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A região do Vale do Paraíba, situada em uma planície cortada pelo Rio Paraíba do Sul, entre as Serras da Mantiqueira e do Mar, possui alternância entre períodos secos e chuvosos, alcançando cerca de 1300 mm por ano. Todas estas características físicas somadas à disposição de moradias em várzeas e áreas com alta declividade contribuem para a ocorrência de desastres naturais. Deste modo, foi realizado o levantamento da vulnerabilidade climática aos desastres naturais da região do Vale do Paraíba. A pesquisa foi dividida em duas partes, passado e futuro. No passado (1990-2008) a região apresentou municípios vulneráveis aos desastres naturais como São José dos Campos, Jacareí, Campos dos Jordão, Taubaté e Aparecida. Os desastres naturais de maior ocorrência foram às inundações (54%) e as tempestades severas (25%) com maior frequência nos meses de janeiro, fevereiro e março. Para o futuro foram analisados dados de precipitação (2070-2100) para os cenários A2 e B2, a partir dos dados de simulação climática futura, modelo ETA/CCS, pela técnica de downscaling dinâmico, o modelo apontou para redução da precipitação na região, sendo de 44% para o cenário A2 e 35% para o cenário B2. Além da redução no total de precipitação, os dados futuros apontam para o aumento do período de dias de permanência de chuva, com predomínio de chuvas leves (0,1 a 5 mm), ou seja, haverá redução nos eventos extremos de precipitação, o que contribuiria para a diminuição de processos geradores de desastres naturais na região do Vale do Paraíba. / The region of Paraíba Valley, situated on a plain crossed by Paraiba do Sul River, between Mantiqueira and Mar mountain rigdes, alternates dry and wet periods, getting about 1300 mm of rain per year. The physical characteristics combined with the location of homes in low and flat lands alongside a watercourse and in areas with steep slopes contribute to the occurrence of natural disasters. This study of climate vulnerability and natural disasters in the region of Paraíba Valley. This research is divided into two parts: past and future. In the past (1990-2008) the region has vulnerable cities to natural disasters. Such as São José dos Campos, Jacareí, Campos do Jordão, Taubaté, and Aparecida. In these cities, the predominant natural disasters were floods (54%) and severe storms (25%) that occur frequently in the months of January, February and March. For the future precipitation data modeled (2070-2100) were analyzed for the scenarios A2 and B2 of IPCC, from the data of future climate simulation, (ETA / CCS model) by applying the dynamic downscaling technique. The model indicates reduced precipitation in the region (44% for A2 scenario and 35% for scenario B2). Besides the reduction in total precipitation, the future data point to the increase in the number of rainy days with the predominancy of ligth rains (0.1 to 5 mm), so, it will have a reduction in extreme precipitation events that could contribute to a decrease of natural disaster generating processes in the region of Paraíba Valley.

The tourism sector in Stockholms city, Sweden, is a dynamic industry that through the years has generated large revenues and job openings. Unpredictable events such as terrorism, pandemics, natural disasters and climate changes, may have great imapct on the tourism sector. This may be true to most cities in the world including Stockholm. in this thesis, the effect of various unpredictable events has been investigated through interviews with city of Stockholm and the authority for community protection and preparedness. In use of strenghts, weaknesses, opportunities and threats (SWOT-analys). The main conclusion of this thesis is that the Covid-19 pandemic (year 2020) has shown that the emergency preparations for unpredictable events are incorrectly dimensiond. This means that the city of Stockholm needs to work more proactively in the future to ensure that the tourism sector is not jeopardized during upcoming unpredictable events.

