Dissertationen zum Thema „Climate databases“

L’augmentation globale des températures au cours de la période 1850-2012 n’est pas uniforme à l’échelle du globe et l’Arctique se réchauffe deux fois plus que la moyenne. Cependant, la couverture temporelle trop courte des données instrumentales rend difficile la distinction entre la variabilité climatique naturelle et celle liée au forçage anthropique. L’étude de la variabilité climatique « exempte » de l’influence humaine est alors réalisée à partir de données proxies indirectes provenant d’archives paléoclimatiques continentales et marines. Dans la région Arctique-subarctique, les enregistrements disponibles à haute résolution sur les derniers 2000 ans ont été centralisé dans la base de données PAGES Arctic 2k. Les objectifs de ces travaux sont l’amélioration de la caractérisation et de l’interprétation de la variabilité climatique sur les derniers 2000 ans, en allant plus loin que la tendance millénaire et les périodes climatiques majeures mais aussi en s'intéressant au rôle et l’expression spatiale de la variabilité interne du système climatique. Cette thèse s'appuie sur la base de données PAGES Arctic 2k permettant l'étude des variations de températures dans la région Arctique-subarctique mais aussi d'une nouvelle base de données permettant de reconstruire les variations hydroclimatiques (précipitations et humidité) dans la région et créée lors de cette étude. L'utilisation de méthodes d'analyse du signal climatique sur des enregistrements régionaux calculés à partir de ces deux bases de données a permis de mettre en évidence une variabilité climatique dans la région Arctique-subarctique s’exprimant depuis les échelles multi-décennales à millénaire. En particulier, les variabilités multi-décennales sont en lien avec la variabilité interne du système climatique. Les variations hydroclimatiques et de températures s'exprimant aux échelles multi-décennales dans la région sont en effet caractérisées par des fréquences spécifiques aux oscillations climatiques régionales (oscillation Atlantique Nord et oscillation Pacifique décennale), en particulier sur les derniers 200 ans. Les travaux réalisés sur la base de données de températures et la réflexion autour de la création et l’exploitation de la base de données hydroclimatiques ont également conduit à la définition d’une méthodologie de travail avec une base de données paléoclimatiques, depuis sa construction jusque la définition de ses limites, notamment en termes de représentativité spatiale des séries contenues dans la base de données et de l'assimilation de données avec des saisonnalités différentes
The temperature increase during the 1850-2012 period is not uniform globally and the Arctic is warming twice as much as the average. However, the short time coverage of instrumental data makes it difficult to distinguish natural climate variability and anthropogenic forcing. The study of climatic variability "free" of human influence requires the use of proxies data measured in continental and marine palaeoclimatic archives. In the Arctic-subarctic region, high resolution records have been centralized in the Arctic 2k PAGES database. The objectives of this work are to improve the characterization and interpretation of climatic variability over the last 2000 years, going beyond the millennial trend and the major climatic periods, but also by focusing on the role and spatial expression of the internal variability of the climate system. This thesis is based on the Arctic 2k PAGES database, which allows the study of temperature variations in the Arctic-subarctic region, as well as a new database to reconstruct hydroclimatic variations (precipitation and humidity) in the region and created during this study. The use of climate signal analysis methods on regional records calculated from these two databases has highlighted climate variability in the Arctic-subarctic region from the multi-decadal to millennial scales.In particular, multi-decadal variability is related to the internal variability of the climate system. The hydroclimatic and temperature variations expressed at multi-decadal scales in the region are characterized by frequencies specific to regional climate oscillations (North Atlantic oscillation and decadal Pacific oscillation), particularly over the last 200 years. The work done on the temperature database and the reflection on the creation and exploitation of the hydroclimatic database have also led to the definition of a working methodology with a palaeoclimatic database, from its construction to the definition of its limits, in particular in terms of the spatial representability of the series contained in the database and the assimilation of data with different seasonings

Les sols sont la principale composantede l’écosystème terrestre et le plus grand réservoir de carbone organique sur Terre, étant très réactifs aux perturbations humaines et aux changements climatiques. Malgré leur importance dans les réservoirs de carbone, la dynamique du carbone des sols est une source importante d'incertitudes pour les prévisions climatiques futures. Le but de la thèse était d'explorer différents aspects d’études du carbone des sols (mesures expérimentales, modélisation et évaluation de bases de données) à différentes échelles spatiales (de l'échelle d'un profil à l'échelle globale). Nous avons souligné que l'estimation des stocks globaux de carbone du sol est encore assez incertaine.Par conséquent le rôle du carbone des sols dans la dynamique du climat devient l'une des principales incertitudes dans les modèles du système terrestre utilisés pour prédire les changements climatiques futurs. La deuxième partie de la thèse porte sur la présentation d'une nouvelle version du modèle IPSL-Land Surface appelé ORCHIDEE-SOM, intégrant la dynamique du 14C dans le sol. Plusieurs tests effectués supposent que les améliorations du modèle devraient se focaliser davantage sur une paramétrisation dépendante de la profondeur,principalement pour la diffusion, afin d'améliorer la représentation du cycle global du carbone dans les modèles de surface terrestre, contribuant ainsi à contraindre les prédictions futures du réchauffement climatique
Soils are the major components ofthe terrestrial ecosystems and the largest organiccarbon reservoir on Earth, being very reactive tohuman disturbance and climate change. Despiteits importance within the carbon reservoirs, soilcarbon dynamics is an important source ofuncertainties for future climate predictions. Theaim of the thesis was to explore different aspectsof soil carbon studies (Experimentalmeasurements, modeling, and databaseevaluation) at different spatial scales (from thescale of a profile to the global scale). Wehighlighted that the estimation of the global soilcarbon stocks is still quite uncertain.Consequently, the role of soil carbon in theclimate dynamics becomes one of the majoruncertainties in the Earth system models (ESMs)used to predict future climate change. Thesecond part of thesis deals with the presentationof a new version of the IPSL-Land SurfaceModel called ORCHIDEE-SOM, incorporatingthe 14C dynamics in the soil. Several tests doneassume that model improvements should focusmore on a depth dependent parameterization,mainly for the diffusion, in order to improve therepresentation of the global carbon cycle inLand Surface Models, thus helping to constrainthe predictions of the future soil organic carbonresponse to global warming

