883 resultados para Climate monitoring and alerting


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There is growing evidence of changes in the timing of important ecological events, such as flowering in plants and reproduction in animals, in response to climate change, with implications for population decline and biodiversity loss. Recent work has shown that the timing of breeding in wild birds is changing in response to climate change partly because individuals are remarkably flexible in their timing of breeding. Despite this work, our understanding of these processes in wild populations remains very limited and biased towards species from temperate regions. Here, we report the response to changing climate in a tropical wild bird population using a long-term dataset on a formerly critically endangered island endemic, the Mauritius kestrel. We show that the frequency of spring rainfall affects the timing of breeding, with birds breeding later in wetter springs. Delays in breeding have consequences in terms of reduced reproductive success as birds get exposed to risks associated with adverse climatic conditions later on in the breeding season, which reduce nesting success. These results, combined with the fact that frequency of spring rainfall has increased by about 60 per cent in our study area since 1962, imply that climate change is exposing birds to the stochastic risks of late reproduction by causing them to start breeding relatively late in the season.

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This paper describes recent variations of the North Atlantic eddy-driven jet stream and analyzes the mean response of the jet to anthropogenic forcing in climate models. Jet stream changes are analyzed both using a direct measure of the near-surface westerly wind maximum and using an EOF-based approach. This allows jet stream changes to be related to the widely used leading patterns of variability: the North Atlantic Oscillation (NAO) and East Atlantic (EA) pattern. Viewed in NAO–EA state space, isolines of jet latitude and speed resemble a distorted polar coordinate system, highlighting the dependence of the jet stream quantities on both spatial patterns. Some differences in the results of the two methods are discussed, but both approaches agree on the general characteristics of the climate models. While there is some agreement between models on a poleward shift of the jet stream in response to anthropogenic forcing, there is still considerable spread between different model projections, especially in winter. Furthermore, the model responses to forcing are often weaker than their biases when compared to a reanalysis. Diagnoses of jet stream changes can be sensitive to the methodologies used, and several aspects of this are also discussed.

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To understand the resilience of aquatic ecosystems to environmental change, it is important to determine how multiple, related environmental factors, such as near-surface air temperature and river flow, will change during the next century. This study develops a novel methodology that combines statistical downscaling and fish species distribution modeling, to enhance the understanding of how global climate changes (modeled by global climate models at coarse-resolution) may affect local riverine fish diversity. The novelty of this work is the downscaling framework developed to provide suitable future projections of fish habitat descriptors, focusing particularly on the hydrology which has been rarely considered in previous studies. The proposed modeling framework was developed and tested in a major European system, the Adour-Garonne river basin (SW France, 116,000 km(2)), which covers distinct hydrological and thermal regions from the Pyrenees to the Atlantic coast. The simulations suggest that, by 2100, the mean annual stream flow is projected to decrease by approximately 15% and temperature to increase by approximately 1.2 °C, on average. As consequence, the majority of cool- and warm-water fish species is projected to expand their geographical range within the basin while the few cold-water species will experience a reduction in their distribution. The limitations and potential benefits of the proposed modeling approach are discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

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The separate effects of ozone depleting substances (ODSs) and greenhouse gases (GHGs) on forcing circulation changes in the Southern Hemisphere extratropical troposphere are investigated using a version of the Canadian Middle Atmosphere Model (CMAM) that is coupled to an ocean. Circulation-related diagnostics include zonal wind, tropopause pressure, Hadley cell width, jet location, annular mode index, precipitation, wave drag, and eddy fluxes of momentum and heat. As expected, the tropospheric response to the ODS forcing occurs primarily in austral summer, with past (1960-99) and future (2000-99) trends of opposite sign, while the GHG forcing produces more seasonally uniform trends with the same sign in the past and future. In summer the ODS forcing dominates past trends in all diagnostics, while the two forcings contribute nearly equally but oppositely to future trends. The ODS forcing produces a past surface temperature response consisting of cooling over eastern Antarctica, and is the dominant driver of past summertime surface temperature changes when the model is constrained by observed sea surface temperatures. For all diagnostics, the response to the ODS and GHG forcings is additive: that is, the linear trend computed from the simulations using the combined forcings equals (within statistical uncertainty) the sum of the linear trends from the simulations using the two separate forcings. Space time spectra of eddy fluxes and the spatial distribution of transient wave drag are examined to assess the viability of several recently proposed mechanisms for the observed poleward shift in the tropospheric jet.

