985 resultados para Variability Model


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The newly developed atmosphere–ocean-chemistry-climate model SOCOL-MPIOM is presented by demonstrating the influence of the interactive chemistry module on the climate state and the variability. Therefore, we compare pre-industrial control simulations with (CHEM) and without (NOCHEM) interactive chemistry. In general, the influence of the chemistry on the mean state and the variability is small and mainly restricted to the stratosphere and mesosphere. The largest differences are found for the atmospheric dynamics in the polar regions, with slightly stronger northern and southern winter polar vortices in CHEM. The strengthening of the vortex is related to larger stratospheric temperature gradients, which are attributed to a parametrization of the absorption of ozone and oxygen in the Lyman-alpha, Schumann–Runge, Hartley, and Higgins bands. This effect is parametrized in the version with interactive chemistry only. A second reason for the temperature differences between CHEM and NOCHEM is related to diurnal variations in the ozone concentrations in the higher atmosphere, which are missing in NOCHEM. Furthermore, stratospheric water vapour concentrations differ substantially between the two experiments, but their effect on the temperatures is small. In both setups, the simulated intensity and variability of the northern polar vortex is inside the range of present day observations. Sudden stratospheric warming events are well reproduced in terms of their frequency, but the distribution amongst the winter months is too uniform. Additionally, the performance of SOCOL-MPIOM under changing external forcings is assessed for the period 1600–2000 using an ensemble of simulations driven by a spectral solar forcing reconstruction. The amplitude of the reconstruction is large in comparison to other state-of-the-art reconstructions, providing an upper limit for the importance of the solar signal. In the pre-industrial period (1600–1850) the simulated surface temperature trends are in reasonable agreement with temperature reconstructions, although the multi-decadal variability is more pronounced. This enhanced variability can be attributed to the variability in the solar forcing. The simulated temperature reductions during the Maunder Minimum are in the lowest probability range of the proxy records. During the Dalton Minimum, when also volcanic forcing is an important driver of temperature variations, the agreement is better. In the industrial period from 1850 onward SOCOL-MPIOM overestimates the temperature increase in comparison to observational data sets. Sensitivity simulations show that this overestimation can be attributed to the increasing trend in the solar forcing reconstruction that is used in this study and an additional warming induced by the simulated ozone changes.

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Decadal and longer timescale variability in the winter North Atlantic Oscillation (NAO) has considerable impact on regional climate, yet it remains unclear what fraction of this variability is potentially predictable. This study takes a new approach to this question by demonstrating clear physical differences between NAO variability on interannual-decadal (<30 year) and multidecadal (>30 year) timescales. It is shown that on the shorter timescale the NAO is dominated by variations in the latitude of the North Atlantic jet and storm track, whereas on the longer timescale it represents changes in their strength instead. NAO variability on the two timescales is associated with different dynamical behaviour in terms of eddy-mean flow interaction, Rossby wave breaking and blocking. The two timescales also exhibit different regional impacts on temperature and precipitation and different relationships to sea surface temperatures. These results are derived from linear regression analysis of the Twentieth Century and NCEP-NCAR reanalyses and of a high-resolution HiGEM General Circulation Model control simulation, with additional analysis of a long sea level pressure reconstruction. Evidence is presented for an influence of the ocean circulation on the longer timescale variability of the NAO, which is particularly clear in the model data. As well as providing new evidence of potential predictability, these findings are shown to have implications for the reconstruction and interpretation of long climate records.

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In this study, we use IP and alkenone biomarker proxies to document the subdecadal variations of sea ice and sea surface temperature in the subpolar North Atlantic induced by the decadally paced explosive tropical volcanic eruptions of the second half of the thirteenth century. The short- and long-term evolutions of both variables were investigated by cross analysis with a simulation of the IPSL-CM5A LR model. Our results show short-term ocean cooling and sea ice expansion in response to each volcanic eruption. They also highlight that the long response time of the ocean leads to cumulative surface cooling and subsurface heat buildup due to sea ice capping. As volcanic forcing relaxes, the surface ocean rapidly warms, likely amplified by subsurface heat, and remains almost ice free for several decades

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Based on common aspects of recent models of career decision-making (CDM) a sixphase model of CDM for secondary students is presented and empirically evaluated. The study tested the hypothesis that students who are in later phases possess more career choice readiness and consider different numbers of career alternatives. 266 Swiss secondary students completed measures tapping phase of CDM, career choice readiness, and number of considered career options. Career choice readiness showed an increase with phase of CDM. Later phases were generally associated with a larger increase in career choice readiness. Number of considered career options showed a curve-linear development with fewer options considered at the beginning and at the end of the process. Male students showed a larger variability in their distribution among the process with more male than female students in the first and last phase of the process. Implications for theory and practice are presented.

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It has been widely accepted for some time that species-appropriate environmental enrichment is important for the welfare of research animals, but its impact on research data initially received little attention. This has now changed, as the use of enrichment as one element of routine husbandry has expanded. In addition to its use in the care of larger research animals, such as nonhuman primates, it is now being used to improve the environments of small research animals, such as rodents, which are used in significantly greater numbers and in a wide variety of studies. Concern has been expressed that enrichment negatively affects both experimental validity and reproducibility. However, when a concise definition of enrichment is used, with a sound understanding of the biology and behaviour of the animal as well as the research constraints, it becomes clear that the welfare of research animals can be enhanced through environmental enrichment without compromising their purpose. Indeed, it is shown that the converse is true: the provision of suitable enrichment enhances the well-being of the animal, thereby refining the animal model and improving the research data. Thus, the argument is made that both the validity and reproducibility of the research are enhanced when proper consideration is given to the research animal's living environment and the animal's opportunities to express species-typical behaviours.

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Chrysophyte cysts are recognized as powerful proxies of cold-season temperatures. In this paper we use the relationship between chrysophyte assemblages and the number of days below 4 °C (DB4 °C) in the epilimnion of a lake in northern Poland to develop a transfer function and to reconstruct winter severity in Poland for the last millennium. DB4 °C is a climate variable related to the length of the winter. Multivariate ordination techniques were used to study the distribution of chrysophytes from sediment traps of 37 low-land lakes distributed along a variety of environmental and climatic gradients in northern Poland. Of all the environmental variables measured, stepwise variable selection and individual Redundancy analyses (RDA) identified DB4 °C as the most important variable for chrysophytes, explaining a portion of variance independent of variables related to water chemistry (conductivity, chlorides, K, sulfates), which were also important. A quantitative transfer function was created to estimate DB4 °C from sedimentary assemblages using partial least square regression (PLS). The two-component model (PLS-2) had a coefficient of determination of View the MathML sourceRcross2 = 0.58, with root mean squared error of prediction (RMSEP, based on leave-one-out) of 3.41 days. The resulting transfer function was applied to an annually-varved sediment core from Lake Żabińskie, providing a new sub-decadal quantitative reconstruction of DB4 °C with high chronological accuracy for the period AD 1000–2010. During Medieval Times (AD 1180–1440) winters were generally shorter (warmer) except for a decade with very long and severe winters around AD 1260–1270 (following the AD 1258 volcanic eruption). The 16th and 17th centuries and the beginning of the 19th century experienced very long severe winters. Comparison with other European cold-season reconstructions and atmospheric indices for this region indicates that large parts of the winter variability (reconstructed DB4 °C) is due to the interplay between the oscillations of the zonal flow controlled by the North Atlantic Oscillation (NAO) and the influence of continental anticyclonic systems (Siberian High, East Atlantic/Western Russia pattern). Differences with other European records are attributed to geographic climatological differences between Poland and Western Europe (Low Countries, Alps). Striking correspondence between the combined volcanic and solar forcing and the DB4 °C reconstruction prior to the 20th century suggests that winter climate in Poland responds mostly to natural forced variability (volcanic and solar) and the influence of unforced variability is low.