La thèse étudie le risque météorologique et économique sous différents angles principalement dans les pays en développement. Elle se décompose en trois chapitres indépendants analysant dans diverses situations la corrélation des risques liés aux aléas météorologique et climatique ou économique, et étudie le potentiel de la région géographique étudiée pour mettre en place un système d’assurance contre le risque étudié. En effet, cette thèse étudie des risques très susceptibles d’être fortement corrélés : que cela concerne le risque météorologique ou climatique, ou le risque lié à la volatilité des prix, les villes voire pays voisins sont exposés aux mêmes risques et de façon simultanée. Cet aspect essentiel compromet la mutualisation du risque, paramètre primordial du modèle économique de l’assurance. A travers les trois chapitres de la thèse, nous étudierons le bénéfice lié à la mutualisation de ces risques a priori relativement corrélés. Le premier chapitre étudie la corrélation des prix du maïs en Tanzanie. A l’aide d’un modèle Copula-GARCH, la dépendance entre les cours du maïs des 20 marchés principaux du pays est modélisée et nous pouvons voir si le prix moyen du maïs est lissé en agrégeant les marchés. Cela permet de voir si l’intégration des marchés permet une efficace mutualisation du risque lié à la volatilité des prix. Le second chapitre s’attache au risque cyclonique dans les îles Pacifique sud et son impact sur les infrastructures. Ce papier propose une modélisation des cyclones tropicaux dans la région étudiée et la distribution de probabilité des cyclones associés à leur force, permettant ainsi de tenir compte du climat actuel pour modéliser les coûts. Avec les données liées aux infrastructures, nous calculons le coût des cyclones, y compris pour les événements extrêmes de très faible probabilité. Le troisième chapitre propose une extension d’un émulateur statistique des rendements agricoles selon des variables climatiques. Nous modélisons l’impact de l’accroissement marginal de la température, des précipitations ou de la concentration en CO2 en faisant une estimation statistique sur des modèles de culture et non sur des données historiques. Cela permet de prendre en compte des effets extrêmes sur des valeurs météorologiques pas ou peu observées jusqu’à présent. La robustesse du modèle est évaluée, entre autres, à l’aide de copules pour comparer la dépendance spatiale entre le modèle et notre émulateur statistique et vérifier que notre estimation capture bien la dépendance géographique. / The PhD dissertation studies meteorological and economic hazard under different angles and mostly in developing countries. It is composed of three independent chapters analyzing different situations dealing with meteorological and climatic or economic hazard correlation. It estimates the potential of the studied regions for implementing an insurance scheme for the risk. Indeed, this thesis studies risks very likely to be highly correlated: whether this is for the meteorological or climatic hazard, or the price volatility risk, neighbored cities or even countries are exposed to the same risk simultaneously. This essential aspect jeopardizes risk mutualization, a key parameter of the economic insurance model. Through the three chapters of this thesis, we study the benefits linked to the mutualization of a priori correlated risks. The first chapter deals with maize price correlation in Tanzania. Using a Copula-GARCH model, we model the dependence among the 20 main markets of the country and assess if the mean maize price is smoothed by aggregating the markets. Hence, we see whether markets integration allows an efficient risk mutualization against the risk of price volatility. The second chapter deals with tropical storms risk in the South Pacific islands and their impact on infrastructures. This paper proposes an artificial tropical cyclones modeling in the region studied as well as the probability distribution of the cyclone’s occurrence and strength. This enables us accounting for the current climate for modeling costs. With data on infrastructures, we calculate the cost due to tropical storms, including for very low probability extreme events. The third chapter proposes an extension for a statistical emulator of crop yields depending climatic variables. We model the marginal impact of an increase of temperature, precipitations and CO2 concentration by running a statistical estimation on crop models rather than historical data. It allows accounting for extreme effects caused by meteorological data values not observed so far. The model robustness is assessed, among others, with copulas to compare the spatial dependence between the model and our statistical emulator and check that our estimation captures the geographic dependence.

abstract: Small island developing states (SIDS) are on the very frontlines of climate change (UNDP, 2017). Increasing attention on the unique social, economic, and environmental vulnerabilities SIDS face has led to the discussion of the overall resilience of this population. Specifically, post-disaster studies of resilience carried out on SIDS have pointed to social resilience and education as two primary indicators of the overall resilience of these vulnerable communities (Aldrich, 2012; Muttarak & Lutz, 2014); yet social aspects of resilience related to SIDS have been underexplored, in comparison to ecological and economic themes (Berkes & Ross, 2013). Thus, the purpose of this qualitative study was to explore the personal and professional lived-natural disaster experiences of SIDS residents who are educators in order to understand their role in building social resilience within their community. In-depth interviews were conducted with educators employed at public and private schools in the United States Virgin Islands. The