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The radiocarbon-dated palaeoecological study of Lago Riane (Ligurian Apennines, NW Italy) presented here forms part of a wider investigation into the relationships between Holocene vegetation succession, climate change and human activities in the northern Apennines. The record of vegetation history from Lago Riane indicates that, since the end of the last glaciation, climate change and prehistoric human activities, combined with several local factors, have strongly influenced the pattern and timing of natural vegetation succession. The pollen record indicates an important change in vegetation cover at Lago Riane at ~8500–8200 cal. years b.p., coincident with a well-known period of rapid climate change. At ~6100 cal. years b.p., Fagus woodland colonised Lago Riane during a period of climate change and expansion of Late Neolithic human activities in the upland zone of Liguria. A marked decline in Abies woodland, and the expansion of Fagus woodland, at ~4700 cal. years b.p., coincided with further archaeological evidence for pastoralism in the mountains of Liguria during the Copper Age. At ~3900–3600 cal. years b.p. (Early to Middle Bronze Age transition), a temporary expansion of woodland at Lago Riane has been provisionally attributed to a decline in human pressure on the environment during a period of short-term climate change

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The vagaries of South Asian summer monsoon rainfall on short and long timescales impact the lives of more than one billion people. Understanding how the monsoon will change in the face of global warming is a challenge for climate science, not least because our state-of-the-art general circulation models still have difficulty simulating the regional distribution of monsoon rainfall. However, we are beginning to understand more about processes driving the monsoon, its seasonal cycle and modes of variability. This gives us the hope that we can build better models and ultimately reduce the uncertainty in our projections of future monsoon rainfall.

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This paper provides an introduction to the Special Issue on “Climate Change and Coupling of Macronutrient Cycles along the Atmospheric, Terrestrial, Freshwater and Estuarine Continuum”, dedicated to Colin Neal on his retirement. It is not intended to be a review of this vast subject, but an attempt to synthesize some of the major findings from the 22 contributions to the Special Issue in the context of what is already known. The major research challenges involved in understanding coupled macronutrient cycles in these environmental media are highlighted, and the difficulties of making credible predictions of the effects of climate change are discussed. Of particular concern is the possibility of interactions which will enhance greenhouse gas concentrations and provide positive feedback to global warming.

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Climate modeling is a complex process, requiring accurate and complete metadata in order to identify, assess and use climate data stored in digital repositories. The preservation of such data is increasingly important given the development of ever-increasingly complex models to predict the effects of global climate change. The EU METAFOR project has developed a Common Information Model (CIM) to describe climate data and the models and modelling environments that produce this data. There is a wide degree of variability between different climate models and modelling groups. To accommodate this, the CIM has been designed to be highly generic and flexible, with extensibility built in. METAFOR describes the climate modelling process simply as "an activity undertaken using software on computers to produce data." This process has been described as separate UML packages (and, ultimately, XML schemas). This fairly generic structure canbe paired with more specific "controlled vocabularies" in order to restrict the range of valid CIM instances. The CIM will aid digital preservation of climate models as it will provide an accepted standard structure for the model metadata. Tools to write and manage CIM instances, and to allow convenient and powerful searches of CIM databases,. Are also under development. Community buy-in of the CIM has been achieved through a continual process of consultation with the climate modelling community, and through the METAFOR team’s development of a questionnaire that will be used to collect the metadata for the Intergovernmental Panel on Climate Change’s (IPCC) Coupled Model Intercomparison Project Phase 5 (CMIP5) model runs.

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The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policy-makers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 peta-flops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather–climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology.