883 resultados para Climate monitoring and alerting


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Based on a case study of Charazani – Bolivia, this article outlines the understanding of adaptive strategies to cope with climate change and its impact on environmental and socioeconomic conditions that are affecting rural livelihoods. Mainly qualitative methods were used to collect and analyze data following the framework for vulnerability assessments of a socio-ecological system. Climate data reveals an increase of precipitation and temperature during the last decades. Furthermore the occurrence of extreme weather events, particularly drought, frost, hailstorms and consequently landslides and fire are increasing. Local testimonies highlight these events as the principle reasons for agricultural losses. This climatic variability and simultaneous social changes were identified as the drivers of vulnerability. Yet, several adaptive measures were identified at household, community and external levels in order to cope with such vulnerability; e.g. traditional techniques in agriculture and risk management. Gradually, farmers complement these activities with contemporary practices in agriculture, like intensification of land use, diversification of irrigation system and use of artificial fertilizers. As part of a recent trend community members are forced to search for new off-farm alternatives beyond agriculture for subsistence. Despite there is a correspondingly large array of possible adaptation measures that families are implementing, local testimonies point out, that farmers often do not have the capacity and neither the economical resources to mitigate the risk in agricultural production. Although several actions are already considered to promote further adaptive capacity, the current target is to improve existing livelihood strategies by reducing vulnerability to hazards induced by climate change.

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In the last decades, there has been a growing tendency towards international trade and globalisation, particularly leading to a significant increase in flows of agricultural commodities worldwide. From a macroeconomic perspective, the commodity projections are more optimistic than the previous years and the long run tendency shows an increasing demand for feedstock. However, the strong shifts of shocks and fluctuations (in terms of prices and volumes) are a concern to global food security, with the number of hungry people rising to nearly one billion. Agriculture is a main user of natural resources, and it has a strong link with rural societies and the environment. Forecasted impacts from climate change, limited productive endorsements and emerging rivals on crop production, such bio-energy, aggravate the panorama on food scarcity. In this context, it is a great challenge on farming and food systems to reduce global hunger and produce in sustainable ways adequate supplies for food, feed, and non-food uses. The main objective of this work is to question the sustainability of food and agriculture systems. It is particularly interesting to know its role and if it will be able to respond to a growing population with increasing food demand in a world where pressure on land, water and other natural resources are already evident, and, moreover, climate change will also condition and impact the outcome. Furthermore, a deeper focus will be set on developing countries, which are expected to emerge and take a leading role in the international arena. This short paper is structured as follows: Section I, “Introduction”, describes the social situation regarding hunger, Section II, “Global Context”, attempts to summarise the current scenario in the international trading scheme and present the emerging rivals for primary resources, and in Section III, “Climate Change”, presents an overview of possible changes in the sector and future perspectives in the field. Finally, in Section IV, “Conclusion”, the main conclusions are presented.

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The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

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This study analyzes the linear relationship between climate variables and milk components in Iran by applying bootstrapping to include and assess the uncertainty. The climate parameters, Temperature Humidity Index (THI) and Equivalent Temperature Index (ETI) are computed from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis (2002–2010). Milk data for fat, protein (measured on fresh matter bases), and milk yield are taken from 936,227 milk records for the same period, using cows fed by natural pasture from April to September. Confidence intervals for the regression model are calculated using the bootstrap technique. This method is applied to the original times series, generating statistically equivalent surrogate samples. As a result, despite the short time data and the related uncertainties, an interesting behavior of the relationships between milk compound and the climate parameters is visible. During spring only, a weak dependency of milk yield and climate variations is obvious, while fat and protein concentrations show reasonable correlations. In summer, milk yield shows a similar level of relationship with ETI, but not with temperature and THI. We suggest this methodology for studies in the field of the impacts of climate change and agriculture, also environment and food with short-term data.

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Wednesday 23rd April 2014 Speaker(s): Willi Hasselbring Organiser: Leslie Carr Time: 23/04/2014 14:00-15:00 Location: B32/3077 File size: 802Mb Abstract The internal behavior of large-scale software systems cannot be determined on the basis of static (e.g., source code) analysis alone. Kieker provides complementary dynamic analysis capabilities, i.e., monitoring/profiling and analyzing a software system's runtime behavior. Application Performance Monitoring is concerned with continuously observing a software system's performance-specific runtime behavior, including analyses like assessing service level compliance or detecting and diagnosing performance problems. Architecture Discovery is concerned with extracting architectural information from an existing software system, including both structural and behavioral aspects like identifying architectural entities (e.g., components and classes) and their interactions (e.g., local or remote procedure calls). In addition to the Architecture Discovery of Java systems, Kieker supports Architecture Discovery for other platforms, including legacy systems, for instance, inplemented in C#, C++, Visual Basic 6, COBOL or Perl. Thanks to Kieker's extensible architecture it is easy to implement and use custom extensions and plugins. Kieker was designed for continuous monitoring in production systems inducing only a very low overhead, which has been evaluated in extensive benchmark experiments. Please, refer to http://kieker-monitoring.net/ for more information.

