64 resultados para Positive climate

em CentAUR: Central Archive University of Reading - UK


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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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We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from 16 climate models and mapping the proportions of model runs showing forest/nonforest shifts or exceedance of natural variability in wildfire frequency and freshwater supply. Our analysis does not assign probabilities to scenarios or weights to models. Instead, we consider distribution of outcomes within three sets of model runs grouped by the amount of global warming they simulate: <2°C (including simulations in which atmospheric composition is held constant, i.e., in which the only climate change is due to greenhouse gases already emitted), 2–3°C, and >3°C. High risk of forest loss is shown for Eurasia, eastern China, Canada, Central America, and Amazonia, with forest extensions into the Arctic and semiarid savannas; more frequent wildfire in Amazonia, the far north, and many semiarid regions; more runoff north of 50°N and in tropical Africa and northwestern South America; and less runoff in West Africa, Central America, southern Europe, and the eastern U.S. Substantially larger areas are affected for global warming >3°C than for <2°C; some features appear only at higher warming levels. A land carbon sink of ≈1 Pg of C per yr is simulated for the late 20th century, but for >3°C this sink converts to a carbon source during the 21st century (implying a positive climate feedback) in 44% of cases. The risks continue increasing over the following 200 years, even with atmospheric composition held constant.

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Relationships between clear-sky longwave radiation and aspects of the atmospheric hydrological cycle are quantified in models, reanalyses, and observations over the period 1980-2000. The robust sensitivity of clear-sky surface net longwave radiation (SNLc) to column-integrated water vapor (CWV) of 1-1.5 Wm(-2) mm(-1) combined with the positive relationship between CWV and surface temperature (T-s) explains substantial increases in clear-sky longwave radiative cooling of the atmosphere (Q(LWc)) to the surface over the period. Clear-sky outgoing longwave radiation (OLRc) is highly sensitive to changes in aerosol and greenhouse gas concentrations in addition to temperature and humidity. Over tropical ocean regions of mean descent, Q(LWc) increases with T-s at similar to 3.5-5.5 W m(-2) K-1 for reanalyses, estimates derived from satellite data, and models without volcanic forcing included. Increased Q(LWc) with warming across the tropical oceans helps to explain model ensemble mean increases in precipitation of 0.1-0.15 mm day(-1) K-1, which are primarily determined by ascent regions where precipitation increases at the rate expected from the Clausius-Clapeyron equation. The implications for future projections in the atmospheric hydrological cycle are discussed

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The interannual variability of the hydrological cycle is diagnosed from the Hadley Centre and Geophysical Fluid Dynamics Laboratory (GFDL) climate models, both of which are forced by observed sea surface temperatures. The models produce a similar sensitivity of clear-sky outgoing longwave radiation to surface temperature of ∼2 W m−2 K−1, indicating a consistent and positive clear-sky radiative feedback. However, differences between changes in the temperature lapse-rate and the height dependence of moisture fluctuations suggest that contrasting mechanisms bring about this result. The GFDL model appears to give a weaker water vapor feedback (i.e., changes in specific humidity). This is counteracted by a smaller upper tropospheric temperature response to surface warming, which implies a compensating positive lapse-rate feedback.

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Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (−22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.

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Current changes in the tropical hydrological cycle, including water vapour and precipitation, are presented over the period 1979-2008 based on a diverse suite of observational datasets and atmosphere-only climate models. Models capture the observed variability in tropical moisture while reanalyses cannot. Observed variability in precipitation is highly dependent upon the satellite instruments employed and only cursory agreement with model simulations, primarily relating to the interannual variability associated with the El Niño Southern Oscillation. All datasets display a positive relationship between precipitation and surface temperature but with a large spread. The tendency for wet, ascending regions to become wetter at the expense of dry, descending regimes is in general reproduced. Finally, the frequency of extreme precipitation is shown to rise with warming in the observations and for the model ensemble mean but with large spread in the model simulations. The influence of the Earth’s radiative energy balance in relation to changes in the tropical water cycle are discussed

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Our understanding of the ancient ocean-atmosphere system has focused on oceanic proxies. However, the study of terrestrial proxies is equally necessary to constrain our understanding of ancient climates and linkages between the terrestrial and oceanic carbon reservoirs. We have analyzed carbon-isotope ratios from fossil plant material through the Valanginian and Lower Hauterivian from a shallow-marine, ammonite-constrained succession in the Crimean Peninsula of the southern Ukraine in order to determine if the Upper Valanginian positive carbon-isotope excursion is expressed in the atmosphere. delta(13)C(plant) values fluctuate around -23% to -22% for the Valanginian-Hauterivian, except during the Upper Valanginian where delta(13)C(plant) values record a positive excursion to similar to-18%. Based upon ammonite biostratigraphy from Crimea, and in conjunction with a composite Tethyan marine delta(13)C(carb) curve, several conclusions can be drawn: (1) the delta(13)C(plant) record indicates that the atmospheric carbon reservoir was affected; (2) the defined ammonite correlations between Europe and Crimea are synchronous; and (3) a change in photosynthetic carbon-isotope fractionation, caused by a decrease in atmospheric PCO2, occurred during the Upper Valanginian Positive delta(13)C excursion. Our new data, combined with other paleoenvironmental and paleoclimatic information, indicate that the Upper Valanginian was a cool period (icehouse) and highlights that the Cretaceous period was interrupted by periods of cooling and was not an equable climate as previously thought. (C) 2005 Elsevier B.V. All rights reserved.