findings indicate that residents who are educators conceptualized resilience according to the following themes and sub-themes: (1) Social Process which involves Social Recovery and Community Alliances to ‘bounce back’ to an undefined level of normalcy and (2) Embodied Identity which was described in terms of Community Personifications of resilience as a trait in general citizens and educators. Participants identified internal and external resources as influential in how residents responded to natural disasters, by so doing, significantly contributing to positive post-disaster outcomes; these resources are referred to in the literature as protective factors (Rutter, 1985). The findings also demonstrate that educators had both a personal and professional responsibility to help their community contend with disasters, and this outcome is best explicated through the concept of protective factors. The research findings are significant because they: (1) contribute to the limited body of literature on social resilience in small island developing states, (2) demonstrate the importance of subjective perspectives in the development of disaster preparedness and management strategies for climate-vulnerable island populations, and (3) indicate a need for future research to use terminology which acknowledges the many ways in which disaster-prone communities have historically demonstrated and/or embodied resilience. / Dissertation/Thesis / Masters Thesis Community Resources and Development 2020

The Caribbean is a complex region that heavily relies on its seasonal rainfall cycle for its economic and societal needs. This makes the Caribbean especially susceptible to hydro-meteorological disasters (e.g., droughts and floods), and other weather/climate risks. Therefore, effectively predicting the Caribbean rainfall cycle is valuable for the region. The efficacy of predicting the Caribbean rainfall cycle is largely dependent on effectively characterizing the climate dynamics of the region. However, the dynamical processes and climate drivers that shape the seasonal cycle are not fully understood, as previous observational studies show inconsistent findings as to what mechanisms influence the mean state and variability of the cycle. These inconsistencies can be attributed to the limitations previous studies have when investigating the Caribbean rainfall cycle, such as using monthly or longer resolutions in the data or analysis that often mask the seasonal transitions and regional differences of rainfall, and investigating the Caribbean under a basin-wide lens rather than a sub-regional lens. This inhibits the ability to accurately calculate and predict subseasonal-to-seasonal (S2S) rainfall characteristics in the region. To address these limitations and inconsistencies, the research in this thesis examines the seasonal climatology, variability, and characteristics of the Caribbean rainfall cycle under a sub-regional and temporally fine lens in order to investigate the prediction of the cycle. Regional variations and dynamical processes of the Caribbean annual rainfall cycle are assessed using (1) a principal component analysis across Caribbean stations using daily observed precipitation data; and, (2) a moisture budget analysis. The results show that the seasonal cycle of rainfall in the Caribbean hinges on three main facilitators of moisture convergence: the Atlantic Intertropical Convergence Zone (ITCZ), the Eastern Pacific ITCZ, and the North Atlantic Subtropical High (NASH). A warm body of sea-surface temperatures (SSTs) in the Caribbean basin known as the Atlantic Warm Pool (AWP) and a low-level jet centered at 925hPa over the Caribbean Sea known as the Caribbean Low-Level Jet (CLLJ) modify the extent of moisture provided by these main facilitators. The interactions of these dynamical processes are responsible for shaping the seasonal components of the annual rainfall cycle: The Winter Dry Season (WDS; mid-November to April); the Early-Rainy Season (ERS; mid-April to mid-June); an intermittent relatively dry period known as the mid-summer drought, (MSD; mid-June to late August), and the Late-Rainy Season (LRS; late August to late November). Five geographical sub-regions are identified in the Caribbean Islands, each with its unique set of dynamical processes, and consequently, its unique pattern of rainfall distribution throughout the rainy season: Northwestern Caribbean, the Western Caribbean, the Central Caribbean, the Central and Southern Lesser Antilles, and Trinidad and Tobago and Guianas. Convergence by sub-monthly transients contributes little to Caribbean rainfall. The wettest and driest Caribbean ERS and LRS years’ are then explored by conducting the following: (1) a spatial composite of rainfall using the daily rainfall data; and, (2) spatial composites of SSTs, sea-level pressure (SLP), and mean flow moisture convergence and transports using monthly data. The ERS and LRS are impacted in distinctly different ways by two different, and largely independent, large-scale phenomena, external to the region: a SLP dipole mode of variability in the North Atlantic known as the North Atlantic Oscillation (NAO), and the El Nino Southern Oscillation (ENSO). Dry ERS years are associated with a persistent dipole of cold and warm SSTs over the Caribbean Sea and Gulf of Mexico, respectively, that are caused by a preceding positive NAO state. This setting involves a wind-evaporation-SST (WES) feedback expressed in enhanced trade winds and consequently, moisture transport divergence over all of the Caribbean, except in portions of the Northwestern Caribbean in May. A contribution from the preceding winter cold ENSO event is also discernible during dry ERS years. Dry LRS years are due to the summertime onset of an El Niño event, developing an inter-basin SLP pattern that