219 resultados para Change-over Designs
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Context: Emotion regulation is critically disrupted in depression and use of paradigms tapping these processes may uncover essential changes in neurobiology during treatment. In addition, as neuroimaging outcome studies of depression commonly utilize solely baseline and endpoint data – which is more prone to week-to week noise in symptomatology – we sought to use all data points over the course of a six month trial. Objective: To examine changes in neurobiology resulting from successful treatment. Design: Double-blind trial examining changes in the neural circuits involved in emotion regulation resulting from one of two antidepressant treatments over a six month trial. Participants were scanned pretreatment, at 2 months and 6 months posttreatment. Setting: University functional magnetic resonance imaging facility. Participants: 21 patients with Major Depressive Disorder and without other Axis I or Axis II diagnoses and 14 healthy controls. Interventions: Venlafaxine XR (doses up to 300mg) or Fluoxetine (doses up to 80mg). Main Outcome Measure: Neural activity, as measured using functional magnetic resonance imaging during performance of an emotion regulation paradigm as well as regular assessments of symptom severity by the Hamilton Rating Scale for Depression. To utilize all data points, slope trajectories were calculated for rate of change in depression severity as well as rate of change of neural engagement. Results: Those depressed individuals showing the steepest decrease in depression severity over the six months were those individuals showing the most rapid increases in BA10 and right DLPFC activity when regulating negative affect over the same time frame. This relationship was more robust than when using solely the baseline and endpoint data. Conclusions: Changes in PFC engagement when regulating negative affect correlate with changes in depression severity over six months. These results are buttressed by calculating these statistics which are more reliable and robust to week-to-week variation than difference scores.
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There are many geochemical reconstructions of environmental change in the mid and high latitudes but relatively few in the tropical latitudes, despite their considerable potential for reconstructing environmental processes that cannot be identified using more traditional proxies. Here we present one reconstruction of environmental change for the tropics. This reconstruction covers the past 50 ka using a suite of geochemical data from the high-resolution sequence of Lynch's Crater in northeast Queensland, Australia, a region highly sensitive to El Niño-Southern Oscillation (ENSO) activity. The 23 major oxides and trace elements measured could be summarised by extracting three axes using principal components analysis (accounting for 72% of the variability). The data indicate that the greatest variability in the geochemical data accounted for erosional activity within the catchment that was associated with past changes in the frequency of ENSO activity (though this was less sensitive during wetter periods, probably as a result of buffering by high vegetation cover). The remaining variability was largely explained by elements that form complexes with organic compounds (e.g., humic acids) and those that are important nutrients for specific vegetation types (and therefore a measure of vegetation distribution). For more detailed reconstructions, further work is required to disentangle the complex controls of elements within sedimentary sequences.
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The impact of climate change on wind power generation potentials over Europe is investigated by considering ensemble projections from two regional climate models (RCMs) driven by a global climate model (GCM). Wind energy density and its interannual variability are estimated based on hourly near-surface wind speeds. Additionally, the possible impact of climatic changes on the energy output of a sample 2.5-MW turbine is discussed. GCM-driven RCM simulations capture the behavior and variability of current wind energy indices, even though some differences exist when compared with reanalysis-driven RCM simulations. Toward the end of the twenty-first century, projections show significant changes of energy density on annual average across Europe that are substantially stronger in seasonal terms. The emergence time of these changes varies from region to region and season to season, but some long-term trends are already statistically significant in the middle of the twenty-first century. Over northern and central Europe, the wind energy potential is projected to increase, particularly in winter and autumn. In contrast, energy potential over southern Europe may experience a decrease in all seasons except for the Aegean Sea. Changes for wind energy output follow the same patterns but are of smaller magnitude. The GCM/RCM model chains project a significant intensification of both interannual and intra-annual variability of energy density over parts of western and central Europe, thus imposing new challenges to a reliable pan-European energy supply in future decades.