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The paper discusses the observed and projected warming in the Caucasus region and its implications for glacier melt, water availability and potential hazards. A strong positive trend in summer air temperatures of 0.05 degrees C year(-1) is observed in the high-altitude areas (above 2000 m) providing for a strong glacier melt. A widespread glacier retreat has also been reported between 1985 and 2000, with an average rate of 8 m year(-1). A warming of 5-7 degrees C is projected for the Sum mer months in the 2071-2100 period under the A2 emission group of scenarios, Suggesting that enhanced glacier melt and a changing water balance can be expected.

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The paper discusses the observed and projected warming in the Caucasus region and its implications for glacier melt and runoff. A strong positive trend in summer air temperatures of 0.05 degrees C a(-1) is observed in the high-altitude areas providing for a strong glacier melt and continuous decline in glacier mass balance. A warming of 4-7 degrees C and 3-5 degrees C is projected for the summer months in 2071-2100 under the A2 and B2 emission scenarios respectively, suggesting that enhanced glacier melt can be expected. The expected changes in winter precipitation will not compensate for the summer melt and glacier retreat is likely to continue. However, a projected small increase in both winter and summer precipitation combined with the enhanced glacier melt will result in increased summer runoff in the currently glaciated region of the Caucasus (independent of whether the region is glaciated at the end of the twenty-first century) by more than 50% compared with the baseline period.

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Long-term trends, interannual and intra-seasonal variability in the mass-balance record from Djankuat glacier, central Greater Caucasus, Russia, are related to local climate change, synoptic and large-scale anomalies in atmospheric circulation. A clear warming signal emerged in the central Greater Caucasus in the early 1990s, leading to a strong increase in ablation. In the absence of a compensating change in winter accumulation, the net mass balance of Djankuat has declined. The highest value of seasonal ablation on record was registered in the summer of 2000. At the beginning of the 21st century these trends reversed. Ablation was below average even in the summer of 2003, which was unusually warm in western Europe. Precipitation and winter accumulation were high, allowing for a partial recovery of net mass balance. The interannual variability in the components of mass balance is weakly related to the North Atlantic Oscillation (NAO) and the Scandinavian teleconnection patterns, but there is a clear link with the large-scale circulation anomalies represented by the Rossby pattern. Five synoptic categories have been identified for the ablation season of 2005, revealing a strong separation between components of radiation budget, air temperature and daily melt. Air temperature is the main control over melt. The highest values of daily ablation are related to the strongly positive NAO which forces high net radiation, and to the warm and moist advection from the Black Sea.

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This paper reports recent changes in the mass balance record from the Djankuat Glacier, central greater Caucasus, Russia, and investigates possible relationships between the components of mass balance, local climate, and distant atmospheric forcing. The results clearly show that a strong warming signal has emerged in the central greater Caucasus, particularly since the 1993/1994 mass balance year, and this has led to a significant increase in the summer ablation of Djankuat. At the same time, there has been no compensating consistent increase in winter precipitation and accumulation leading to the strong net loss of mass and increase in glacier runoff. Interannual variability in ablation and accumulation is partly associated with certain major patterns of Northern Hemisphere climatic variability. The positive phase of the North Pacific (NP) teleconnection pattern forces negative geopotential height and temperature anomalies over the Caucasus in summer and results in reduced summer melt, such as in the early 1990s, when positive NP extremes resulted in a temporary decline in ablation rates. The positive phase of the NP is related to El Nino-Southern Oscillation, and it is possible that a teleconnection between the tropical Pacific sea surface temperatures and summer air temperatures in the Caucasus is bridged through the NP pattern. More recently, the NP pattern was predominantly negative, and this distant moderating forcing on summer ablation in the Caucasus was absent. Statistically significant correlations are observed between accumulation and the Scandinavian (SCA) teleconnection pattern. The frequent occurrence of the positive SCA phase at the beginning of accumulation season results in lower than average snowfall and reduced accumulation. The relationship between the North Atlantic Oscillation (NAO), Arctic Oscillation, and accumulation is weak, although positive precipitation anomalies in the winter months are associated with the negative phase of the NAO. A stronger positive correlation is observed between accumulation on Djankuat and geopotential height over the Bay of Biscay unrelated to the established modes of the Northern Hemisphere climatic variability. These results imply that the mass balance of Djankuat is sensitive to the natural variability in the climate system. Distant forcing, however, explains only 16% of the variance in the ablation record and cannot fully explain the recent increase in ablation and negative mass balance.

