283 resultados para Intergovernmental Panel on Climate Change


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Recent urban air temperature increase is attributable to the climate change and heat island effects due to urbanization. This combined effects of urbanization and global warming can penetrate into the underground and elevate the subsurface temperature. In the present study, over-100 years measurements of subsurface temperature at a remote rural site were analysed, and an increasing rate of 0.17⁰C per decade at soil depth of 30cm due to climate change was identified in the UK, but the subsurface warming in an urban site showed a much higher rate of 0.85⁰C per decade at a 30cm depth and 1.18⁰C per decade at 100cm. The subsurface urban heat island (SUHI) intensity obtained at the paired urban-rural stations in London showed an unique 'U-shape', i.e. lowest in summer and highest during winter. The maximum SUHII is 3.5⁰C at 6:00 AM in December, and the minimum UHII is 0.2⁰C at 18:00PM in July. Finally, the effects of SUHI on the energy efficiency of the horizontal ground source heat pump (GSHP) were determined. Provided the same heat pump used, the installation at an urban site will maintain an overall higher COP compared with that at a rural site in all seasons, but the highest COP improvement can be achieved in winter.

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Climate models indicate a future wintertime precipitation reduction in the Mediterranean region but there is large uncertainty in the amplitude of the projected change. We analyse CMIP5 climate model output to quantify the role of atmospheric circulation in the Mediterranean precipitation change. It is found that a simple circulation index, i.e. the 850 hPa zonal wind (U850) in North Africa, well describes the year to year fluctuations in the area-averaged Mediterranean precipitation, with positive (i.e. westerly) U850 anomalies in North Africa being associated with positive precipitation anomalies. Under climate change, U850 in North Africa and the Mediterranean precipitation are both projected to decrease consistently with the relationship found in the inter-annual variability. This enables us to estimate that about 85% of the CMIP5 mean precipitation response and 80% of the variance in the inter-model spread are related to changes in the atmospheric circulation. In contrast, there is no significant correlation between the mean precipitation response and the global-mean surface warming across the models. It follows that the uncertainty in cold-season Mediterranean precipitation projection will not be narrowed unless the uncertainty in the atmospheric circulation response is reduced.

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Climate change is expected to increase the frequency of some climatic extremes. These may have drastic impacts on biodiversity, particularly if meteorological thresholds are crossed, leading to population collapses. Should this occur repeatedly, populations may be unable to recover, resulting in local extinctions. Comprehensive time series data on butterflies in Great Britain provide a rare opportunity to quantify population responses to both past severe drought and the interaction with habitat area and fragmentation. Here, we combine this knowledge with future projections from multiple climate models, for different Representative Concentration Pathways (RCPs), and for simultaneous modelled responses to different landscape characteristics. Under RCP8.5, which is associated with ‘business as usual’ emissions, widespread drought-sensitive butterfly population extinctions could occur as early as 2050. However, by managing landscapes and particularly reducing habitat fragmentation, the probability of persistence until mid-century improves from around zero to between 6 and 42% (95% confidence interval). Achieving persistence with a greater than 50% chance and right through to 2100 is possible only under both low climate change (RCP2.6) and semi-natural habitat restoration. Our data show that, for these drought-sensitive butterflies, persistence is achieved more effectively by restoring semi-natural landscapes to reduce fragmentation, rather than simply focusing on increasing habitat area, but this will only be successful in combination with substantial emission reductions.

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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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Global change drivers are known to interact in their effects on biodiversity, but much research to date ignores this complexity. As a consequence, there are problems in the attribution of biodiversity change to different drivers and, therefore, our ability to manage habitats and landscapes appropriately. Few studies explicitly acknowledge and account for interactive (i.e., nonadditive) effects of land use and climate change on biodiversity. One reason is that the mechanisms by which drivers interact are poorly understood. We evaluate such mechanisms, including interactions between demographic parameters, evolutionary trade-offs and synergies and threshold effects of population size and patch occupancy on population persistence. Other reasons for the lack of appropriate research are limited data availability and analytical issues in addressing interaction effects. We highlight the influence that attribution errors can have on biodiversity projections and discuss experimental designs and analytical tools suited to this challenge. Finally, we summarize the risks and opportunities provided by the existence of interaction effects. Risks include ineffective conservation management; but opportunities also arise, whereby the negative impacts of climate change on biodiversity can be reduced through appropriate land management as an adaptation measure. We hope that increasing the understanding of key mechanisms underlying interaction effects and discussing appropriate experimental and analytical designs for attribution will help researchers, policy makers, and conservation practitioners to better minimize risks and exploit opportunities provided by land use-climate change interactions.

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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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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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Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.