Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (leaves 127-137).

Thesis (Ph. D.)--University of Hawaii at Manoa, 2002. / Includes bibliographical references (leaves 62-66).

Thesis (M.S. in E.A.S.)--School of Earth and Atmospheric Sciences, Georgia Institute of Technology, 2004. Directed by James Gaherty. / Includes bibliographical references (leaves 38-42).

Esta tese investiga se eventos anômalos de precipitação pluviométrica (PP) na Planície Costeira do Rio Grande do Sul (PCRGS) estão relacionados a modos de variabilidade climática e como essa relação pode afetar o ambiente costeiro. A PP e suas anomalias foram estatisticamente correlacionadas aos modos de variabilidade climática, o Modo Anular do Hemisfério Sul (SAM) e El Niño - Oscilação Sul (ENOS). O índice do ENOS utilizado foi o Multivariate ENSO Index (MEI) e do SAM foi o de Nan e Li (2003). Para o cálculo das anomalias de PP foram utilizados dados do satélite Tropical Rainfall Measurement Mission, entre 1998 e 2013. As correlações foram calculadas por meio de matrizes de classificação, e suas significâncias pelo teste-t de Student. A área de estudo foi dividida em costas sul (33°44’39” – 32°09’36”S), central (32°09’36” – 30°10’12”S) e norte (30°10’12” – 29°19’34”S) e para cada uma delas foi escolhido um geoindicador (sangradouros ou lagunas), examinados em imagens de satélite. Comparouse os geoindicadores em períodos de PP anomalamente positiva e negativa. Para destacar as variações nos geoindicadores foram utilizadas composições RGB 543 dos sensores Thematic Mapper (TM) e Enhanced Thematic Mapper Plus (ETM+) do Landsat. Os resultados apontam para correlação negativa entre as anomalias de PP nas costas sul e central com o SAM e correlação positiva das anomalias de PP da costa sul com o MEI. A PP na costa norte não apresenta correlação com nenhum dos dois índices. Foram identificados 28 eventos anômalos de PP no período 1998-2013. Nas imagens de satélite todos geoindicadores apontaram para variações morfológicas e hídricas entre os períodos PP acima e abaixo da média, sendo a costa norte a que apresenta menor variação visível. A costa sul tem a menor média de PP e o maior número de eventos anômalos de PP, dos quais 67% eram de PP negativa. A maioria dos eventos são de PP negativa (78%) e podem estar relacionados simultaneamente ao SAM positivo e MEI negativo, ou somente ao MEI positivo. Todos eventos de PP positiva foram concomitantes ao MEI positivo. As costas sul e central mostram uma redução na PP média. Essa tendência pode estar relacionada as mudanças climáticas globais, pela intensificação do SAM positivo e de eventos El Niño e La Niña. As variações observadas nos geoindicadores (sangradouros ou lagunas) indicam que a redução na PP média resulta em menor volume de sedimentos transportados do pós praia para a zona de arrebentação e face praial, alterando o balanço sedimentar. As areias secas dos campos de dunas transportadas pelo vento podem assorear lagos e lagunas da área de estudo, desequilibrando o ecossistema. / This thesis investigates whether anomalous events of precipitation (PP) in the Coastal Plain of Rio Grande do Sul (RGSCP) are related to climate variability modes and how this relationship can affect the coastal environment. The PP and its anomalies were statistically correlated to climate variability modes, the Southern Annular Mode (SAM) and El Niño-Southern Oscillation (ENSO). The used ENSO index was the Multivariate ENSO Index (MEI) and SAM is the one defined by Nan and Li (2003). For the calculation of the PP anomalies, we used data from the Tropical Rainfall Measurement Mission satellite, from 1998 to 2013. Correlations were calculated using classification matrices, and their significance by the the Student t-test. The study area was divided into south (33°44'39" – 32°09'36"S), central (32°09'36"– 30°10'12"S) and north (30°10'12"– 29°19'34"S) coasts and for each one it was chosen a geoindicador (washouts or lagoons), examined on satellite images. This investigation compared the geoindicators in positive and negative anomalous PP periods. To highlight variations in the geoindicators, it was used the RGB 543 composition of the Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) Landsat sensors. The results point to a negative correlation of the PP anomalies in the southern and central coasts with the SAM and a positive correlation of PP anomalies in the south coast with the MEI. The north coast PP is not correlated with any of the two indexes. Twenty-eight anomalous PP events were found in the 1988–2013 period. In satellite images, all geoindicators pointed to morphological and hydrological variations between periods of PP above and below the mean, the northern coast has the least visible variations. The south coast has the lowest mean PP and the largest number of anomalous events, of which 67% were negative PP. The majority of events are negative PP (78%), they could be simultaneously connected to a positive SAM and a negative MEI, or only to a positive MEI. All positive PP events were concomitant to a positive MEI. The central and southern coasts show a decrease in the men PP. This trend may be related to global climate change, by the intensification of the positive SAM and of El Niño and La Niña events. The variations observed in geoindicators (washouts or lagoons) indicate that the reduction in the mean PP results in lower volume of sediments transported from the backshore to the surf zone and the shoreface, changing the sedimentary balance. The dry sands from the wind-transported dune fields could silt up lakes and lagoons of the study area, unbalancing the ecosystem.

