292 resultados para 040105 Climatology (excl. Climate Change Processes)


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Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models.

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In this paper we show how a seemingly unremarkable object – a cattle grid – has come to presence climate change in partial and contingent ways on the Lizard Peninsula, Cornwall, UK. We identify the cattle grid as an ‘anticipatory object’ through which conservation organisations seek to manage the future and adapt to climate change, but which at the same time presences that unthought-of future for others in the landscape. We explore the ways in which the cattle grid acts to presence something that is not only absent – climate change – but has uncertain imminence. We investigate the ways in which the cattle grid make climate relevant as an embodied and experiential process, a physical and intellectual artefact, and the means to imagine climate and the ways it might change. Drawing upon interpretative approaches informed by theorisations of materiality, presence and absence to understand climate change as a social phenomenon, we go beyond a consideration of this ordinary object defined by its function to consider how the object is experienced, the processes and practices through which people relate to it, and the ways in which social meaning accumulates around it. The empirical basis for this argument is provided by in-depth interviews with local representatives of Natural England, residents and farmers.

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Cities and global climate change are closely linked: cities are where the bulk of greenhouse gas emissions take place through the consumption of fossil fuels; they are where an increasing proportion of the world’s people live; and they also generate their own climate – commonly characterized by the urban heat island. In this way, understanding the way cities affect the cycling of energy, water, and carbon to create an urban climate is a key element of climate mitigation and adaptation strategies, especially in the context of rising global temperatures and deteriorating air quality in many cities. As climate models resolve finer spatial-scales, they will need to represent those areas in which more than 50% of the world’s population already live to provide climate projections that are of greater use to planning and decision-making. Finally, many of the processes that are instrumental in determining urban climate are the same factors leading to global anthropogenic climate change, namely regional-scale land-use changes; increased energy use; and increased emissions of climatically-relevant atmospheric constituents. Cities are therefore both a case study for understanding, and an agent in mitigating, anthropogenic climate change. This chapter reviews and summarizes the current state of understanding of the physical basis of urban climates, as well as our ability to represent these in models. We argue that addressing the challenges of managing urban environments in a changing climate requires understanding the energy, water, and carbon balances for an urban landscape and, importantly, their interactions and feedbacks, together with their links to human behaviour and controls. We conclude with some suggestions for where further research is needed.

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How effective are multi-stakeholder scenarios building processes to bring diverse actors together and create a policy-making tool to support sustainable development and promote food security in the developing world under climate change? The effectiveness of a participatory scenario development process highlights the importance of ‘boundary work’ that links actors and organizations involved in generating knowledge on the one hand, and practitioners and policymakers who take actions based on that knowledge on the other. This study reports on the application of criteria for effective boundary work to a multi-stakeholder scenarios process in East Africa that brought together a range of regional agriculture and food systems actors. This analysis has enabled us to evaluate the extent to which these scenarios were seen by the different actors as credible, legitimate and salient, and thus more likely to be useful. The analysis has shown gaps and opportunities for improvement on these criteria, such as the quantification of scenarios, attention to translating and communicating the results through various channels and new approaches to enable a more inclusive and diverse group of participants. We conclude that applying boundary work criteria to multi-stakeholder scenarios processes can do much to increase the likelihood of developing sustainable development and food security policies that are more appropriate.

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Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth’s climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community

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The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

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Climate change in the UK is expected to cause increases in temperatures, altered precipitation patterns and more frequent and extreme weather events. In this review we discuss climate effects on dissolved organic matter (DOM), how altered DOM and water physico-chemical properties will affect treatment processes and assess the utility of techniques used to remove DOM and monitor water quality. A critical analysis of the literature has been undertaken with a focus on catchment drivers of DOM character, removal of DOM via coagulation and the formation of disinfectant by-products (DBPs). We suggest that: (1) upland catchments recovering from acidification will continue to produce more DOM with a greater hydrophobic fraction as solubility controls decrease; (2) greater seasonality in DOM export is likely in future due to altered precipitation patterns; (3) changes in species diversity and water properties could encourage algal blooms; and (4) that land management and vegetative changes may have significant effects on DOM export and treatability but require further research. Increases in DBPs may occur where catchments have high influence from peatlands or where algal blooms become an issue. To increase resilience to variable DOM quantity and character we suggest that one or more of the following steps are undertaken at the treatment works: a) ‘enhanced coagulation’ optimised for DOM removal; b) switching from aluminium to ferric coagulants and/or incorporating coagulant aids; c) use of magnetic ion-exchange (MIEX) pre-coagulation; and d) activated carbon filtration post-coagulation. Fluorescence and UV absorbance techniques are highlighted as potential methods for low-cost, rapid on-line process optimisation to improve DOM removal and minimise DBPs.