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Precipitation indices are commonly used as climate change indicators. Considering four Climate Variability and Predictability-recommended indices, this study assesses possible changes in their spatial patterns over Portugal under future climatic conditions. Precipitation data from the regional climate model Consortium for Small-Scale Modelling–Climate version of the Local Model (CCLM) ensemble simulations with ECHAM5/MPI-OM1 boundary conditions are used for this purpose. For recent–past, medians and probability density functions of the CCLM-based indices are validated against station-based and gridded observational dataset from ENSEMBLES-based (gridded daily precipitation data provided by the European Climate Assessment & Dataset project) indices. It is demonstrated that the model is able to realistically reproduce not only precipitation but also the corresponding extreme indices. Climate change projections for 2071–2100 (A1B and B1 SRES scenarios) reveal significant decreases in total precipitation, particularly in autumn over northwestern and southern Portugal, though changes exhibit distinct local and seasonal patterns and are typically stronger for A1B than for B1. The increase in winter precipitation over northeastern Portugal in A1B is the most important exception to the overall drying trend. Contributions of extreme precipitation events to total precipitation are also expected to increase, mainly in winter and spring over northeastern Portugal. Strong projected increases in the dry spell lengths in autumn and spring are also noteworthy, giving evidence for an extension of the dry season from summer to spring and autumn. Although no coupling analysis is undertaken, these changes are qualitatively related to modifications in the large-scale circulation over the Euro-Atlantic area, more specifically to shifts in the position of the Azores High and associated changes in the large-scale pressure gradient over the area.
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The synoptic evolution and some meteorological impacts of the European winter storm Kyrill that swept across Western, Central, and Eastern Europe between 17 and 19 January 2007 are investigated. The intensity and large storm damage associated with Kyrill is explained based on synoptic and mesoscale environmental storm features, as well as on comparisons to previous storms. Kyrill appeared on weather maps over the US state of Arkansas about four days before it hit Europe. It underwent an explosive intensification over the Western North Atlantic Ocean while crossing a very intense zonal polar jet stream. A superposition of several favourable meteorological conditions west of the British Isles caused a further deepening of the storm when it started to affect Western Europe. Evidence is provided that a favourable alignment of three polar jet streaks and a dry air intrusion over the occlusion and cold fronts were causal factors in maintaining Kyrill's low pressure very far into Eastern Europe. Kyrill, like many other strong European winter storms, was embedded in a pre-existing, anomalously wide, north-south mean sea-level pressure (MSLP) gradient field. In addition to the range of gusts that might be expected from the synoptic-scale pressure field, mesoscale features associated with convective overturning at the cold front are suggested as the likely causes for the extremely damaging peak gusts observed at many lowland stations during the passage of Kyrill's cold front. Compared to other storms, Kyrill was by far not the most intense system in terms of core pressure and circulation anomaly. However, the system moved into a pre-existing strong MSLP gradient located over Central Europe which extended into Eastern Europe. This fact is considered determinant for the anomalously large area affected by Kyrill. Additionally, considerations of windiness in climate change simulations using two state-of-the-art regional climate models driven by ECHAM5 indicate that not only Central, but also Eastern Central Europe may be affected by higher surface wind speeds at the end of the 21st century. These changes are partially associated with the increased pressure gradient over Europe which is identified in the ECHAM5 simulations. Thus, with respect to the area affected, as well as to the synoptic and mesoscale storm features, it is proposed that Kyrill may serve as an interesting study case to assess future storm impacts.
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Winter storm-track activity over the Northern Hemisphere and its changes in a greenhouse gas scenario (the Special Report on Emission Scenarios A1B forcing) are computed from an ensemble of 23 single runs from 16 coupled global climate models (CGCMs). All models reproduce the general structures of the observed climatological storm-track pattern under present-day forcing conditions. Ensemble mean changes resulting from anthropogenic forcing include an increase of baroclinic wave activity over the eastern North Atlantic, amounting to 5%–8% by the end of the twenty-first century. Enhanced activity is also found over the Asian continent and over the North Pacific near the Aleutian Islands. At high latitudes and over parts of the subtropics, activity is reduced. Variations of the individual models around the ensemble average signal are not small, with a median of the pattern correlation near r = 0.5. There is, however, no evidence for a link between deviations in present-day climatology and deviations with respect to climate change.
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Boreal winter wind storm situations over Central Europe are investigated by means of an objective cluster analysis. Surface data from the NCEP-Reanalysis and ECHAM4/OPYC3-climate change GHG simulation (IS92a) are considered. To achieve an optimum separation of clusters of extreme storm conditions, 55 clusters of weather patterns are differentiated. To reduce the computational effort, a PCA is initially performed, leading to a data reduction of about 98 %. The clustering itself was computed on 3-day periods constructed with the first six PCs using "k-means" clustering algorithm. The applied method enables an evaluation of the time evolution of the synoptic developments. The climate change signal is constructed by a projection of the GCM simulation on the EOFs attained from the NCEP-Reanalysis. Consequently, the same clusters are obtained and frequency distributions can be compared. For Central Europe, four primary storm clusters are identified. These clusters feature almost 72 % of the historical extreme storms events and add only to 5 % of the total relative frequency. Moreover, they show a statistically significant signature in the associated wind fields over Europe. An increased frequency of Central European storm clusters is detected with enhanced GHG conditions, associated with an enhancement of the pressure gradient over Central Europe. Consequently, more intense wind events over Central Europe are expected. The presented algorithm will be highly valuable for the analysis of huge data amounts as is required for e.g. multi-model ensemble analysis, particularly because of the enormous data reduction.