No description available.

There is growing concern in the United States and abroad that changes in climate may have serious adverse impacts on communities and their civil infrastructure systems. In response, governments and agencies have begun to investigate adaptation: actions taken to reduce the vulnerability or increase the resiliency of natural and human systems in light of expected climate change. In the transportation sector, adaptation planning has predominantly pursued risk-based strategies that seek to identify climate impacts, and assess infrastructure vulnerabilities across multiple asset types, in network-level planning. However, given the complexity of the myriad asset types of which engineered civil infrastructure systems are composed, these frameworks may not adequately address the unique concerns of these various individual asset types. This research develops a risk-based framework to assess and prioritize at a network-level the risks of highway culvert assets to the projected impacts of climate change, specifically focusing on increases in extreme precipitation, and the associated potential for flooding. The framework is applied in a series of case studies using culvert management data provided by four state DOTs, and national climate change projection and infrastructure datasets. The framework developed proposes a new characterization of infrastructure climate change risk, based upon the catastrophe model, to address the need for qualitative approaches to risk given the uncertain nature of climate change, and the sometimes sparse inventory and attribute data for various assets. This characterization proposes three “dimensions” of infrastructure climate risk (climate change impact exposure, asset climate impact vulnerability, and asset criticality) to assign culvert asset priorities. The research develops a method to project the geospatial extent and changes in magnitude of extreme precipitation events; it also develops two measures of culvert vulnerability to increased flow conditions based upon data collected in general culvert management activities. This research demonstrates that existing data sources can be reasonably combined in an analytical assessment framework to identify climate change impact risks to highway culvert assets, providing an additional resource to the existing climate change adaptation planning and risk management toolkit in the transportation infrastructure sector, and also laying a foundation for further refinement of these methods. The results of this research demonstrate that existing climate change projection data, when used alongside culvert inventory and attribute data, provides a reasonable means by which to analyze the projected exposure of culvert assets to climate change impacts. This research also demonstrates that existing culvert management data provides a reasonable foundation upon which to assess the relative vulnerability of culverts to increased flow conditions, although additional research is necessary to develop these methods. The structure of the proposed framework provides a viable means by which quantitative climate change projections, asset vulnerability, and asset criticality data can be combined in a mixed-methods approach to qualitatively characterize climate change impact risks to highway culvert assets despite uncertainty in climate change projections and other inputs.