Examination of empirical research confirmed that climate change is a complex problem of anthropological origin and revealed the need for a management framework to facilitate strategic decisions aimed at mitigating a rise in global temperatures of 2-°C linked to irresponsible and unsustainable business practices. The purpose of this simulation study was to develop a management framework of resilience, robustness, sustainability, and adaptive-capacity (RRSA) for organizations viewed as complex systems to address the current unsustainable state. As such, the evolutionary-RRSA prisoner's dilemma (PD) simulation was developed using an evolutionary game theory approach to agent based modeling and simulation, to generate data. Regression analyses tested the relationships between organizational resilience (x1), robustness (x2), and sustainability (x3) as independent variables, and the dependent variable of adaptive capacity (y) for cooperative and defective strategies. The findings were that complex nonlinear relationships exist between resilience, robustness, sustainability, and adaptive-capacity, which is sensitive to initial conditions and may emerge and evolve from combinations of cooperative and defective decisions within the evolutionary RRSA PD management tool. This study resulted in the RRSA management framework, a cyclical 4-phased approach, which may be used by climate governance leaders, negotiators, and policy-makers to facilitate strategy to move global climate change policy forward by guiding bottom-up consumption and production of GHGs, thereby improving adaptive-capacity, while mitigating an increase in global temperatures of 2-°C, which in turn would improve global socio-economic conditions.

Esta tese apresenta novos metodos baseados na teoria dos fractais e em tecnicas de mineração de dados para dar suporte ao monitoramento agrícola em escala regional, mais especicamente areas com plantações de cana-de-açucar que tem um papel importante na economia brasileira como uma alternativa viavel para a substituição de combustíveis fósseis. Uma vez que o clima tem um grande impacto na agricultura, os agrometeorologistas utilizam dados climáticos associados a índices agrometeorológicos e mais recentemente dados provenientes de satélites para apoiar a tomada de decisão. Neste sentido, foi proposto um método que utiliza a dimensão fractal para identicar mudanças de tendências nas séries climáticas juntamente com um módulo de análise estatística para definir quais atributos são responsáveis por essas alterações de comportamento. Além disso, foram propostos dois métodos de medidas de similaridade para auxiliar na comparação de diferentes regiões agrícolas representadas por múltiplas variáveis provenientes de dados meteorológicos e imagens de sensoriamento remoto. Diante da importância de se estudar os extremos climáticos que podem se intensicar dado os cenários que preveem mudanças globais no clima, foi proposto o algoritmo CLIPSMiner que identifica padrões relevantes e extremos em séries climáticas. CLIPSMiner também permite a identificação de correlação de múltiplas séries considerando defasagem de tempo e encontra padrões de acordo com parâmetros que podem ser calibrados pelos usuários. A busca por padrões de associação entre séries foi alcançada por meio de duas abordagens distintas. A primeira delas integrou o cálculo da correlação de dimensão fractal com uma técnica para tornar os valores contínuos das séries em intervalos discretos e um algoritmo de regras de associação gerando o método Apriori-FD. Embora tenha identificado padrões interessantes em relação a temperatura, este método não conseguiu lidar de forma apropriada com defasagem temporal. Foi proposto então o algoritmo CLEARMiner que de forma não-supervisionada minera padrões em uma série associando-os a padrões em outras séries considerando a possibilidade de defasagem temporal. Os métodos propostos foram comparados a técnicas similares e avaliados por um grupo composto por meteorologistas, agrometeorologistas e especialistas em sensoriamento remoto. Os experimentos realizados mostraram que a aplicação de técnicas de mineração de dados e fractais contribui para melhorar a análise dos dados agrometeorológicos e de satélite auxiliando no trabalho de pesquisadores, além de se configurar como uma ferramenta importante para apoiar a tomada de decisão no agronegócio
This thesis presents new methods based on fractal theory and data mining techniques to support agricultural monitoring in regional scale, specifically regions with sugar canefields. This commodity greatly contributes to the Brazilian economy since it is a viable alternative to replace fossil fuels. Since climate in uences the national agricultural production, researchers use climate data associated to agrometeorological indexes, and recently they also employed data from satellites to support decision making processes. In this context, we proposed a method that uses the fractal dimension to identify trend changes in climate series jointly with a statistical analysis module to define which attributes are responsible for the behavior alteration in the series. Moreover, we also proposed two methods of similarity measure to allow comparisons among different agricultural regions represented by multiples variables from meteorological data and remote sensing images. Given the importance of studying the extreme weather events, which could increase in intensity, duration and frequency according to different scenarios indicated by climate forecasting models, we proposed the CLIPSMiner algorithm to identify relevant patterns and extremes in climate series. CLIPSMiner also detects correlations among multiple time series considering time lag and finds patterns according to parameters, which can be calibrated by the users. We applied two distinct approaches in order to discover association patterns on time series. The first one is the Apriori-FD method that integrates an algorithm to perform attribute selection through applying the correlation fractal dimension, an algorithm of discretization to convert continuous values of series into discrete intervals, and a well-known association rules algorithm (Apriori). Although Apriori-FD has identified interesting patterns related to temperature, this method failed to appropriately deal with time lag. As a solution, we proposed CLEARMiner that is an unsupervised algorithm in order to mine the association patterns in one time series relating them to patterns in other series considering the possibility of time lag. The proposed methods were compared with similar techniques as well as assessed by a group of meteorologists, and specialists in agrometeorology and remote sensing. The experiments showed that applying data mining techniques and fractal theory can contribute to improve the analyses of agrometeorological and satellite data. These new techniques can aid researchers in their work on decision making and become important tools to support decision making in agribusiness

