916 resultados para United Nations Framework Convention on Climate Change (Organization)
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We assessed the importance of temperature, salinity, and predation for the size structure of zooplankton and provided insight into the future ecological structure and function of shallow lakes in a warmer climate. Artificial plants were introduced in eight comparable coastal shallow brackish lakes located at two contrasting temperatures: cold-temperate and Mediterranean climate region. Zooplankton, fish, and macroinvertebrates were sampled within the plants and at open-water habitats. The fish communities of these brackish lakes were characterized by small-sized individuals, highly associated with submerged plants. Overall, higher densities of small planktivorous fish were recorded in the Mediterranean compared to the cold-temperate region, likely reflecting temperature-related differences as have been observed in freshwater lakes. Our results suggest that fish predation is the major control of zooplankton size structure in brackish lakes, since fish density was related to a decrease in mean body size and density of zooplankton and this was reflected in a unimodal shaped biomass-size spectrum with dominance of small sizes and low size diversity. Salinity might play a more indirect role by shaping zooplankton communities toward more salt-tolerant species. In a global-warming perspective, these results suggest that changes in the trophic structure of shallow lakes in temperate regions might be expected as a result of the warmer temperatures and the potentially associated increases in salinity. The decrease in the density of largebodied zooplankton might reduce the grazing on phytoplankton and thus the chances of maintaining the clear water state in these ecosystems
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Drawing on his recent experience in the climate negotiations in Doha as an advisor and negotiator on a wide variety of issues, Andrei Marcu offers his assessment of the progress achieved in the two weeks of intensive talks. In spite of modest results, he describes the talks as an important and necessary step in the revolution, first ignited at the Montreal negotiations in 2005, that rejected the top-down Kyoto Protocol model in favour of a bottom-up climate change regime. In his view, the decisions taken in Doha enable the start of a new negotiating process aimed at delivering a new global climate agreement.
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The land/sea warming contrast is a phenomenon of both equilibrium and transient simulations of climate change: large areas of the land surface at most latitudes undergo temperature changes whose amplitude is more than those of the surrounding oceans. Using idealised GCM experiments with perturbed SSTs, we show that the land/sea contrast in equilibrium simulations is associated with local feedbacks and the hydrological cycle over land, rather than with externally imposed radiative forcing. This mechanism also explains a large component of the land/sea contrast in transient simulations as well. We propose a conceptual model with three elements: (1) there is a spatially variable level in the lower troposphere at which temperature change is the same over land and sea; (2) the dependence of lapse rate on moisture and temperature causes different changes in lapse rate upon warming over land and sea, and hence a surface land/sea temperature contrast; (3) moisture convergence over land predominantly takes place at levels significantly colder than the surface; wherever moisture supply over land is limited, the increase of evaporation over land upon warming is limited, reducing the relative humidity in the boundary layer over land, and hence also enhancing the land/sea contrast. The non-linearity of the Clausius–Clapeyron relationship of saturation specific humidity to temperature is critical in (2) and (3). We examine the sensitivity of the land/sea contrast to model representations of different physical processes using a large ensemble of climate model integrations with perturbed parameters, and find that it is most sensitive to representation of large-scale cloud and stomatal closure. We discuss our results in the context of high-resolution and Earth-system modelling of climate change.
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Under anthropogenic climate change it is possible that the increased radiative forcing and associated changes in mean climate may affect the “dynamical equilibrium” of the climate system; leading to a change in the relative dominance of different modes of natural variability, the characteristics of their patterns or their behavior in the time domain. Here we use multi-century integrations of version three of the Hadley Centre atmosphere model coupled to a mixed layer ocean to examine potential changes in atmosphere-surface ocean modes of variability. After first evaluating the simulated modes of Northern Hemisphere winter surface temperature and geopotential height against observations, we examine their behavior under an idealized equilibrium doubling of atmospheric CO2. We find no significant changes in the order of dominance, the spatial patterns or the associated time series of the modes. Having established that the dynamic equilibrium is preserved in the model on doubling of CO2, we go on to examine the temperature pattern of mean climate change in terms of the modes of variability; the motivation being that the pattern of change might be explicable in terms of changes in the amount of time the system resides in a particular mode. In addition, if the two are closely related, we might be able to assess the relative credibility of different spatial patterns of climate change from different models (or model versions) by assessing their representation of variability. Significant shifts do appear to occur in the mean position of residence when examining a truncated set of the leading order modes. However, on examining the complete spectrum of modes, it is found that the mean climate change pattern is close to orthogonal to all of the modes and the large shifts are a manifestation of this orthogonality. The results suggest that care should be exercised in using a truncated set of variability EOFs to evaluate climate change signals.