Esta tese investiga se eventos anômalos de precipitação pluviométrica (PP) na Planície Costeira do Rio Grande do Sul (PCRGS) estão relacionados a modos de variabilidade climática e como essa relação pode afetar o ambiente costeiro. A PP e suas anomalias foram estatisticamente correlacionadas aos modos de variabilidade climática, o Modo Anular do Hemisfério Sul (SAM) e El Niño - Oscilação Sul (ENOS). O índice do ENOS utilizado foi o Multivariate ENSO Index (MEI) e do SAM foi o de Nan e Li (2003). Para o cálculo das anomalias de PP foram utilizados dados do satélite Tropical Rainfall Measurement Mission, entre 1998 e 2013. As correlações foram calculadas por meio de matrizes de classificação, e suas significâncias pelo teste-t de Student. A área de estudo foi dividida em costas sul (33°44’39” – 32°09’36”S), central (32°09’36” – 30°10’12”S) e norte (30°10’12” – 29°19’34”S) e para cada uma delas foi escolhido um geoindicador (sangradouros ou lagunas), examinados em imagens de satélite. Comparouse os geoindicadores em períodos de PP anomalamente positiva e negativa. Para destacar as variações nos geoindicadores foram utilizadas composições RGB 543 dos sensores Thematic Mapper (TM) e Enhanced Thematic Mapper Plus (ETM+) do Landsat. Os resultados apontam para correlação negativa entre as anomalias de PP nas costas sul e central com o SAM e correlação positiva das anomalias de PP da costa sul com o MEI. A PP na costa norte não apresenta correlação com nenhum dos dois índices. Foram identificados 28 eventos anômalos de PP no período 1998-2013. Nas imagens de satélite todos geoindicadores apontaram para variações morfológicas e hídricas entre os períodos PP acima e abaixo da média, sendo a costa norte a que apresenta menor variação visível. A costa sul tem a menor média de PP e o maior número de eventos anômalos de PP, dos quais 67% eram de PP negativa. A maioria dos eventos são de PP negativa (78%) e podem estar relacionados simultaneamente ao SAM positivo e MEI negativo, ou somente ao MEI positivo. Todos eventos de PP positiva foram concomitantes ao MEI positivo. As costas sul e central mostram uma redução na PP média. Essa tendência pode estar relacionada as mudanças climáticas globais, pela intensificação do SAM positivo e de eventos El Niño e La Niña. As variações observadas nos geoindicadores (sangradouros ou lagunas) indicam que a redução na PP média resulta em menor volume de sedimentos transportados do pós praia para a zona de arrebentação e face praial, alterando o balanço sedimentar. As areias secas dos campos de dunas transportadas pelo vento podem assorear lagos e lagunas da área de estudo, desequilibrando o ecossistema. / This thesis investigates whether anomalous events of precipitation (PP) in the Coastal Plain of Rio Grande do Sul (RGSCP) are related to climate variability modes and how this relationship can affect the coastal environment. The PP and its anomalies were statistically correlated to climate variability modes, the Southern Annular Mode (SAM) and El Niño-Southern Oscillation (ENSO). The used ENSO index was the Multivariate ENSO Index (MEI) and SAM is the one defined by Nan and Li (2003). For the calculation of the PP anomalies, we used data from the Tropical Rainfall Measurement Mission satellite, from 1998 to 2013. Correlations were calculated using classification matrices, and their significance by the the Student t-test. The study area was divided into south (33°44'39" – 32°09'36"S), central (32°09'36"– 30°10'12"S) and north (30°10'12"– 29°19'34"S) coasts and for each one it was chosen a geoindicador (washouts or lagoons), examined on satellite images. This investigation compared the geoindicators in positive and negative anomalous PP periods. To highlight variations in the geoindicators, it was used the RGB 543 composition of the Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) Landsat sensors. The results point to a negative correlation of the PP anomalies in the southern and central coasts with the SAM and a positive correlation of PP anomalies in the south coast with the MEI. The north coast PP is not correlated with any of the two indexes. Twenty-eight anomalous PP events were found in the 1988–2013 period. In satellite images, all geoindicators pointed to morphological and hydrological variations between periods of PP above and below the mean, the northern coast has the least visible variations. The south coast has the lowest mean PP and the largest number of anomalous events, of which 67% were negative PP. The majority of events are negative PP (78%), they could be simultaneously connected to a positive SAM and a negative MEI, or only to a positive MEI. All positive PP events were concomitant to a positive MEI. The central and southern coasts show a decrease in the men PP. This trend may be related to global climate change, by the intensification of the positive SAM and of El Niño and La Niña events. The variations observed in geoindicators (washouts or lagoons) indicate that the reduction in the mean PP results in lower volume of sediments transported from the backshore to the surf zone and the shoreface, changing the sedimentary balance. The dry sands from the wind-transported dune fields could silt up lakes and lagoons of the study area, unbalancing the ecosystem.