The Kentucky Mesonet is a high-density, mesoscale network of automated meteorological and climatological sensing platforms being developed across the commonwealth. Data communications, collection, processing, and delivery mechanisms play a critical role in such networks, and the World Meteorological Organization recognizes that “an observing system is not complete unless it is connected to other systems that deliver the data to the users.” This document reviews the implementation steps, decisions, and rationale surrounding communications and computing infrastructure development to support the Mesonet. A general overview of the network and technology-related research is provided followed by a review of pertinent literature related to in situ sensing network technology. Initial infrastructure design considerations are then examined followed by an in-depth review of the Mesonet communications and computing architecture. Finally, some general benefits of the Mesonet to the citizens of Kentucky are highlighted.

This thesis documents the development and application of a unique database orientated software package, BugsCEP, for environmental and climatic reconstruction from fossil beetle (Coleoptera) assemblages. The software tools are described, and the incorporated statistical methods discussed and evaluated with respect to both published modern and fossil data, as well as the author’s own investigations.

BugsCEP consists of a reference database of ecology and distribution data for over 5 800 taxa, and includes temperature tolerance data for 436 species. It also contains abundance and summary data for almost 700 sites - the majority of the known Quaternary fossil coleopteran record of Europe. Sample based dating evidence is stored for a large number of these sites, and the data are supported by a bibliography of over 3 300 sources. Through the use of built in statistical methods, employing a specially developed habitat classification system (Bugs EcoCodes), semi-quantitative environmental reconstructions can be undertaken, and output graphically, to aid in the interpretation of sites. A number of built in searching and reporting functions also increase the efficiency with which analyses can be undertaken, including the facility to list the fossil record of species found by searching the ecology and distribution data. The existing Mutual Climatic Range (MCR) climate reconstruction method is implemented and improved upon in BugsCEP, as BugsMCR, which includes predictive modelling and the output of graphs and climate space maps.

The evaluation of the software demonstrates good performance when compared to existing interpretations. The standardization method employed in habitat reconstructions, designed to enable the inter-comparison of samples and sites without the interference of differing numbers of species and individuals, also appears to be robust and effective. Quantitative climate reconstructions can be easily undertaken from within the software, as well as an amount of predictive modelling. The use of jackknifing variants as an aid to the interpretation of climate reconstructions is discussed, and suggested as a potential indicator of reliability. The combination of the BugStats statistical system with an enhanced MCR facility could be extremely useful in increasing our understanding of not only past environmental and climate change, but also the biogeography and ecology of insect populations in general.

BugsCEP is the only available software package integrating modern and fossil coleopteran data, and the included reconstruction and analysis tools provide a powerful resource for research and teaching in palaeo-environmental science. The use of modern reference data also makes the package potentially useful in the study of present day insect faunas, and the effects of climate and environmental change on their distributions. The reconstruction methods could thus be inverted, and used as predictive tools in the study of biodiversity and the implications of sustainable development policies on present day habitats.