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Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., and Bell, M.J., 1995, A peanut simulation model: I. Model development and testing. Agron. J. 87, 1085-1093]. GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures. Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10-30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes-principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence, the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates. (C) 2007 Elsevier B.V. All rights reserved.
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Previous assessments of the impacts of climate change on heat-related mortality use the "delta method" to create temperature projection time series that are applied to temperature-mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heatrelated mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature-mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heatrelated mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2°C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.
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Changes to the behaviour of subseasonal precipitation extremes and active-break cycles of the Indian summer monsoon are assessed in this study using pre-industrial and 2 × CO2 integrations of the Hadley Centre coupled model HadCM3, which is able to simulate the monsoon seasonal cycle reasonably. At 2 × CO2, mean summer rainfall increases slightly, especially over central and northern India. The mean intensity of daily precipitation during the monsoon is found to increase, consistent with fewer wet days, and there are increases to heavy rain events beyond changes in the mean alone. The chance of reaching particular thresholds of heavy rainfall is found to approximately double over northern India, increasing the likelihood of damaging floods on a seasonal basis. The local distribution of such projections is uncertain, however, given the large spread in mean monsoon rainfall change and associated extremes amongst even the most recent coupled climate models. The measured increase of the heaviest precipitation events over India is found to be broadly in line with the degree of atmospheric warming and associated increases in specific humidity, lending a degree of predictability to changes in rainfall extremes. Active-break cycles of the Indian summer monsoon, important particularly due to their effect on agricultural output, are shown to be reasonably represented in HadCM3, in particular with some degree of northward propagation. We note an intensification of both active and break events, particularly when measured against the annual cycle, although there is no suggestion of any change to the duration or likelihood of monsoon breaks. Copyright © 2009 Royal Meteorological Society
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This paper describes the development and first results of the “Community Integrated Assessment System” (CIAS), a unique multi-institutional modular and flexible integrated assessment system for modelling climate change. Key to this development is the supporting software infrastructure, SoftIAM. Through it, CIAS is distributed between the community of institutions which has each contributed modules to the CIAS system. At the heart of SoftIAM is the Bespoke Framework Generator (BFG) which enables flexibility in the assembly and composition of individual modules from a pool to form coupled models within CIAS, and flexibility in their deployment onto the available software and hardware resources. Such flexibility greatly enhances modellers’ ability to re-configure the CIAS coupled models to answer different questions, thus tracking evolving policy needs. It also allows rigorous testing of the robustness of IA modelling results to the use of different component modules representing the same processes (for example, the economy). Such processes are often modelled in very different ways, using different paradigms, at the participating institutions. An illustrative application to the study of the relationship between the economy and the earth’s climate system is provided.
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A review of the implications of climate change for freshwater resources, based on Chapter 4 of Working Group 2, IPCC.