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National policies in North America have not been drafted properly to address the problem of climate change, following the impasse of international negotiations. Facing this scenario, new alternatives emerge with the leadership and participation of new actors. Local governments in North America, especially of British Columbia, Ontario and Quebec, have been developing strategies to face climate change and emissions reduction in parallel to the national efforts and the global governance strategies. These local governments have developed a transregional approach that has resulted in the creation of regional institutions such as the Western Climate Initiative, the Regional Greenhouse GasInitiative and the Midwestern GreenhouseGas Reduction Accord.Their main goal is to establish regional carbon markets to mitigate and adapt to climate change impacts in a cost-effective way. In spite of these efforts, these initiatives have faced the overlapping problem among them and with national and globalstrategies. The goal of this research is to explore how these carbon markets have developed convergence policies. Convergence among these markets is expressed in their offset system and in secondary markets.

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Resumen basado en el de la publicaci??n

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Aquesta tesi es basa en el programa de reintroducció de la llúdriga eurasiàtica (Lutra lutra) a les conques dels rius Muga i Fluvià (Catalunya) durant la segona meitat dels 1990s. Els objectius de la tesi foren demostrar la viabilitat de la reintroducció, demostrar l'èxit de la mateixa, estudiar aspectes ecològics i etològics de l'espècie, aprofitant l'oportunitat única de gaudir d'una població "de disseny" i determinar les probabilitats de supervivència de la població a llarg termini. La reintroducció de la llúdriga a les conques dels rius Muga i Fluvià va reeixir, doncs l'àrea geogràfica ocupada efectivament es va incrementar fins a un 64% d'estacions positives a l'hivern 2001-02. La troballa de tres exemplars adults nascuts a l'àrea de reintroducció és una altra prova que valida l'èxit del programa. La densitat d'exemplars calculada a través dels censos visuals ha resultat baixa (0.04-0.11 llúdrigues/km), però s'aproxima al que hom pot esperar en els primers estadis d'una població reintroduïda, encara poc nombrosa però distribuïda en una gran àrea. La mortalitat post-alliberament va ser del 22% un any després de l'alliberament, similar o inferior a la d'altres programes de reintroducció de llúdrigues reeixits. La mortalitat va ser deguda principalment a atropellaments (56%). El patró d'activitat de les llúdrigues reintroduïdes va esdevenir principalment nocturn i crepuscular, amb una escassa activitat diürna. Les seves àrees vitals van ser del mateix ordre (34,2 km) que les calculades en d'altres estudis realitzats a Europa. La longitud mitjana de riu recorreguda per una llúdriga durant 24 hores va ser de 4,2 km per les femelles i 7,6 km pels mascles. Durant el període de radioseguiment dues femelles van criar i els seus moviments van poder ser estudiats amb deteniment. La resposta de la nova població de llúdrigues a les fluctuacions estacionals en la disponibilitat d'aigua, habitual a les regions mediterrànies, va consistir en la concentració en una àrea menor durant el període de sequera estival, a causa de l'increment de trams secs, inhabitables per la llúdriga per la manca d'aliment, fet que va provocar expansions i contraccions periòdiques en l'àrea de distribució. La persistència a llarg termini de la població reintroduïda va ser estudiada mitjançant una Anàlisi de Viabilitat Poblacional (PVA). El resultat va ser un baix risc d'extinció de la població en els propers 100 anys i la majoria dels escenaris simulats (65%) van assolir el criteri d'un mínim de 90% de probabilitat de supervivència. Del model poblacional construït es dedueix que un punt clau per assegurar la viabilitat de la població reintroduïda és la reducció de la mortalitat accidental. A l'àrea d'estudi, els atropellaments causen més del 50% de la mortalitat i aquesta pot ser reduïda mitjançant la construcció de passos de fauna, el tancament lateral d'alguns trams de carretera perillosos i el control de la velocitat en algunes vies. El projecte de reintroducció ha posat a punt un protocol per a la captura, maneig i alliberament de llúdrigues salvatges, que pot contenir informació útil per a programes similars. També ha suposat una oportunitat única d'estudiar una població dissenyada artificialment i poder comparar diversos mètodes per estimar la distribució i la densitat de poblacions de llúdrigues. Per últim, la reintroducció portada a terme a les conques dels rius Muga i Fluvià ha aconseguit crear una nova població de llúdrigues, que persisteix en el temps, que es reprodueix regularment i que es dispersa progressivament, fins i tot a noves conques fluvials.

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The representation of the diurnal cycle in the Hadley Centre climate model is evaluated using simulations of the infrared radiances observed by Meteosat 7. In both the window and water vapour channels, the standard version of the model with 19 levels produces a good simulation of the geographical distributions of the mean radiances and of the amplitude of the diurnal cycle. Increasing the vertical resolution to 30 levels leads to further improvements in the mean fields. The timing of the maximum and minimum radiances reveals significant model errors, however, which are sensitive to the frequency with which the radiation scheme is called. In most regions, these errors are consistent with well documented errors in the timing of convective precipitation, which peaks before noon in the model, in contrast to the observed peak in the late afternoon or evening. When the radiation scheme is called every model time step (half an hour), as opposed to every three hours in the standard version, the timing of the minimum radiance is improved for convective regions over central Africa, due to the creation of upper-level layer-cloud by detrainment from the convection scheme, which persists well after the convection itself has dissipated. However, this produces a decoupling between the timing of the diurnal cycles of precipitation and window channel radiance. The possibility is raised that a similar decoupling may occur in reality and the implications of this for the retrieval of the diurnal cycle of precipitation from infrared radiances are discussed.