Esta tese investiga se eventos anômalos de precipitação pluviométrica (PP) na Planície Costeira do Rio Grande do Sul (PCRGS) estão relacionados a modos de variabilidade climática e como essa relação pode afetar o ambiente costeiro. A PP e suas anomalias foram estatisticamente correlacionadas aos modos de variabilidade climática, o Modo Anular do Hemisfério Sul (SAM) e El Niño - Oscilação Sul (ENOS). O índice do ENOS utilizado foi o Multivariate ENSO Index (MEI) e do SAM foi o de Nan e Li (2003). Para o cálculo das anomalias de PP foram utilizados dados do satélite Tropical Rainfall Measurement Mission, entre 1998 e 2013. As correlações foram calculadas por meio de matrizes de classificação, e suas significâncias pelo teste-t de Student. A área de estudo foi dividida em costas sul (33°44’39” – 32°09’36”S), central (32°09’36” – 30°10’12”S) e norte (30°10’12” – 29°19’34”S) e para cada uma delas foi escolhido um geoindicador (sangradouros ou lagunas), examinados em imagens de satélite. Comparouse os geoindicadores em períodos de PP anomalamente positiva e negativa. Para destacar as variações nos geoindicadores foram utilizadas composições RGB 543 dos sensores Thematic Mapper (TM) e Enhanced Thematic Mapper Plus (ETM+) do Landsat. Os resultados apontam para correlação negativa entre as anomalias de PP nas costas sul e central com o SAM e correlação positiva das anomalias de PP da costa sul com o MEI. A PP na costa norte não apresenta correlação com nenhum dos dois índices. Foram identificados 28 eventos anômalos de PP no período 1998-2013. Nas imagens de satélite todos geoindicadores apontaram para variações morfológicas e hídricas entre os períodos PP acima e abaixo da média, sendo a costa norte a que apresenta menor variação visível. A costa sul tem a menor média de PP e o maior número de eventos anômalos de PP, dos quais 67% eram de PP negativa. A maioria dos eventos são de PP negativa (78%) e podem estar relacionados simultaneamente ao SAM positivo e MEI negativo, ou somente ao MEI positivo. Todos eventos de PP positiva foram concomitantes ao MEI positivo. As costas sul e central mostram uma redução na PP média. Essa tendência pode estar relacionada as mudanças climáticas globais, pela intensificação do SAM positivo e de eventos El Niño e La Niña. As variações observadas nos geoindicadores (sangradouros ou lagunas) indicam que a redução na PP média resulta em menor volume de sedimentos transportados do pós praia para a zona de arrebentação e face praial, alterando o balanço sedimentar. As areias secas dos campos de dunas transportadas pelo vento podem assorear lagos e lagunas da área de estudo, desequilibrando o ecossistema. / This thesis investigates whether anomalous events of precipitation (PP) in the Coastal Plain of Rio Grande do Sul (RGSCP) are related to climate variability modes and how this relationship can affect the coastal environment. The PP and its anomalies were statistically correlated to climate variability modes, the Southern Annular Mode (SAM) and El Niño-Southern Oscillation (ENSO). The used ENSO index was the Multivariate ENSO Index (MEI) and SAM is the one defined by Nan and Li (2003). For the calculation of the PP anomalies, we used data from the Tropical Rainfall Measurement Mission satellite, from 1998 to 2013. Correlations were calculated using classification matrices, and their significance by the the Student t-test. The study area was divided into south (33°44'39" – 32°09'36"S), central (32°09'36"– 30°10'12"S) and north (30°10'12"– 29°19'34"S) coasts and for each one it was chosen a geoindicador (washouts or lagoons), examined on satellite images. This investigation compared the geoindicators in positive and negative anomalous PP periods. To highlight variations in the geoindicators, it was used the RGB 543 composition of the Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) Landsat sensors. The results point to a negative correlation of the PP anomalies in the southern and central coasts with the SAM and a positive correlation of PP anomalies in the south coast with the MEI. The north coast PP is not correlated with any of the two indexes. Twenty-eight anomalous PP events were found in the 1988–2013 period. In satellite images, all geoindicators pointed to morphological and hydrological variations between periods of PP above and below the mean, the northern coast has the least visible variations. The south coast has the lowest mean PP and the largest number of anomalous events, of which 67% were negative PP. The majority of events are negative PP (78%), they could be simultaneously connected to a positive SAM and a negative MEI, or only to a positive MEI. All positive PP events were concomitant to a positive MEI. The central and southern coasts show a decrease in the men PP. This trend may be related to global climate change, by the intensification of the positive SAM and of El Niño and La Niña events. The variations observed in geoindicators (washouts or lagoons) indicate that the reduction in the mean PP results in lower volume of sediments transported from the backshore to the surf zone and the shoreface, changing the sedimentary balance. The dry sands from the wind-transported dune fields could silt up lakes and lagoons of the study area, unbalancing the ecosystem.