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The Mediterranean region has been identified as a global warming hotspot, where future climate impacts are expected to have significant consequences on societal and ecosystem well-being. To put ongoing trends of summer climate into the context of past natural variability, we reconstructed climate from maximum latewood density (MXD) measurements of Pinus heldreichii (1521–2010) and latewood width (LWW) of Pinus nigra (1617–2010) on Mt. Olympus, Greece. Previous research in the northeastern Mediterranean has primarily focused on inter-annual variability, omitting any low-frequency trends. The present study utilizes methods capable of retaining climatically driven long-term behavior of tree growth. The LWW chronology corresponds closely to early summer moisture variability (May–July, r = 0.65, p < 0.001, 1950–2010), whereas the MXD-chronology relates mainly to late summer warmth (July–September, r = 0.64, p < 0.001; 1899–2010). The chronologies show opposing patterns of decadal variability over the twentieth century (r = −0.68, p < 0.001) and confirm the importance of the summer North Atlantic Oscillation (sNAO) for summer climate in the northeastern Mediterranean, with positive sNAO phases inducing cold anomalies and enhanced cloudiness and precipitation. The combined reconstructions document the late twentieth—early twenty-first century warming and drying trend, but indicate generally drier early summer and cooler late summer conditions in the period ~1700–1900 CE. Our findings suggest a potential decoupling between twentieth century atmospheric circulation patterns and pre-industrial climate variability. Furthermore, the range of natural climate variability stretches beyond summer moisture availabilityobserved in recent decades and thus lends credibility to the significant drying trends projected for this region in current Earth System Model simulations.

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Information on the relationship between cumulative fossil CO2 emissions and multiple climate targets is essential to design emission mitigation and climate adaptation strategies. In this study, the transient response of a climate or environmental variable per trillion tonnes of CO2 emissions, termed TRE, is quantified for a set of impact-relevant climate variables and from a large set of multi-forcing scenarios extended to year 2300 towards stabilization. An  ∼ 1000-member ensemble of the Bern3D-LPJ carbon–climate model is applied and model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte Carlo-type framework. Uncertainties in TRE estimates include both scenario uncertainty and model response uncertainty. Cumulative fossil emissions of 1000 Gt C result in a global mean surface air temperature change of 1.9 °C (68 % confidence interval (c.i.): 1.3 to 2.7 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and a steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic meridional overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The constrained model ensemble is also applied to determine the response to a pulse-like emission and in idealized CO2-only simulations. The transient climate response is constrained, primarily by long-term ocean heat observations, to 1.7 °C (68 % c.i.: 1.3 to 2.2 °C) and the equilibrium climate sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability.

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The fatality risk caused by avalanches on road networks can be analysed using a long-term approach, resulting in a mean value of risk, and with emphasis on short-term fluctuations due to the temporal variability of both, the hazard potential and the damage potential. In this study, the approach for analysing the long-term fatality risk has been adapted by modelling the highly variable short-term risk. The emphasis was on the temporal variability of the damage potential and the related risk peaks. For defined hazard scenarios resulting from classified amounts of snow accumulation, the fatality risk was calculated by modelling the hazard potential and observing the traffic volume. The avalanche occurrence probability was calculated using a statistical relationship between new snow height and observed avalanche releases. The number of persons at risk was determined from the recorded traffic density. The method resulted in a value for the fatality risk within the observed time frame for the studied road segment. The long-term fatality risk due to snow avalanches as well as the short-term fatality risk was compared to the average fatality risk due to traffic accidents. The application of the method had shown that the long-term avalanche risk is lower than the fatality risk due to traffic accidents. The analyses of short-term avalanche-induced fatality risk provided risk peaks that were 50 times higher than the statistical accident risk. Apart from situations with high hazard level and high traffic density, risk peaks result from both, a high hazard level combined with a low traffic density and a high traffic density combined with a low hazard level. This provided evidence for the importance of the temporal variability of the damage potential for risk simulations on road networks. The assumed dependence of the risk calculation on the sum of precipitation within three days is a simplified model. Thus, further research is needed for an improved determination of the diurnal avalanche probability. Nevertheless, the presented approach may contribute as a conceptual step towards a risk-based decision-making in risk management.