BugsCEP can be downloaded from http://www.bugscep.com

This thesis builds on the work of previous coleopteran-based climatic reconstructions to recreate the environment and climate of the last 20,000 14C years of northwest Europe using the data and methods available within the Bugs Coleopteran Ecology Package, and aims to assess the ability of the BugsCEP results to provide information regarding events and anthropogenic changes on environment during the Anthropocene. Samples and data from 134 sites across northwest Europe and the British Isles were included in this study. The Mutual Climatic Range method and the BugStats module based on habitat code classifications were used to create the climatic and environmental reconstructions respectively, the results of which are provided in eight isotherm maps for 14.5-9 14C years BP and 2 EcoFigure graphs for 20,000 14C to present. While the results of some isotherm maps align with the changes described in previous studies, other climate trends are muted within these results. Likewise, some previously recognized environmental shifts in Europe are visible, whereas other major events are not distinguishable within the environmental record. An assessment of the environmental reconstruction results finds that though there is not sufficient material to support any proposed Anthropocene start dates, effects of anthropogenic influence upon the environment may be visible starting within the last 2,000 14C years; the results also show some support for the Vera Hypothesis.

Quaternary records provide an opportunity to examine the nature of the vegetation and fire responses to rapid past climate changes comparable in velocity and magnitude to those expected in the 21st-century. The best documented examples of rapid climate change in the past are the warming events associated with the Dansgaard–Oeschger (D–O) cycles during the last glacial period, which were sufficiently large to have had a potential feedback through changes in albedo and greenhouse gas emissions on climate. Previous reconstructions of vegetation and fire changes during the D–O cycles used independently constructed age models, making it difficult to compare the changes between different sites and regions. Here, we present the ACER (Abrupt Climate Changes and Environmental Responses) global database, which includes 93 pollen records from the last glacial period (73–15 ka) with a temporal resolution better than 1000 years, 32 of which also provide charcoal records. A harmonized and consistent chronology based on radiometric dating (¹⁴C, ²³⁴U∕²³⁰Th, optically stimulated luminescence (OSL), ⁴⁰Ar∕³⁹Ar-dated tephra layers) has been constructed for 86 of these records, although in some cases additional information was derived using common control points based on event stratigraphy. The ACER database compiles metadata including geospatial and dating information, pollen and charcoal counts, and pollen percentages of the characteristic biomes and is archived in Microsoft Access^TM at https://doi.org/10.1594/PANGAEA.870867.

July temperature (TJUL) and total annual precipitation (ANNP) are reconstructed to better understand the spatial and temporal patterns of change in North America over the last 2,000 years using pollen databases. Using a customized application in R, the reconstructions use a composite averaging of multiple site reconstructions that show a distinct warmer Medieval Warm Period (MWP) compared to the colder Little Ice Age (LIA). Results show that, both multi-centennial scale periods are re- constructed as cooler than the last 50 years. Regional time series from several forested ecoregions show positive anomalies up to 0.6ºC during the MWP and anomalies up to -0.3ºC during the LIA. In order to test whether the TJUL reconstructions are biased to the modern calibration climate data, we show a distinct difference between the reconstructions when using station versus reanalysis-based modern TJUL fields. Reconstructions using station-based modern calibration data sets better reflect the centennial to multi-centennial scale climate variability as compared to the reanalysis-based modern calibration data sets that reveal a warm-bias. We justify the choice of the Whitmore et al. (2005) modern data set for large-scale pollen-based paleoclimate reconstructions. Finally we use Local Indicators of Spatial Association (LISA) to spatially filter the ANNP reconstructions in order to distinguish regional hydroclimate patterns from local site-specific conditions. Results show that a La Nina, positive North Atlantic Oscillation (+NAO) and positive Atlantic Multidecadal Oscillation (+AMO) state-like dominated both the MWP and Roman Warm Period (RWP), although the MWP was generally drier. In contrast, the Dark Ages Cold (DAC) period was likely dominated by El Nino, negative NAO and negative AMO state-like circulation. Minimum solar and high volcanic activity is likely to have contributed to more complex hydroclimate regional patterns during the LIA. The results presented in this dissertation can be used as benchmark data sets for future climate data-model comparisons in order to improve our understanding of natural climate variability during the past 2,000 years in the context of modern human-induced climate change.