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A U-series calcrete chronology has been constructed for three Late Quaternary terrace units, termed the D1, D2 and D3 terraces in age descending order, from the Rio Aguas river system of the Sorbas basin, southeast Spain. The D1 terrace formed between 30,300 +/- 4400 year BP and 12,140 +/- 360 year BP, correlating well with the Last Glacial Maximum when rates of sediment supply would have increased greatly, because of higher rates of weathering, reduced vegetation cover and weak soil development. The D2 terrace formed between 12,800 +/- 1100 year BP and 9,600 +/- 530 year BP, correlating well with the Younger Dryas event. The D3 terrace could only be poorly constrained to the early Holocene and no unequivocal cause could be assigned to this period of aggradation. The sedimentology and geomorphology of the D2 terrace suggests, however, that the aggradation of this unit was a response to diapirism/karstic processes occurring within the underlying Messinian gypsum strata and the subsequent damming of the Aguas system. Therefore, despite its coincident occurrence with the Younger Dryas, aggradation of the D2 terrace is unrelated to climate change. The style of this response, controlled predominantly by the characteristics of the underlying bedrock, makes correlating the terrace record of the Aguas with other systems in the Mediterranean unreliable. This study, therefore, highlights the problems of correlating fluvial sequences in regions of variable tectonics, climatic history and bedrock geology and emphasises the need to properly understand the main controls on individual fluvial systems before any attempt is made to correlate their depositional histories. (C) 2004 Elsevier Ltd. All rights reserved.
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Large temperature variations on land, in the air, and at the ocean surface, and highly variable flux of ice-rafted debris (IRD) delivered to the North Atlantic Ocean show that rapid climate fluctuations took place during the last glacial period. These quasi-periodic, high-amplitude climate variations followed a sequence of events recognized as a rapid warming, followed by a phase of gradual cooling, and terminating with more rapid cooling and increased flux of IRD to the north Atlantic Ocean. Each cycle lasted ˜1500 years, and was followed by an almost identical sequence. These cycles are referred to as Dansgaard/Oechger cycles (D/O cycles), and approximately every fourth cycle culminated in a more pronounced cooling with a massive discharge of IRD into the north Atlantic Ocean over an interval of ˜500 years. These massive discharges of IRD are known as Heinrich layers. “Heinrich events” are thus characterized as a rapid transfer of IRD from a “source,” the bed of the Laurentide Ice Sheet (LIS), to a “sink,” the North Atlantic.
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The Human Development Index (HDI) introduced by the United Nations Development Programme (UNDP) in 1990 has helped facilitate widespread debate amongst development researchers, practitioners and policy makers. The HDI is an aggregate index, calculated on an annual basis by the UNDP and published in its Human Development Reports, comprising measures of three components deemed by them to be central to development: W income (the gross domestic product per capita), (ii) education (adult literacy rate) and (iii) health (life expectancy at birth). The results of calculating the HDI are typically presented as country/regional league tables, and provide a quick means for policy makers and others to judge performance. Perhaps partly because of the relative simplicity of the index, the HDI has managed to achieve a level of acceptance and use amongst politicians and policy makers that has yet to emerge with any indicator of sustainability. Indeed, despite its existence for 11 years, including nine years after the Rio Earth Summit, the HDI has not even been modified to take on board wider issues of sustainability. This paper will critically examine the potential for 'greening' the HDI so as to include environmental and resource-consumption dimensions. Copyright (C) 2003 John Wiley & Sons, Ltd and ERP Environment.
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Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC-AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water-balance-related parameters. Temperature-dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon 'dieback' results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long-term investments are required.
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Heat waves are expected to increase in frequency and magnitude with climate change. The first part of a study to produce projections of the effect of future climate change on heat-related mortality is presented. Separate city-specific empirical statistical models that quantify significant relationships between summer daily maximum temperature (T max) and daily heat-related deaths are constructed from historical data for six cities: Boston, Budapest, Dallas, Lisbon, London, and Sydney. ‘Threshold temperatures’ above which heat-related deaths begin to occur are identified. The results demonstrate significantly lower thresholds in ‘cooler’ cities exhibiting lower mean summer temperatures than in ‘warmer’ cities exhibiting higher mean summer temperatures. Analysis of individual ‘heat waves’ illustrates that a greater proportion of mortality is due to mortality displacement in cities with less sensitive temperature–mortality relationships than in those with more sensitive relationships, and that mortality displacement is no longer a feature more than 12 days after the end of the heat wave. Validation techniques through residual and correlation analyses of modelled and observed values and comparisons with other studies indicate that the observed temperature–mortality relationships are represented well by each of the models. The models can therefore be used with confidence to examine future heat-related deaths under various climate change scenarios for the respective cities (presented in Part 2).