de transição (primavera e outono, 429 e 223 casos respectivamente). Analisando as altas taxas de raios destes sistemas, fica evidente que o critério realmente seleciona casos severos. Com a região amazônica dividida em seis sub-regiões e os casos acumulados por trimestre (JFM, AMJ, JAS, OND) sub-região Southern Amazonia (SA) contabiliza o maior número de casos, com um total de 271 para o período do estudo, sendo OND o trimestre com maior ocorrência (135), o menor AMJ (29). O mês de outubro chama atenção para esta sub-região como o mês com maior número de casos, totalizando 59, dos quais 83% ocorrem a partir das 12 horas local. Estes casos foram investigados nas composições de reanálise, assim como os casos a partir de 12 horas local de outubro da sub-região Central Amazonia (CA). De forma geral: 1) SA tem maior área com cisalhamento médio mais intenso (8 m/s) do que CA, principalmente para 00Z, 06Z e 12Z; 2) valores médios de divergência positiva do vento em 200 hPa mostram-se mais significativos para CA do que para SA; 3) convergência do vento em 950 hPa é mais evidente para SA do que para CA e 4) CA é predominantemente mais úmida em baixos níveis do que SA. Histogramas com valores pontuais para cada um destes casos, em ambas as sub-regiões, são apresentados no intuito de auxiliar a identificação destes casos por previsores. O critério de identificação de tempo severo na Amazônia mostra-se eficiente, sendo o cisalhamento do vento entre 500-850 hPa e a convergência do vento em 950 hPa os como parâmetros mais importantes na região SA, onde há maior ocorrência de tempestades severas. / The Amazon region plays a key role in climate regulation, both at the regional scale and on a global scale. Rainfall in the region is very heterogeneous, mainly because of the vast size of the Amazon. Among the systems responsible for rainfall, some stand out as extreme storm events, as can be seen in many previous studies. However, unlike the mid-latitudes, in the tropical region there is no widely acknowledged set of conditions for severe weather identification. This study seeks to identify a criterion for identifying severe weather in the Amazon region from the database Precipitation Features (PF) - 1998-2012 - generated and stored by the University of Utah, based on the TRMM satellite data. This study will also attempt to identify synoptic features associated with the occurrence of these events through compositions using the reanalysis NCEP CFSR data. Using the PCTF subset of Level 2 of PF database, the criteria established for identifying severe cases include: 1) systems with 80 or more pixels PCT85 GHz <250 K; 2) systems with one or more pixel with PCT85 GHz <100 K; 3) systems with convective rain volume greater than 1000 km2 mm/h and 4) at least one record of lightning. Comparing the systems selected by this criterion with the Mesoscale Convective Systems already cataloged it can be seen that the seasonal distribution is similar, although the stations with the highest number of cases are the transition seasons (spring and fall, 429 and 223 cases, respectively). Analyzing high rates of rays found in these systems, it is clear that the criterion truly selects severe cases. With the Amazon region divided into six sub-regions and cases accumulated by quarter (JFM, AMJ, JAS, OND) South of the Amazon sub region (SA) accounts for the largest number of cases, with a total of 271 for the period of study, OND quarter with higher occurrence (135), the lowest AMJ (29). The month of October draws attention to this sub-region as the month with the highest number of cases, totaling 59, of which 83% occur after 12 local time. These cases have been investigated in compositions, as well as cases observed after 12 local time in October for Amazon Central subregion (CA). In general: 1) SA has larger area with average stronger shear (8 m/s) than AC, especially for 00Z, 06Z and 12Z; 2) average wind positive divergence values at 200 hPa were more significant for CA than for SA; 3) Wind convergence at 950 hPa is more obvious for SA than at CA and 4) is predominantly CA moster at low levels than SA. Histograms with specific values for each of these cases, both sub regions are presented in order to help identify predictors for these cases. The severe weather identification criterion in the Amazon proves efficient, while the wind shear between 500-850 hPa and wind convergence in 950 hPa stand out as important parameters in the SA region, where there is greater occurrence of severe storms.

The contribution of this thesis is twofold: 1) the development of a hydrodynamic landscape evolution model for use on high-performance computing systems and 2) assessing the sensitivity of hydrogeomorphic processes to high-resolution rainfall input data and erosional parameterisation using the model. The thesis addresses a limitation in numerical landscape evolution models regarding how spatial variation in rainfall is represented or parameterised within such models. Typically, landscape evolution models forsake a realistic representation of rainfall patterns in favour of a simpler treatment of rainfall as being spatially homogeneous across the model domain. This simplification of rainfall spatial variability is still made despite the fact that many geomorphological processes are sensitive to thresholds of sediment entrainment and transport, driven by the distribution and movement of water within the landscape. The thesis starts by exploring current limitations in rainfall representation in landscape evolution models, and assesses various precipitation data sources that could be potentially used as more realistic rainfall inputs to landscape evolution models. A numerical model of landscape evolution is developed for deployment on high-performance parallel computing systems, based on the established CAESAR-Lisflood model (Coulthard et al., 2013). The new model code is benchmarked, showing performance benefits compared with the original CAESAR-Lisflood model it is based on. The model is applied to assessing the sensitivity of flood-inundation predictions, sediment flux, and erosion distribution within river catchments to spatial variation in rainfall during extreme storm events. Two real storm events that caused localised flash flooding in the UK are used as test cases: the Boscastle storm of 2004 and the North York Moors storm of 2005. Flood extent predictions and river discharges are found to be sensitive to the use of spatially variable input rainfall data, with high-resolution rainfall data leading to larger peak flood discharges. However, the differences are less pronounced in smaller catchments. The role of sediment erosion during large floods is also assessed, but it is found to play a minor role relative to spatially variable rainfall data. In contrast, the geomorphological response of catchments to single storm events is shown to be less sensitive to the spatial heterogeneity of rainfall input and controlled more strongly by the choice of erosional process parameterisation within the model. Nonetheless, spatial variability in rainfall data is shown to increase sediment yields during flash flood simulations.

A região amazônica desempenha papel fundamental na regulação do clima, tanto em escala regional quanto em escala global. A precipitação na região é bastante heterogênea, sobretudo devido à vasta extensão territorial da Amazônia. Dentre os sistemas responsáveis pela precipitação, alguns se destacam como eventos extremos de tempestades, como pode ser verificado em diversos estudos anteriores. Contudo, diferentemente das latitudes médias, na região tropical não há um conjunto de definições amplamente conhecido e difundido para identificação de tempo severo. O presente estudo busca identificar um critério para identificação de tempo severo na região amazônica a partir da base de dados Precipitation Features (PF) 1998 a 2012 - gerados e armazenados pela Universidade de Utah, com base nos dados do satélite TRMM. Além disso, identificar características sinóticas associadas ao ambiente de ocorrência destes eventos, através de composições com dados da reanálise CFSR-NCEP, bem como parâmetros importantes na identificação de tempestades. Utilizando o subconjunto PCTF do Nível 2 da base de dados PF, o critério estabelecido para identificação de casos severos compreende sistemas com: 80 pixels ou mais PCT85 GHz <250 K; 1 pixel ou mais com PCT85 GHz < 100 K; volume de chuva convectiva maior do que 1000 mm/h km2 e pelo menos um registro de raio. Comparando os sistemas selecionados pelo critério com os Sistemas Convectivos de Mesoescala já catalogados é possível notar que a distribuição sazonal é semelhante, embora as estações com maior número de casos sejam as estações de transição (primavera e outono, 429 e 223 casos respectivamente). Analisando as altas taxas de raios destes sistemas, fica evidente que o critério realmente seleciona casos severos. Com a região amazônica dividida em seis sub-regiões e os casos acumulados por trimestre (JFM, AMJ, JAS, OND) sub-região Southern Amazonia (SA) contabiliza o maior número de casos, com um total de 271 para o período do estudo, sendo OND o trimestre com maior ocorrência (135), o menor AMJ (29). O mês de outubro chama atenção para esta sub-região como o mês com maior número de casos, totalizando 59, dos quais 83% ocorrem a partir das 12 horas local. Estes casos foram investigados nas composições de reanálise, assim como os casos a partir de 12 horas local de outubro da sub-região Central Amazonia (CA). De forma geral: 1) SA tem maior área com cisalhamento médio mais intenso (8 m/s) do que CA, principalmente para 00Z, 06Z e 12Z; 2) valores médios de divergência positiva do vento em 200 hPa mostram-se mais significativos para CA do que para SA; 3) convergência do vento em 950 hPa é mais evidente para SA do que para CA e 4) CA é predominantemente mais úmida em baixos níveis do que SA. Histogramas com valores pontuais para cada um destes casos, em ambas as sub-regiões, são apresentados no intuito de auxiliar a identificação destes casos por previsores. O critério de identificação de tempo severo na Amazônia mostra-se eficiente, sendo o cisalhamento do vento entre 500-850 hPa e a convergência do vento em 950 hPa os como parâmetros mais importantes na região SA, onde há maior ocorrência de tempestades severas. / The Amazon region plays a key role in climate regulation, both at the regional scale and on a global scale. Rainfall in the region is very heterogeneous, mainly because of the vast size of the Amazon. Among the systems responsible for rainfall, some stand out as extreme storm events, as can be seen in many previous studies. However, unlike the mid-latitudes, in the tropical region there is no widely acknowledged set of conditions for severe weather identification. This study seeks to identify a criterion for identifying severe weather in the Amazon region from the database Precipitation Features (PF) - 1998-2012 - generated and stored by the University of Utah, based on the TRMM satellite data. This study will also attempt to identify synoptic features associated with the occurrence of these events through compositions using the reanalysis NCEP CFSR data. Using the PCTF subset of Level 2 of PF database, the criteria established for identifying severe cases include: 1) systems with 80 or more pixels PCT85 GHz <250 K; 2) systems with one or more pixel with PCT85 GHz <100 K; 3) systems with convective rain volume greater than 1000 km2 mm/h and 4) at least one record of lightning. Comparing the systems selected by this criterion with the Mesoscale Convective Systems already cataloged it can be seen that the seasonal distribution is similar, although the stations with the highest number of cases are the transition seasons (spring and fall, 429 and 223 cases, respectively). Analyzing high rates of rays found in these systems, it is clear that the criterion truly selects severe cases. With the Amazon region divided into six sub-regions and cases accumulated by quarter (JFM, AMJ, JAS, OND) South of the Amazon sub region (SA) accounts for the largest number of cases, with a total of 271 for the period of study, OND quarter with higher occurrence (135), the lowest AMJ (29). The month of October draws attention to this sub-region as the month with the highest number of cases, totaling 59, of which 83% occur after 12 local time. These cases have been investigated in compositions, as well as cases observed after 12 local time in October for Amazon Central subregion (CA). In general: 1) SA has larger area with average stronger shear (8 m/s) than AC, especially for 00Z, 06Z and 12Z; 2) average wind positive divergence values at 200 hPa were more significant for CA than for SA; 3) Wind convergence at 950 hPa is more obvious for SA than at CA and 4) is predominantly CA moster at low levels than SA. Histograms with specific values for each of these cases, both sub regions are presented in order to help identify predictors for these cases. The severe weather identification criterion in the Amazon proves efficient, while the wind shear between 500-850 hPa and wind convergence in 950 hPa stand out as important parameters in the SA region, where there is greater occurrence of severe storms.