Le changement climatique et les invasions biologiques sont parmi les plus grandes menaces de la biodiversité et leurs impacts pourraient augmenter jusqu’à la fin du siècle. Parmi les espèces envahissantes, les fourmis sont un groupe particulièrement néfaste dû à leurs impacts sur les espèces natives, les processus écosystémique, la santé, l’agriculture et l’économie. L’objectif de cette thèse était de prédire les invasions de fourmis – en particulier avec le changement climatique qui pourrait favoriser les invasions en éliminant des barrières thermiques. J’ai utilisé trois approches complémentaires afin d’étudier le potentiel de différentes espèces à envahir : des modèles de distribution, des expériences comportementales et l’analyses d’une base de données de traits écologiques. J’ai modélisé l’aire favorable pour 15 espèces de fourmis parmi les pires, à la fois globalement, par continents, et dans les 34 hotspots de biodiversité. La distribution potentielle de seulement cinq espèce est prédite de diminuer (jusqu’à 35.8%) avec le changement climatique et l’aire potentielle diminue pour la plupart des espèces jusqu’à 63.2%. Les hotspots d’invasions de fourmis se situaient surtout dans des régions tropicales et subtropicales et ils correspondent particulièrement aux hotspots de biodiversité. Contrairement à ce qui est généralement admis, le changement climatique et les invasions biologiques n’agiront pas de manière synergique pour les fourmis. Par contre, les invasions de fourmis resteront probablement un problème global majeur, en particuliers dans les zones où les hotspots de biodiversité et les hotspots d’invasion se superposent. Les modèles de distribution ont identifié de larges zones de recouvrement entre aires favorables de plusieurs espèces de fourmis envahissantes. Dans le futur, ces espèces pourraient arriver simultanément dans les mêmes régions et entrer en compétition. Dans une série d’expériences, j’ai testé les différences comportementales entre 7 espèces de fourmis envahissantes (Anoplolepis gracilipes, Paratrechina longicornis, Myrmica rubra, Linepithema humile, Lasius neglectus, Wasmannia auropunctata et Pheidole megacephala). J’ai découvert deux stratégies comportementales différentes. Les interactions au niveau de la colonie ont suivi des processus démographiques plus complexes. De plus, j’ai mis au point deux expériences pour tester la capacité des fourmis envahissantes à explorer un nouvel espace et à exploiter des ressources. J’ai trouvé des différences significatives entre espèces et leur capacité à dominer par interférence comportementale était négativement corrélée à leurs capacités à découvrir et exploiter des ressources. Cette série d’expériences suggère que les ‘mécanismes’ d’invasion sont plus complexes que ce qui est généralement suggéré et que différentes espèces pourraient utiliser des stratégies comportementales différentes. Étant donné qu’il existe plus de 250 espèces de fourmis exotiques, il serait intéressant de pouvoir identifier à l’avance des futurs envahisseurs potentiels. Afin d’identifier des traits associés au caractère envahissant des fourmis, j’ai mis en place une base de données qui contient 2193 espèces de fourmis et 24 traits écologiques. J’ai effectué une analyse préliminaire de différences de traits entre fourmis natives et envahissantes qui a montré qu’il existe clairement des groupement distincts de natives et envahissantes, avec les espèces exotiques au milieu. Ces résultats pourraient servir de base pour construire un modèle prédictif des invasions de fourmis. Ces différentes approches (modèles, expériences, base de données) sont complémentaires car elles s’intéressent à des aspects différents du futur des invasions de fourmis qui sera vraisemblablement fortement influencé par le changement climatique. Le pires envahisseurs de demain ne seront probablement pas les même qu’aujourd’hui et les zones les plus à risque pourraient changer également
Climate change and biological invasions are both among the greatest threats to biodiversity and their impacts might increase by the end of the century. Among invasive species, ants are a prominent group due to their negative impacts on native species, ecosystem processes, human and animal health, agro-ecosystems and the economy. The objective of this thesis was to forecast future ant invasions – especially in the light of on-going climate change, which is generally thought to favour invasive species by removing thermal barriers. I used three complementary approaches to study the potential of different ant species to invade in the future: species distribution modelling, behavioural experiments and the analysis of a database of ecological traits. I modelled suitable area for 15 of the worst invasive ant species, both currently and with predicted climate change, globally, regionally and within the world’s 34 biodiversity hotspots. Surprisingly, the potential distribution of only five species was predicted to increase (up to 35.8%) with climate change, with most declining by up to 63.3%. The ant invasion hotspots are predominantly in tropical and subtropical regions of South America, Africa, Asia and Oceanic islands, and particularly correspond with biodiversity hotspots. Contrary to general expectations, climate change and biological invasions will not systematically act synergistically for ants. In addition, I found that the impacts of climate change can change over time and even reverse the trend of the impact (i.e., an increase instead of a decrease or vice versa). However, ant invasions will likely remain as a major global problem, especially where invasion hotspots coincide with biodiversity hotspots. The species distribution models have identified large potentially overlapping distributions of several invasive ants. In the future, these species may arrive simultaneously in the same regions and compete with each other. In a series of experiments, I tested behavioural differences among 7 highly invasive ant species (Anoplolepis gracilipes, Paratrechina longicornis, Myrmica rubra, Linepithema humile, Lasius neglectus, Wasmannia auropunctata and Pheidole megacephala). I discovered two different behavioural strategies among invasive ants. Interactions at the colony level, exhibited more complex demographic processes and more variability. Further, I investigated resource competition and differences in resource exploitation. I found significant differences among species, with competitive abilities that were negatively correlated with behavioural dominance. This series of experiments suggests that the ‘mechanisms’ of invasiveness are more complex than previously thought and that different invasive ant species may use different behavioural strategies. Since there are more than 250 exotic species of ants, it would be interesting to identify potential future invaders. In order to identify traits associated with invasiveness in ants, I set up a database with 2193 ant species and 24 ecological characteristics. I performed a preliminary analysis of trait differences between native and invasive ants that shows clearly different clusters of invasive and native species, with exotic species in between. These results could be used as a basis to construct a predictive model of future ant invasions. The different methods used (models, experiments, database) are complementary in that they explore different aspects of the future ant invasions which are likely to be influenced by on-going climate change. The worst invaders of tomorrow may not be the same as today and similarly, areas most at risk are likely to change

L'objectif de ce mémoire était une contribution à la conception et à la réalisation d'une station ambulatoire à vocation strictement agricole répondant aux exigences du cahier de charges défini par les experts agronomes. Cette station a pour but de doter l'exploitant agricole moderne d'une aide climatologique de précision et ceci en temps réel avec un cout relativement dérisoire. Le mémoire présente l'architecture de cet instrument compose d'un ensemble de capteurs et d'une électronique organisée autour d'un microcontrôleur et d'un composant FPGA. Un chapitre est consacré à l'organisation logicielle et le mémoire se termine par la présentation des résultats d'une validation sur site d'une année. En conclusion nous envisagerons l'évolution ultérieure de ce dispositif et son extension au domaine du suivi de la pollution atmosphérique.