moves moisture out of the Caribbean, except in portions of the Northwestern Caribbean in November. Both large-scale climate drivers would have the opposite effect during their opposite phases leading to wet years in both seasons. Existing methodologies that calculate S2S rainfall characteristics were not found to be suitable for a region like the Caribbean, given its complex rainfall pattern; therefore, a novel and comprehensive method is devised and utilized to calculate onset, demise, and MSD characteristics in the Caribbean. When applying the method to calculate S2S characteristics in the Caribbean, meteorological onsets and demises, which are calculated via each year’s ERS and LRS mean thresholds, effectively characterize the seasonal evolution of mean onsets and demises in the Caribbean. The year-to-year variability of MSD characteristics, and onsets and demises that are calculated by climatological ERS and LRS mean thresholds resemble the variability of seasonal rainfall totals in the Caribbean and are statistically significantly correlated with the identified dynamical processes that impact each seasonal component of the rainfall cycle. Finally, the seasonal prediction of the Caribbean rainfall cycle is assessed using the identified variables that could provide predictive skill of S2S rainfall characteristics in the region. Canonical correlation analysis is used to predict seasonal rainfall characteristics of station-averaged sub-regional frequency and intensity of the ERS and LRS wet days, and magnitude of the MSD. Predictor fields are based on observations from the ERA-Interim reanalysis and GCM output from the North America Multi-Model Ensemble (NMME). Spearman Correlation and Relative Operating Characteristics are applied to assess the forecast skill. The use of SLP, 850-hPa zonal winds (u850), vertically integrated zonal (UQ), and meridional (VQ) moisture fluxes show comparable, if not better, forecast skill than SSTs, which is the most common predictor field for regional statistical prediction. Generally, the highest ERS predictive skill is found for the frequency of wet days, and the highest LRS predictive skill is found for the intensity of wet days. Rainfall characteristics in the Central and Eastern Caribbean have statistically significant predictive skill. Forecast skill of rainfall characteristics in the Northwestern and Western Caribbean are lower and less consistent. The sub-regional differences and consistently significant skill across lead times up to at least two months can be attributed to persistent SST/SLP anomalies during the ERS that resemble the North Atlantic Oscillation pattern, and the summer-time onset of the El Niño-Southern Oscillation during the LRS. The spatial pattern of anomalies during the MSD bears resemblance to both the ERS and LRS spatial patterns. The findings from this thesis provide a more comprehensive and complete understanding of the climate dynamics, variability, and annual mean state of the Caribbean rainfall cycle. These results have important implications for prediction, decision-making, modeling capabilities, understanding the genesis of hydro-meteorological disasters, investigating rainfall under other modes of variability, and Caribbean impact studies regarding weather risks and future climate.

Thesis advisor: Rebekah L. Coley / Recent decades have witnessed the increasing spatial concentration of poverty and affluence in the United States (Biscoff & Reardon, 2013). Given well-documented links between neighborhood economic contexts and wellbeing (Chow et al., 2005), this has the potential to exacerbate disparities in health, particularly for people with limited neighborhood choice. However, limited research has systematically examined the neighborhood features underlying these links. A more nuanced understanding of why neighborhood poverty matters is essential for promoting equitable neighborhood development. Using rigorous analytic techniques that account for the dynamic nature of neighborhoods and help adjust for selection bias, I considered two complementary questions: 1) do observed neighborhood resources and stressors mediate associations between neighborhood poverty and wellbeing within and between individuals; and 2) how do observed versus perceived changes in neighborhood features mediate links between neighborhood poverty and wellbeing? I combined individual-level longitudinal data from the Post-Katrina Study of Resilience and Recovery with administrative neighborhood data drawn from the Census Bureau, FBI, and EPA. Analyses focused on a sample of 606 participants – primarily young Black mothers with low levels of income – who were affected by Hurricane Katrina, most of whom experienced some period of forced relocation. Participants were surveyed once before (2003/04) and twice after (2006/07; 2009) the hurricane. Results paint a complex picture. Contrasting with prior research, total effects of neighborhood poverty on wellbeing were limited. However, changes in neighborhood poverty were linked to wellbeing indirectly through intermediary neighborhood features, with results pointing to benefits and detriments of rising neighborhood poverty. Results were driven by those who changed neighborhoods over the course of the study. For participants that lived in the same New Orleans neighborhood across waves, changes in neighborhood poverty proved less consequential. Overall, results suggest that rather than treating neighborhood poverty as uniformly problematic for wellbeing, efforts to promote health equity should identify and build upon existing assets of neighborhoods, like affordability and amenity access, while also reducing stressors. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Lynch School of Education. / Discipline: Counseling, Developmental and Educational Psychology.