Approved for public release, distribution is unlimited / This study investigates severe weather events occurring in the Midwest, Central, and Northeastern United States from May through September 2004. Severe weather events are pinpointed using tornado and hail reports and correlating them with NEXRAD radar data to determine maximum intensity of the event. Severe storms that occur within 30 minutes of a model forecast hour are catalogued for further investigation. Once these events are diagnosed, ETA-212 and MM5 model data is regridded, centered on the storm. Divergence values at 300 hPa are extracted from the model data for each storm event. These storms are then grouped in three ways: all storms, tornadic storms, and hail producing storms. The averaged maximum divergence values from the ETA-212 for each group are examined from the 0 hour analysis through the 21 hour forecast. From these averaged divergence values, a matrix of recommended divergence threshold values is derived. For the MM5 data, a subset of storms is examined. The MM5 and ETA-212 are run on an identical set of storms, and the divergence forecasts are compared. / Captain, United States Air Force

This study presents a climatology of convectively-generated strong wind gusts (SWG) occurred in Southern Brazil in the 2005-2015 period. The selection of these events was based on surface hourly data from the operational network of automated weather stations (AWSs) operated by Brazil’s National Meteorological Institute (INMET, in portuguese) and geostacionary meteorological satellite imagery. The time series of the atmospheric variables recorded by the AWSs during the SWGs events were evaluated aiming at detecting cold pools and mesohighs. Proximity soundings and Climate Forecast System Reanalysis (CFSR) and Climate Forecast System Version 2 (CFSv2) reanalysis data were used to assess the atmospheric environment during the occurence of the wind gust events. It was evalueted whether the atmospheric conditions highlight environments that discriminates the occurence of the SWG of those less intense. Moreover, a comparision was conducted among atmospheric profiles generated from CFSR/CFSv2 reanalysis and profiles obtained from operational soundings taken in Southern Brazil in the 1996-2015 period. The results showed that INMET’s AWS were able to sample convectively-driven cold pools and mesohighs following the wind gusts. The highest frequency of SWGs was in the spring and summer months. Most SWGs were detected from mid-afternoon to overnight hours. The western portion of Southern Brazil displayed the largest frequency of SWGs. The median value of pressure variations following the SWG +4,6 hPa, with extreme values (95% percentile) reaching +8,2 hPa. The median value for temperature variations was -6,5 C, with extremes values below -13,0 C. Overall, the results showed that the atmospheric parameters demonstrate some discrimination between SWGs and weaker wind gusts. The Downdraft Convective Available Potential Energy (DCAPE) and the Derecho Composite Parameter (DCP) were the atmospheric parameters that better discriminate the atmospheric environment favorable to the occurence of SWGs. The comparision between atmospheric profiles generated from CFSR/CFSv2 data and observed soundings showed that the reanalysis reproduce well the thermodynamic parameters, but significantly underestimates the kinematic parameters. / Neste trabalho é apresentada uma climatologia de rajadas (RAJ) de vento convectivas intensas ocorridas na região sul do Brasil entre 2005 e 2015. A seleção destes eventos foi feita com base nos dados horários da rede operacional de estações meteorológicas automáticas (EMAs) de superfície do Instituto Nacional de Meteorologia (INMET) e imagens de satélites meteorológicos geoestacionários. As séries temporais das variáveis atmosféricas registradas pelas EMAs durante os eventos de RAJ foram avaliadas para detectar piscinas de ar frio e mesoaltas. O ambiente atmosférico durante a ocorrência das RAJ foi analisando utilizando-se perfis atmosféricos extraídos de sondagens de proximidade e de dados de reanálise do Climate Forecast System Reanalysis (CFSR) e Climate Forecast System Version 2 (CFSv2). Avaliou-se se as condições atmosféricas ressaltam ambientes que discriminem a ocorrência das rajadas convectivas mais intensas daquelas menos intensas. Foi conduzida também uma comparação entre os perfis atmosféricos extraídos da reanálise CFSR/CFSv2 e os perfis obtidos de sondagens operacionais realizadas no sul do Brasil para o período entre 1996 e 2015. Os resultados mostraram que as EMAs-INMET conseguiram amostrar as piscinas de ar frio e mesoaltas que acompanham as rajadas convectivas. As rajadas intensas ocorreram com mais frequência na primavera e verão, e predominantemente entre o final da tarde e a madrugada. Em geral, houve uma ligeira tendência para uma maior ocorrência de RAJ nas EMAs-INMET do setor oeste da Região Sul. A mediana das variações de pressão acompanhando a RAJ foi de +4,6 hPa, com valores mais extremos (percentil 95%) atingindo +8,2 hPa. A mediana das variações de temperatura foi -6,5 C, com valores extremos abaixo de -13,0 C. De maniera geral, os parâmetros atmosféricos conseguiram demonstrar alguma discriminação entre a classe de RAJ intensas e as rajadas mais fracas. O Downdraft Convective Available Potential Energy (DCAPE) e o Derecho Composite Parameter (DCP) foram os parâmtros que melhor discriminaram ambientes atmosféricos favoráveis à ocorrência de rajadas de vento intensas. A comparação entre reanálise CFSR/CFSv2 e sondagens observadas mostrou que a reanálise reproduziu bem os parâmetros termodinâmicos, mas subestimou significativamente os parâmtros cinemáticos.