This thesis outlines a technique for rapid documentation of historic sites in volatile cultural landscapes. Using Holt Cemetery as an exemplary case study, a workflow was developed incorporating RTK terrain survey, UAS aerial imagery, photogrammetry, GIS, and smartphone data collection in order to create a multifaceted database of the material and spatial conditions, as well as the patterns of use, that exist at the cemetery. The purpose of this research is to create a framework for improving the speed of data creation and increasing the accessibility of information regarding threatened cultural resources. It is intended that these processes can be scaled and adapted for use at any site, and that the products generated can be utilized by researchers, resource management professionals, and preservationists. In utilizing expedited methods, this thesis specifically advocates for documentation of sites that exist in coastal environments and are facing imminent destruction due to environmental degradation.

abstract: The subliminal impact of framing of social, political and environmental issues such as climate change has been studied for decades in political science and communications research. Media framing offers an “interpretative package" for average citizens on how to make sense of climate change and its consequences to their livelihoods, how to deal with its negative impacts, and which mitigation or adaptation policies to support. A line of related work has used bag of words and word-level features to detect frames automatically in text. Such works face limitations since standard keyword based features may not generalize well to accommodate surface variations in text when different keywords are used for similar concepts. This thesis develops a unique type of textual features that generalize triplets extracted from text, by clustering them into high-level concepts. These concepts are utilized as features to detect frames in text. Compared to uni-gram and bi-gram based models, classification and clustering using generalized concepts yield better discriminating features and a higher classification accuracy with a 12% boost (i.e. from 74% to 83% F-measure) and 0.91 clustering purity for Frame/Non-Frame detection. The automatic discovery of complex causal chains among interlinked events and their participating actors has not yet been thoroughly studied. Previous studies related to extracting causal relationships from text were based on laborious and incomplete hand-developed lists of explicit causal verbs, such as “causes" and “results in." Such approaches result in limited recall because standard causal verbs may not generalize well to accommodate surface variations in texts when different keywords and phrases are used to express similar causal effects. Therefore, I present a system that utilizes generalized concepts to extract causal relationships. The proposed algorithms overcome surface variations in written expressions of causal relationships and discover the domino effects between climate events and human security. This semi-supervised approach alleviates the need for labor intensive keyword list development and annotated datasets. Experimental evaluations by domain experts achieve an average precision of 82%. Qualitative assessments of causal chains show that results are consistent with the 2014 IPCC report illuminating causal mechanisms underlying the linkages between climatic stresses and social instability.
Dissertation/Thesis
Doctoral Dissertation Computer Science 2018

The subject of this diploma thesis is the analysis of long-term changes in precipitation in Europe over the period 1961 - 2011. Emphasis is placed on determining differences in values of trends in precipitation among selected data sources and on analyzing the spatial distribution of annual and seasonal changes in precipitation in Europe, including a discussion of possible causes of differences in these changes in individual areas. Another aim is to illustrate, describe and account for the differences in trend values among different data sources: the ECA&D station database, the interpolation network data sets E-OBS and CRU TS and two reanalyses JRA-55 and NCEP/NCAR. Depending on the amount and quality of data available for the comparison of data sets, changes in precipitation totals were described over a long-term scale in absolute and also, to a lesser degree, in relative values. The first part summarizes the scientific literature dealing with the changes in precipitation characteristics throughout the world and in Europe. There follows a description of the suitability of individual types of data sources for estimating trends in precipitation totals. Scientific articles usually describe long-term changes based on a single data source rather than using a variety of individual types of data sources....

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
Coastal areas provide habitats that are a source of natural protection, food, recreation, and livelihood. These ecosystems are designed to withstand the threat of natural hazards to protect inland areas. However, dynamic, and extreme climatic changes threaten to damage such areas, particularly in low-lying, small island states as Jamaica. With the Coastal Vulnerability Index (CVI) method, areas of coastal exposure were identified and assessed using the InVEST Model. It was found that 23% of the coastline is highly exposed to climatic hazards across 177 communities. Validation of the model outputs with the Disaster Inventory DesInventar Database revealed that there was statistical evidence to state that significantly more frequent events causing damage and loss of life or property occurred in areas the model identified as highly exposed than in the less exposed areas. The island's socio-economic conditions at the parish level were analyzed with descriptive statistics to determine that 48% of the population has at least one unmet basic need, with the South to South-East parishes comparably more vulnerable due to the population size and exposure in coastal areas. Therefore, the findings of this assessment will be useful for disaster planning and coastal conservation and may be replicated in similar countries, especially surrounding islands towards a regional assessment. The creation of a combined coastal and social vulnerability index provides a balanced view of both major concerns on the susceptibility of populated coastal regions. This index is critical to the advancement of how we can comparatively quantify these characteristics and highlight areas for holistic improvement of lives, not addressing both concerns in isolation.