En el Perú, existe una gran necesidad de reducir el impacto de los desastres naturales ocasionados por el fenómeno El Niño, ya que genera cuantiosas pérdidas, algunas pueden ser tanto humanas como materiales. Este evento hidro-climático, que azotó al país por última vez en el año 2017, evidenció que no existen soluciones tecnológicas para reducir las consecuencias de este tipo de acontecimientos. Por tal motivo, el presente proyecto pretende, analizar los principales peligros e impacto de los desastres naturales del fenómeno “El Niño” en el Perú, la aplicación de las TIC que hoy en día se utilizan en la gestión de desastres naturales, el diseño de un catálogo de soluciones tecnológicas incluyendo para cada una su arquitectura física y el costo aproximado de implementación, la validación de las soluciones tecnológicas a través de expertos en desastres climatológicos e investigación tecnológica, y por último, definir una hoja de ruta para la implementación de las soluciones tecnológicas propuestas. Se espera que el catálogo ayude a las entidades peruanas públicas o privadas, encargadas de la gestión de desastres naturales, a poner en marcha soluciones TIC que supongan una mejora y un mejor resultado en la atención de desastres sin necesidad de tener un amplio conocimiento sobre las TIC y que brinden una gama de posibilidades tanto en la diversidad de componentes que conforma cada solución tecnológica y costos. / In Peru, there is a great need to reduce the impact of natural disasters caused by the El Niño southern oscillation phenomenon (ENSO), since it generates large losses both human and material. This hydro-climatic event, which hit the country for the last time in 2017, showed that there are no technological solutions to reduce the consequences of this type of events. For this reason, this project aims to analyze the main dangers and impact of natural disasters of the "El Niño" phenomenon in Peru, the application of ICT that are used today in the management of natural disasters, design a catalog of technological solutions including, for each one, its physical architecture and the approximate cost of implementation, the validation of the technological solutions through experts in climatological disasters and technological research, and finally, define a Roadmap for the proposed technological solutions. It is expected that the catalog will help Peruvian public or private entities, in charge of natural disaster management, to implement ICT solutions that will improve and improve disaster response without needing to have extensive knowledge about the ICT and that offer a range of possibilities both in the diversity of components that make up each technological solution and costs. / Tesis

Una de las preocupaciones que mayormente tienen los países en vías de desarrollo es el efecto de los desastres naturales sobre la educación. Por este motivo, la presente investigación realiza un análisis del efecto de los desastres naturales: Heladas e inundaciones, sobre la generación de resultados educativos, medido como puntaje de pruebas estandarizadas de matemática y lenguaje. Además, se analiza si la tipología de estos desastres podría implicar resultados diferenciados. Para ello, se aplica un modelo de efectos aleatorios con una base de datos panel disponible del estudio Young Lives (Niños del Milenio). En efecto, el estudio confirma la hipótesis de que los desastres naturales evaluados influyen en los resultados educativos por el lado de riqueza del hogar y estado de salud del estudiante. / One of the concerns that developing countries have mostly is the effect of natural disasters on education. Therefore, the present investigation carries out an analysis of the effect of natural disasters: Frost and floods, on the generation of educational results, measured as a standardized math and language test score. Furthermore, whether the typology of these disasters could imply differentiated results. For this, a random effects model is applied with a panel database available from the Young Lives study. Hence, the study confirms the hypothesis that the natural disasters evaluated influence educational outcomes on the side of household wealth and student health status. / Trabajo de investigación

Many studies find support that natural disaster events and post-conflict episodes increase the risk of organized violence. However, few are found to investigate if post-conflict countries become more violent in the aftermath of natural disasters. By combining research on post-conflict violence, natural disasters, and non-state violence, it is argued in this study that disasters such as earthquakes, floods, and pandemics strain the capacities of all governments, and in post-conflict countries, the weakened capacities of governments can cause public security gaps. These power vacuums, as a result of natural disasters, can incentivize non-state groups to expand and compete for control, and consequently causes the severity of violence to increase. This argument is estimated on country-year data consisting of 64 post-conflict countries between 1989‒2015. A statistically significant correlation between natural disasters and the increased severity of non-state violence is found when testing the argument using Ordinary Least Squares (OLS) and logistic regression, control variables, and different dependent variables. However, due to limiting factors in the statistical models, the results are deemed too ambivalent to fully support the hypothesis.