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In the first part of this paper (Ulbrich et al. 2003), we gave a description of the August 2002 rainfall events and the resultant floods, in particular of the flood wave of the River Elbe. The extreme precipitation sums observed in the first half of the month were primarily associated with two rainfall episodes. The first episode occurred on 6/7 August 2002. The main rainfall area was situated over Lower Austria, the south-western part of the Czech Republic and south-eastern Germany. A severe flash flood was produced in the Lower Austrian Waldviertel (`forest quarter’ ). The second episode on 11± 13 August 2002 most severely affected the Erz Mountains and western parts of the Czech Republic. During this second episode 312mm of rain was recorded between 0600GMT on 12 August and 0600GMT on 13 August at the Zinnwald weather station in the ErzMountains, which is a new 24-hour record for Germany. The flash floods resulting from this rainfall episode and the subsequent Elbe flood produced the most expensive weatherrelated catastrophe in Europe in recent decades. In this part of the paper we discuss the meteorological conditions and physical mechanisms leading to the two main events. Similarities to the conditions that led to the recent summer floods of the River Oder in 1997 and the River Vistula in 2001 will be shown. This will lead us to a consideration of trends in extreme rainfall over Europe which are found in numerical simulations of anthropogenic climate change.
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We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.
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We used fossil pollen to investigate the response of the eastern Chiquitano seasonally-dry tropical forest (SDTF), lowland Bolivia, to high-amplitude climate change associated with glacial–interglacial cycles. Changes in the structure, composition and diversity of the past vegetation are compared with palaeoclimate data previously reconstructed from the same record, and these results shed light on the biogeographic history of today’s highly disjunct blocks of SDTF across South America. We demonstrate that lower glacial temperatures limited tropical forest in the Chiquitanía region, and suggest that SDTF was absent or restricted at latitudes below 17°S, the proposed location of the majority of the hypothesized ‘Pleistocene dry forest arc’ (PDFA). At 19500 yrs b.p., warming supported the establishment of a floristically-distinct SDTF, which showed little change throughout the glacial–Holocene transition, despite a shift to significantly wetter conditions beginning ca. 12500–12200 yrs b.p. Anadenanthera colubrina, a key SDTF taxon, arrived at 10000 yrs b.p., which coincides with the onset of drought associated with an extended dry season. Lasting until 3000 yrs b.p., Holocene drought caused a floristic shift to more drought-tolerant taxa and a reduction in α-diversity (shown by declining palynological richness), but closed-canopy forest was maintained throughout. In contrast to the PDFA, the modern distribution of SDTF most likely represents the greatest spatial coverage of these forests in southern South America since glacial times. We find that temperature is a key climatic control upon the distribution of lowland South American SDTF over glacial-interglacial timescales, and seasonality of rainfall exerts a strong control on their floristic composition.
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Quantitative simulations of the global-scale benefits of climate change mitigation are presented, using a harmonised, self-consistent approach based on a single set of climate change scenarios. The approach draws on a synthesis of output from both physically-based and economics-based models, and incorporates uncertainty analyses. Previous studies have projected global and regional climate change and its impacts over the 21st century but have generally focused on analysis of business-as-usual scenarios, with no explicit mitigation policy included. This study finds that both the economics-based and physically-based models indicate that early, stringent mitigation would avoid a large proportion of the impacts of climate change projected for the 2080s. However, it also shows that not all the impacts can now be avoided, so that adaptation would also therefore be needed to avoid some of the potential damage. Delay in mitigation substantially reduces the percentage of impacts that can be avoided, providing strong new quantitative evidence for the need for stringent and prompt global mitigation action on greenhouse gas emissions, combined with effective adaptation, if large, widespread climate change impacts are to be avoided. Energy technology models suggest that such stringent and prompt mitigation action is technologically feasible, although the estimated costs vary depending on the specific modelling approach and assumptions.