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-09-27T14:34:11Z No. of bitstreams: 1 ALBERTO SMITH MARTÍNEZ - DISSERTAÇÃO PPGMet 1990..pdf: 13526465 bytes, checksum: 4046ef5126ade3f308837da19a9332af (MD5) / Made available in DSpace on 2018-09-27T14:34:11Z (GMT). No. of bitstreams: 1 ALBERTO SMITH MARTÍNEZ - DISSERTAÇÃO PPGMet 1990..pdf: 13526465 bytes, checksum: 4046ef5126ade3f308837da19a9332af (MD5) Previous issue date: 1990-12-19 / Capes / O re 1 ac ionamrnt o entre o fenómeno El Niño/Oscilação do Sul (FNSO) e a precipitação no Panamá foi estudado para o período de 1967 a 1986 mediante a utilização de dados de totais mensais e de anomalias de precipitação, cartas de anomalias de precipitação, dados e composições da anomalia da temperatura da superfície do mar (TSM) na costa do Peru e proximidades, e por uma análise estatística simples. Os resultados indicam que durante os anos ENSO a precipitação ap resen t a-se, em média, IP, 7'/. abaixo do normal. Porém, há regiões com anomalias negativas de até 50% devido á considerável variabilidade espacial de precipitação. A estação chuvosa (abri1-novembro) é interrompida por desvios negativos predominantes nos meses de julho e agosto ocasionando uma significativa redução de precipitação durante a estação. Correlações efetuadas indicam uma estreita relação negativa entre a precipitação P O sinal do FNSO, com os mais altos Índices para os atrasos ("lag") de 3 meses, sugerindo que a precipitação total de um mês pode spr prevista com antecedência através dos dados da TSM. Mediante os resultados obtidos neste estudo e pelas descrições do comportamento do sistema oceano-atmos fera durante o ENSO apresentadas por vários pesquisadores conclue-se que é o deslocamento anómalo da 7ona de Convergência Intertropical (ITCZ), principal fator de precipitação no Panamá, o maior responsável pelas anomalias de precipitação apresentadas no pais durante o evento. / Thp relationship bptwppn thp El Nino/Southern Oscillation (ENSO) phenomenon and Panamá precipitation was studied for the period 1967-1986 using precipitation composites and total means, deviation maps of precipitation, sea surface temperature anomalies data from Peru coast and proximities and a simple statistic analysis. Results indicate that during the ENSO years the precipitation show, on the average, 12.7% below normal. However a considerable precipitation variability in space exhibit regions with negatives anomalies up to 5<Ò'Á. The rainy season (AprilNovember) is interrupted by negatives deviations prevailing on the months of July and August causing a significative reduction in precipitation during the season. Correlations indicates a close negative relation between precipitation and the ENSO signal, introducing the most higher indexes for delay ("lag") of 3 months and indicating that a month total precipitation can be expected in advance with the TSM data. With the results on this study and descriptions of the ocean-atmosphere system behaviour during the ENSO presented by various researchers, we may conclude that the anomaly shift of the Inter-Tropical Convergence Zone (ITCZ), mainly factor of precipitation on Panamá, is the major responsible for the precipitation anomalies presented in the country during the event.

Growth and development in the context of climate change and environmental challengesare issues of increasing importance in the economic debate. With higher levels of greenhousegases in the atmosphere, droughts and other forms of extreme weather are expected to increasein frequency. Some of the worst affected are people living in sub-Saharan African countries. However, there are literature showing that countries who diversify their production becomesmore resilient against negative shocks. This study aims to determine the relationship betweenprecipitation anomalies and GDP per capita growth under different levels of concentrationof the export portfolio, in order to understand what kind of diversification reduces economicrisks connected to precipitation. Precipitation anomalies, such as abnormally heavy rainfallor droughts, is seen as a good measurement for climate change, and can thus be treated aseconomic shocks. We are using data on export product shares and monthly precipitation todetermine whether the level of sectoral diversification in exports affects the influence precipitation anomalies have on GDP per capita growth. The effects are estimated using a two-stageleast squares model, only targeting countries in SSA for our estimations. The results show thatpositive weather anomalies correlate with lower levels of GDP per capita growth. But the samenegative trend cannot be seen for negative precipitation anomalies. The results also show thatthe level of diversification within exports does not have any significant effect on the influencethat precipitation anomalies have on GDP per capita growth.