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Grassroots innovations emerge as networks generating innovative solutions for climate change adaptation and mitigation. However, it is unclear if grassroots innovations can be successful in responding to climate change. Little evidence exists on replication, international comparisons are rare, and research tends to overlook discontinued responses in favour of successful ones. We take the Transition Movement as a case study of a rapidly spreading transnational grassroots network, and include both active and non-active local transition initiatives. We investigate the replication of grassroots innovations in different contexts with the aim to uncover general patterns of success and failure, and identify questions for future research. An online survey was carried out in 23 countries (N=276). The data analysis entailed testing the effect of internal and contextual factors of success as drawn from the existing literature, and the identification of clusters of transition initiatives with similar internal and contextual factor configurations. Most transition initiatives consider themselves successful. Success is defined along the lines of social connectivity and empowerment, and external environmental impact. We find that less successful transition initiatives might underestimate the importance of contextual factors and material resources in influencing success. We also find that their diffusion is linked to the combination of local-global learning processes, and that there is an incubation period during which a transition initiative is consolidated. Transition initiatives seem capable of generalising organisational principles derived from unique local experiences that seem to be effective in other local contexts. However, the geographical locations matter with regard to where transition initiatives take root and the extent of their success, and ‘place attachment’ may have a role in the diffusion of successful initatives. We suggest that longitudinal comparative studies can advance our understanding in this regard, as well as inform the changing nature of the definition of success at different stages of grassroots innovation development, and the dynamic nature of local and global linkages.

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A statistical–dynamical downscaling (SDD) approach for the regionalization of wind energy output (Eout) over Europe with special focus on Germany is proposed. SDD uses an extended circulation weather type (CWT) analysis on global daily mean sea level pressure fields with the central point being located over Germany. Seventy-seven weather classes based on the associated CWT and the intensity of the geostrophic flow are identified. Representatives of these classes are dynamically downscaled with the regional climate model COSMO-CLM. By using weather class frequencies of different data sets, the simulated representatives are recombined to probability density functions (PDFs) of near-surface wind speed and finally to Eout of a sample wind turbine for present and future climate. This is performed for reanalysis, decadal hindcasts and long-term future projections. For evaluation purposes, results of SDD are compared to wind observations and to simulated Eout of purely dynamical downscaling (DD) methods. For the present climate, SDD is able to simulate realistic PDFs of 10-m wind speed for most stations in Germany. The resulting spatial Eout patterns are similar to DD-simulated Eout. In terms of decadal hindcasts, results of SDD are similar to DD-simulated Eout over Germany, Poland, Czech Republic, and Benelux, for which high correlations between annual Eout time series of SDD and DD are detected for selected hindcasts. Lower correlation is found for other European countries. It is demonstrated that SDD can be used to downscale the full ensemble of the Earth System Model of the Max Planck Institute (MPI-ESM) decadal prediction system. Long-term climate change projections in Special Report on Emission Scenarios of ECHAM5/MPI-OM as obtained by SDD agree well to the results of other studies using DD methods, with increasing Eout over northern Europe and a negative trend over southern Europe. Despite some biases, it is concluded that SDD is an adequate tool to assess regional wind energy changes in large model ensembles.

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Conceptualizing climate as a distinct variable limits our understanding of the synergies and interactions between climate change and the range of abiotic and biotic factors, which influence animal health. Frameworks such as eco-epidemiology and the epi-systems approach, while more holistic, view climate and climate change as one of many discreet drivers of disease. Here, I argue for a new paradigmatic framework: climate-change syndemics. Climate-change syndemics begins from the assumption that climate change is one of many potential influences on infectious disease processes, but crucially is unlikely to act independently or in isolation; and as such, it is the inter-relationship between factors that take primacy in explorations of infectious disease and climate change. Equally importantly, as climate change will impact a wide range of diseases, the frame of analysis is at the collective rather than individual level (for both human and animal infectious disease) across populations.

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Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.

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We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.

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Horticulture may be defined as the intensive cultivation and harvesting of plants for financial, environmental and social profit. Evidence for the occurrence of climate change more generally and reasons why this process is happening with such rapidity are discussed. These changes are then considered in terms of the effects which might alter the options for worldwide intensive horticultural cultivation of plants and its interactions with other organisms. Potentially changing climates will have considerable impact upon horticultural processes and productivity across the globe . Climate change will alter the growth patterns and capabilities for flowering and fruiting of many perennial and annual horticultural plants. In some regions perennial fruit crops are likely to experience substantial difficulties because of altered seasonal conditions affecting dormancy, acclimation and subsequent flowering and fruiting. Elsewhere these crops may benefit from the effects of climate change as a result of reduced cold damage and increased length of the growing season. There will be considerable effects for aerial and edaphic microbes invertebrate and vertebrate animals which have benign and pathogenic interactions with horticultural plants. Microbial activity and as a consequence soil fertility may alter. New pests and pathogens may become prevalent and damaging in areas where the climate previously excluded their activity. Vital resources such as water and nutrients may become scarce in some regions reducing opportunities for growing horticultural crops. Wind and windiness are significant factors governing the success of horticultural plants and the scale of their impacts may change as climate alters. Damaging winds could limit crop growing in areas where previously it flourished. Forms of macro- and micro-landscaping will change as the spectrum of plants which can be cultivated alters and the availability of resources and their cost changes driven by scarcities brought about by climate change. The horticultural economy of India as it may be affected by climate change is described as an individual example in a detailed study.

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Precipitation over western Europe (WE) is projected to increase (decrease) roughly northward (equatorward) of 50°N during the 21st century. These changes are generally attributed to alterations in the regional large-scale circulation, e.g., jet stream, cyclone activity, and blocking frequencies. A novel weather typing within the sector (30°W–10°E, 25–70°N) is used for a more comprehensive dynamical interpretation of precipitation changes. A k-means clustering on daily mean sea level pressure was undertaken for ERA-Interim reanalysis (1979–2014). Eight weather types are identified: S1, S2, S3 (summertime types), W1, W2, W3 (wintertime types), B1, and B2 (blocking-like types). Their distinctive dynamical characteristics allow identifying the main large-scale precipitation-driving mechanisms. Simulations with 22 Coupled Model Intercomparison Project 5 models for recent climate conditions show biases in reproducing the observed seasonality of weather types. In particular, an overestimation of weather type frequencies associated with zonal airflow is identified. Considering projections following the (Representative Concentration Pathways) RCP8.5 scenario over 2071–2100, the frequencies of the three driest types (S1, B2, and W3) are projected to increase (mainly S1, +4%) in detriment of the rainiest types, particularly W1 (−3%). These changes explain most of the precipitation projections over WE. However, a weather type-independent background signal is identified (increase/decrease in precipitation over northern/southern WE), suggesting modifications in precipitation-generating processes and/or model inability to accurately simulate these processes. Despite these caveats in the precipitation scenarios for WE, which must be duly taken into account, our approach permits a better understanding of the projected trends for precipitation over WE.

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Global climate changes during the Cenozoic (65.5–0 Ma) caused major biological range shifts and extinctions. In northern Europe, for example, a pattern of few endemics and the dominance of wide-ranging species is thought to have been determined by the Pleistocene (2.59–0.01 Ma) glaciations. This study, in contrast, reveals an ancient subsurface fauna endemic to Britain and Ireland. Using a Bayesian phylogenetic approach, we found that two species of stygobitic invertebrates (genus Niphargus) have not only survived the entire Pleistocene in refugia but have persisted for at least 19.5 million years. Other Niphargus species form distinct cryptic taxa that diverged from their nearest continental relative between 5.6 and 1.0 Ma. The study also reveals an unusual biogeographical pattern in the Niphargus genus. It originated in north-west Europe approximately 87 Ma and underwent a gradual range expansion. Phylogenetic diversity and species age are highest in north-west Europe, suggesting resilience to extreme climate change and strongly contrasting the patterns seen in surface fauna. However, species diversity is highest in south-east Europe, indicating that once the genus spread to these areas (approximately 25 Ma), geomorphological and climatic conditions enabled much higher diversification. Our study highlights that groundwater ecosystems provide an important contribution to biodiversity and offers insight into the interactions between biological and climatic processes.