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During the twentieth century sea surface temperatures in the Atlantic Ocean exhibited prominent multidecadal variations. The source of such variations has yet to be rigorously established—but the question of their impact on climate can be investigated. Here we report on a set of multimodel experiments to examine the impact of patterns of warming in the North Atlantic, and cooling in the South Atlantic, derived from observations, that is characteristic of the positive phase of the Atlantic Multidecadal Oscillation (AMO). The experiments were carried out with six atmospheric General Circulation Models (including two versions of one model), and a major goal was to assess the extent to which key climate impacts are consistent between the different models. The major climate impacts are found over North and South America, with the strongest impacts over land found over the United States and northern parts of South America. These responses appear to be driven by a combination of an off-equatorial Gill response to diabatic heating over the Caribbean due to increased rainfall within the region and a Northward shift in the Inter Tropical Convergence Zone (ITCZ) due to the anomalous cross-equatorial SST gradient. The majority of the models show warmer US land temperatures and reduced Mean Sea Level Pressure during summer (JJA) in response to a warmer North Atlantic and a cooler South Atlantic, in line with observations. However the majority of models show no significant impact on US rainfall during summer. Over northern South America, all models show reduced rainfall in southern hemisphere winter (JJA), whilst in Summer (DJF) there is a generally an increase in rainfall. However, there is a large spread amongst the models in the magnitude of the rainfall anomalies over land. Away from the Americas, there are no consistent significant modelled responses. In particular there are no significant changes in the North Atlantic Oscillation (NAO) over the North Atlantic and Europe in Winter (DJF). Additionally, the observed Sahel drying signal in African rainfall is not seen in the modelled responses. Suggesting that, in contrast to some studies, the Atlantic Multidecadal Oscillation was not the primary driver of recent reductions in Sahel rainfall.

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A surface forcing response framework is developed that enables an understanding of time-dependent climate change from a surface energy perspective. The framework allows the separation of fast responses that are unassociated with global-mean surface air temperature change (ΔT), which is included in the forcing, and slow feedbacks that scale with ΔT. The framework is illustrated primarily using 2 × CO2 climate model experiments and is robust across the models. For CO2 increases, the positive downward radiative component of forcing is smaller at the surface than at the tropopause, and so a rapid reduction in the upward surface latent heat (LH) flux is induced to conserve the tropospheric heat budget; this reduces the precipitation rate. Analysis of the time-dependent surface energy balance over sea and land separately reveals that land areas rapidly regain energy balance, and significant land surface warming occurs before global sea temperatures respond. The 2 × CO2 results are compared to a solar increase experiment and show that some fast responses are forcing dependent. In particular, a significant forcing from the fast hydrological response found in the CO2 experiments is much smaller in the solar experiment. The different fast response explains why previous equilibrium studies found differences in the hydrological sensitivity between these two forcings. On longer time scales, as ΔT increases, the net surface longwave and LH fluxes provide positive and negative surface feedbacks, respectively, while the net surface shortwave and sensible heat fluxes change little. It is found that in contrast to their fast responses, the longer-term response of both surface energy fluxes and the global hydrological cycle are similar for the different forcing agents.

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This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO2) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO2, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5-10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970-1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO2 concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061 +/- 0.0036 hPa per %CO2. Although an increase of 0.61 hPa in NAO for a doubling in CO2 represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models' inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.

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One of the major uncertainties in the ability to predict future climate change, and hence its impacts, is the lack of knowledge of the earth's climate sensitivity. Here, data are combined from the 1985-96 Earth Radiation Budget Experiment (ERBE) with surface temperature change information and estimates of radiative forcing to diagnose the climate sensitivity. Importantly, the estimate is completely independent of climate model results. A climate feedback parameter of 2.3 +/- 1.4 W m(-2) K-1 is found. This corresponds to a 1.0-4.1-K range for the equilibrium warming due to a doubling of carbon dioxide (assuming Gaussian errors in observable parameters, which is approximately equivalent to a uniform "prior" in feedback parameter). The uncertainty range is due to a combination of the short time period for the analysis as well as uncertainties in the surface temperature time series and radiative forcing time series, mostly the former. Radiative forcings may not all be fully accounted for; however, all argument is presented that the estimate of climate sensitivity is still likely to be representative of longer-term climate change. The methodology can be used to 1) retrieve shortwave and longwave components of climate feedback and 2) suggest clear-sky and cloud feedback terms. There is preliminary evidence of a neutral or even negative longwave feedback in the observations, suggesting that current climate models may not be representing some processes correctly if they give a net positive longwave feedback.