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The likelihood that continuing greenhouse-gas emissions will lead to an unmanageable degree of climate change [1] has stimulated the search for planetary-scale technological solutions for reducing global warming [2] (“geoengineering”), typically characterized by the necessity for costly new infrastructures and industries [3]. We suggest that the existing global infrastructure associated with arable agriculture can help, given that crop plants exert an important influence over the climatic energy budget 4 and 5 because of differences in their albedo (solar reflectivity) compared to soils and to natural vegetation [6]. Specifically, we propose a “bio-geoengineering” approach to mitigate surface warming, in which crop varieties having specific leaf glossiness and/or canopy morphological traits are specifically chosen to maximize solar reflectivity. We quantify this by modifying the canopy albedo of vegetation in prescribed cropland areas in a global-climate model, and thereby estimate the near-term potential for bio-geoengineering to be a summertime cooling of more than 1°C throughout much of central North America and midlatitude Eurasia, equivalent to seasonally offsetting approximately one-fifth of regional warming due to doubling of atmospheric CO2[7]. Ultimately, genetic modification of plant leaf waxes or canopy structure could achieve greater temperature reductions, although better characterization of existing intraspecies variability is needed first.
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The extent to which past climate change has dictated the pattern and timing of the out-of-Africa expansion by anatomically modern humans is currently unclear [Stewart JR, Stringer CB (2012) Science 335:1317–1321]. In particular, the incompleteness of the fossil record makes it difficult to quantify the effect of climate. Here, we take a different approach to this problem; rather than relying on the appearance of fossils or archaeological evidence to determine arrival times in different parts of the world, we use patterns of genetic variation in modern human populations to determine the plausibility of past demographic parameters. We develop a spatially explicit model of the expansion of anatomically modern humans and use climate reconstructions over the past 120 ky based on the Hadley Centre global climate model HadCM3 to quantify the possible effects of climate on human demography. The combinations of demographic parameters compatible with the current genetic makeup of worldwide populations indicate a clear effect of climate on past population densities. Our estimates of this effect, based on population genetics, capture the observed relationship between current climate and population density in modern hunter–gatherers worldwide, providing supporting evidence for the realism of our approach. Furthermore, although we did not use any archaeological and anthropological data to inform the model, the arrival times in different continents predicted by our model are also broadly consistent with the fossil and archaeological records. Our framework provides the most accurate spatiotemporal reconstruction of human demographic history available at present and will allow for a greater integration of genetic and archaeological evidence.
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Interpretation of ice-core records is currently limited by paucity of modelling at adequate temporal and spatial resolutions. Several key questions relate to mechanisms of polar amplification and inter-hemispheric coupling on glacial/interglacial timescales. Here, we present the first results from a large set of global ocean–atmosphere climate model ‘snap-shot’ simulations covering the last 120 000 years using the Hadley Centre climate model (HadCM3) at up to 1 kyr temporal resolution. Two sets of simulations were performed in order to examine the roles of orbit and greenhouse gases versus ice-sheet forcing of orbital-scale climate change. A series of idealised Heinrich events were also simulated, but no changes to aerosols or vegetation were prescribed. This paper focuses on high latitudes and inter-hemispheric linkages. The simulations reproduce polar temperature trends well compared to ice-core reconstructions, although the magnitude is underestimated. Polar amplification varies with obliquity, but this variability is dampened by including variations in land ice coverage, while the overall amplification factor increases. The relatively constant amplification of Antarctic temperatures (with ice-sheet forcing included) suggests it is possible to use Antarctic temperature reconstructions to estimate global changes (which are roughly half the magnitude). Atlantic Ocean overturning circulation varies considerably only with the introduction of Northern Hemisphere ice sheets, but only weakens in the North Atlantic in the deep glacial, when ocean–sea-ice feedbacks result in the movement of the region of deep convection to lower latitudes and with the introduction of freshwater to the surface North Atlantic in order to simulate Heinrich events.
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According to many modern economic theories, actions simply reflect an individual's preferences, whereas a psychological phenomenon called “cognitive dissonance” claims that actions can also create preference. Cognitive dissonance theory states that after making a difficult choice between two equally preferred items, the act of rejecting a favorite item induces an uncomfortable feeling (cognitive dissonance), which in turn motivates individuals to change their preferences to match their prior decision (i.e., reducing preference for rejected items). Recently, however, Chen and Risen [Chen K, Risen J (2010) J Pers Soc Psychol 99:573–594] pointed out a serious methodological problem, which casts a doubt on the very existence of this choice-induced preference change as studied over the past 50 y. Here, using a proper control condition and two measures of preferences (self-report and brain activity), we found that the mere act of making a choice can change self-report preference as well as its neural representation (i.e., striatum activity), thus providing strong evidence for choice-induced preference change. Furthermore, our data indicate that the anterior cingulate cortex and dorsolateral prefrontal cortex tracked the degree of cognitive dissonance on a trial-by-trial basis. Our findings provide important insights into the neural basis of how actions can alter an individual's preferences.