碩士
臺北醫學大學
醫學資訊研究所
97
In the recent years, because of the ageing problem in the population structure of Taiwan, the threat of the cardiovascular illness for Taiwanese people is constantly increasing. In the literature reports of many countries with different climate conditions have pointed out that the occurrence and mortality of such illness do tend to be different according to the change of the seasons and the surrounding temperature. Taiwan is situated in the subtropical zone, and its type of climate is sea-island, therefore, it is affected a great deal by its surrounding climate. The Taiwanese terrain is both long and narrow at its north and south ends, and so the climate condition of both ends can be different at any given one time. For example, the north can be cold while the south is experiencing hot weather, or the north is raining while the south is having a sunny day. For this very own reason, if the research is only done to one county or city alone, the strength of persuasion can be deemed a little low. The purpose of this research is to investigate the Taiwanese people’s cardiovascular illness and the relatedness between the relative climate factors and the change in the atmospheric temperature. The source of information is the research database of the National Health Insurance from year 2000 to 2002. From this database, any related case with its climate observation data in the corresponding year is chosen as the research subject. The collected data is also divided according to different counties and cities, and whether the occurrence of the illness is related to the change in the surrounding climate factors is discussed individually. The relationship between the number of people seeking medical advice and each different climate factors is also analyzed. Regression analysis is used in this research to figure out the related risk of each climate factors to the number of people seeking medical advice. And after that, VAR model in the time series is then used to further analysis. Finally, a Web interface system is created according to different counties and cities, and the analyzed information is displayed in integral. All is done with the expectation of utilizing the point-and-click technique in the Web interface from the users to allow the understanding of the relationship between the number of people having cardiovascular illness seeking medical advice and each different climate factors.

碩士
國立臺灣大學
生醫電子與資訊學研究所
100
The relationships between temperature and other climatic factors and diseases have been widely understood in some relationships between climatic factors and diseases but not been comprehensive enough in the other certain relationships, especially in the twenty-four solar terms time-scale. “Solar Terms” in Chinese culture is the specific calendar in conjunction with the seasonal climate in a year and can create best harvest. In traditional Chinese medicine the climate changes of four seasons makes human body imbalance and cause disease, but there are not enough literatures to present exact statistics specific in the relationship between disease and climate on the annual twenty-four solar terms. In this study we used the data from outpatient records during years from 2005 to 2010 in National Health Insurance Research Database (NHIRD) and climatic factors including temperature and atmospheric pressure during the same years in Central Weather Bureau. Data in Gregorian calendar time scale would be transformed into twenty-four solar terms and mined. We also used cross-correlation coefficients to present the relationships between climates and diseases, and tried to explain how climatic factors impact diseases in the time scale of the solar terms on the view of traditional Chinese medicine by the modern theory. In addition to the observations to the average annual trend of diseases, this study also used Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) in Hilbert-Huang Transform to decompose many Internal Mode Functions (Intrinsic Mode Function), exploring the trend of diseases in the time scale of solar terms, as well as comparing diseases to explore the comorbidity. We also compared many parameters to select the ideal solution to the disease data decomposed by EEMD. The trends of climate data and the relationship with diseases were also explored by the aforementioned methods We obtained many results after these experiments. In addition to non-decomposed statistic results, we also found that EMD/EEMD algorithm can filter noises from the data and get smoother cyclical functions. While the more decomposition of the volatility of disease information but also makes more relevant to be searched out, and for the other study. As more functions decomposed, the more relationships would be found and could be studied more.

Dissertação de Mestrado em Tecnologias de Informação Geográfica apresentada à Faculdade de Ciências e Tecnologia
O aumento da população mundial e das suas atividades e a crescente concentração de população nos centros urbanos resultam em alterações não só nas características físicas da superfície terrestre como igualmente, nas características climáticas. Como resultado desta ação antropogénica, as cidades registam valores mais elevados de temperatura em comparação com as áreas rurais circundantes. A constatação de que as temperaturas da cidade são mais elevadas, já foi estudada e documentada por um longo período temporal, referindo-se a este fenómeno como “ilhas de calor urbano”.Ao longo dos últimos anos, esta temática tem registado grande destaque, em particular, nos meios de comunicação social, pela existência de um fenómeno denominado aquecimento global. Este fenómeno pode ser descrito como o aumento significativo das temperaturas a nível mundial e que com uso de modelos matemáticos de previsão do futuro climático foi perspetivado como sendo bastante significativo no futuro.Contudo, para que possa ser efetivamente possível avaliar de uma forma mais precisa as futuras características climáticas do planeta, é importante perceber qual são as características do local onde estão implantadas as estações meteorológicas usadas nos modelos matemáticos. Isto porque nestas projeções são utilizados dados históricos das estações. Ora, se uma estação estava anteriormente localizada num ambiente rural e se, com o passar do tempo, sofreu ao seu redor um processo de urbanização, as temperaturas registadas passaram a verificar um aumento significativo. O uso de mais estações localizadas em ambiente urbano, em comparação com estações localizadas em ambiente rural nestes modelos tem suscitado o interesse científico, dado que pode ter ‘enviesado’ os resultados dos modelos das projeções climáticas.Assim o principal objetivo deste trabalho é testar uma metodologia que ajude a melhorar a classificação de áreas urbanas a nível mundial feita no âmbito do projeto World Urban Database and Access Portal Tools (WUDAPT), para que se possa conhecer o ambiente envolvente das estações meteorológicas. Para isso, propõe-se uma metodologia que recorre a dados de Informação Geográfica Voluntária, especificamente, a dados do OpenStreetMap (OSM), para complementar os resultados da classificação de imagens de satélite nestas áreas.A metodologia baseia-se na combinação, usando regras previamente estabelecidas, dos resultados obtidos através da classificação de imagens de satélite com a informação obtida a partir do OSM, depois de associada às classes usadas no projeto WUDAPT.Os objetivos propostos inicialmente foram cumpridos, no entanto existem ainda limitações associadas à metodologia proposta, que deverão ser abordadas em trabalho futuro.
The increase in the world’s population and its activities, and the increasing concentration of population in the urban centers, has resulted in alterations, not only in the physical characteristics of the terrestrial surface, but also in terms of the climate. As a result of this anthropogenic action, cities are experiencing higher temperature values compared to the surrounding rural areas. The evidence that the city temperatures are higher has been studied and documented for a long time, referred to as the "urban heat island."Over the last few years, this issue has become particularly prominent in the media, due to the existence of a phenomenon called global warming. This phenomenon can be described as the significant increase of temperatures worldwide, which, with the use of mathematical models of the prediction of the future climate, has been foreseen as being quite significant in the future.However, in order to be able to accurately assess the future climatic characteristics of the planet, it is important to understand the characteristics of the location of the meteorological stations used in mathematical models. This is important because, in these projections, historical data of the stations are used. However, if a station was previously located in a rural environment and if, over time, it had an urbanization process around it, the temperatures registered will have increased significantly. The use of more stations located in an urban environment compared to stations located in rural environments in these models has aroused scientific interest, since it may have 'biased' the results of the climate projection models.Thus, the main objective of this work is to contribute and propose a methodology that will help to improve the precision of the classification of urban areas of the world made in the framework of the World Urban Database and Access Portal Tools (WUDAPT) project, so that the surrounding environment of the meteorological stations is better known. For this, a methodology is proposed that uses Volunteered Geographic Information, specifically OpenStreetMap data, to complement the results of the classification of satellite images in these areas.The methodology was based on the combination, using previously established rules, of the results obtained in the classification of satellite images and the data available in OpenStreetMap once they are associated to the classes used in the WUDAPT project.The objectives initially proposed were fulfilled; however, there are still some limitations associated with the proposed methodology, which should be addressed in future work.
Universidade de Coimbra - Bolseiro SASUC

As correntes oceânicas resultam do efeito do vento e das variações de densidade da água, juntamente com a rotação da Terra, com os acidentes geográficos e topográficos do fundo marinho. Estas interações perfazem uma circulação geral média de escala grande e de mesoescala, que transporta calor e propriedades. A presente dissertação de mestrado consiste na elaboração de uma ferramenta em software MATLAB que lê dados climáticos da NOAA (National Oceanic and Atmospheric Administration) World Ocean Database (2013) por forma a permitir a avaliação e caracterização do Oceano Atlântico Noroeste, através das estruturas de temperatura, salinidade, densidade, velocidade do som e componentes geostróficas, a ser utilizado para qualquer área de interesse do utilizador, no oceano. Na área estudada as principais correntes são: a Corrente quente do Golfo, a Corrente fria do Labrador e a Corrente da Deriva do Atlântico Norte. Existem também estruturas de mesoescala, como vórtices, eddies, meandros e jatos, que não serão visíveis porque a abordagem é apoiada em climatologia de médias temporais. Pretende-se ainda identificar as massas de água presentes, como a Água Central do Atlântico Norte, a Água Superior Subártica, a Água Intermédia do Atlântico Norte, a Água Mediterrânica e a Água Profunda do Atlântico Norte
Ocean currents result from the effect of wind and water density variations, along with the Earth's rotation, with geographic and topographical seabed occurrences. These interactions make up a medium general circulation of large scale and mesoscale, which carries heat and properties. The present dissertation consists of the elaboration of a MATLAB software tool that reads NOAA World Ocean Database (2013) climatic data in order to allow the evaluation and characterization of the Northwest Atlantic Ocean through the structures of temperature, salinity, density, velocity of sound and geostrophic components, to be used for any area of interest to the user, in the ocean. In the studied area, the main currents are: the Gulf Stream, the Labrador Cold Current and the North Atlantic Drift Current. There are also mesoscale structures, such as vortices, eddies, meanders and jets, which will not be visible because the approach is supported in climatology of temporal averages. It is also intended to identify the bodies of water present, such as the North Atlantic Central Water, the Subarctic Upper Water, the Intermediate Water of the North Atlantic, the Mediterranean Water and the Deep North Atlantic Water.