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Understanding the preferential timescales of variability in the North Atlantic, usually associated with the Atlantic meridional overturning circulation (AMOC), is essential for the prospects for decadal prediction. However, the wide variety of mechanisms proposed from the analysis of climate simulations, potentially dependent on the models themselves, has stimulated the debate of which processes take place in reality. One mechanism receiving increasing attention, identified both in idealized models and observations, is a westward propagation of subsurface buoyancy anomalies that impact the AMOC through a basin-scale intensification of the zonal density gradient, enhancing the northward transport via thermal wind balance. In this study, we revisit a control simulation from the Institut Pierre-Simon Laplace Coupled Model 5A (IPSL-CM5A), characterized by a strong AMOC periodicity at 20 years, previously explained by an upper ocean–atmosphere–sea ice coupled mode driving convection activity south of Iceland. Our study shows that this mechanism interacts constructively with the basin-wide propagation in the subsurface. This constructive feedback may explain why bi-decadal variability is so intense in this coupled model as compared to others.

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We analyse the variability of the probability distribution of daily wind speed in wintertime over Northern and Central Europe in a series of global and regional climate simulations covering the last centuries, and in reanalysis products covering approximately the last 60 years. The focus of the study lies on identifying the link of the variations in the wind speed distribution to the regional near-surface temperature, to the meridional temperature gradient and to the North Atlantic Oscillation. Our main result is that the link between the daily wind distribution and the regional climate drivers is strongly model dependent. The global models tend to behave similarly, although they show some discrepancies. The two regional models also tend to behave similarly to each other, but surprisingly the results derived from each regional model strongly deviates from the results derived from its driving global model. In addition, considering multi-centennial timescales, we find in two global simulations a long-term tendency for the probability distribution of daily wind speed to widen through the last centuries. The cause for this widening is likely the effect of the deforestation prescribed in these simulations. We conclude that no clear systematic relationship between the mean temperature, the temperature gradient and/or the North Atlantic Oscillation, with the daily wind speed statistics can be inferred from these simulations. The understand- ing of past and future changes in the distribution of wind speeds, and thus of wind speed extremes, will require a detailed analysis of the representation of the interaction between large-scale and small-scale dynamics.

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Lake Ohrid (Macedonia, Albania) is thought to be more than 1.2 million years old and host more than 300 endemic species. As a target of the International Continental scientific Drilling Program (ICDP), a successful deep drilling campaign was carried out within the scope of the Scientific Collaboration on Past Speciation Conditions in Lake Ohrid (SCOPSCO) project in 2013. Here, we present lithological, sedimentological, and (bio-)geochemical data from the upper 247.8 m composite depth of the overall 569 m long DEEP site sediment succession from the central part of the lake. According to an age model, which is based on 11 tephra layers (first-order tie points) and on tuning of bio-geochemical proxy data to orbital parameters (second-order tie points), the analyzed sediment sequence covers the last 637 kyr. The DEEP site sediment succession consists of hemipelagic sediments, which are interspersed by several tephra layers and infrequent, thin (< 5 cm) mass wasting deposits. The hemipelagic sediments can be classified into three different lithotypes. Lithotype 1 and 2 deposits comprise calcareous and slightly calcareous silty clay and are predominantly attributed to interglacial periods with high primary productivity in the lake during summer and reduced mixing during winter. The data suggest that high ion and nutrient concentrations in the lake water promoted calcite precipitation and diatom growth in the epilimnion during MIS15, 13, and 5. Following a strong primary productivity, highest interglacial temperatures can be reported for marine isotope stages (MIS) 11 and 5, whereas MIS15, 13, 9, and 7 were comparably cooler. Lithotype 3 deposits consist of clastic, silty clayey material and predominantly represent glacial periods with low primary productivity during summer and longer and intensified mixing during winter. The data imply that the most severe glacial conditions at Lake Ohrid persisted during MIS16, 12, 10, and 6, whereas somewhat warmer temperatures can be inferred for MIS14, 8, 4, and 2. Interglacial-like conditions occurred during parts of MIS14 and 8.

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In the California Current System the spring transition from poleward to equatorward alongshore wind stress heralds the beginning of upwelling-favorable conditions. The phytoplankton response to this transition is investigated using 8 years ( 1998-2005) of daily, 4-km resolution, Sea-viewing Wide Field of view Sensor ( SeaWiFS) chlorophyll a concentration data. Cluster analysis of the chlorophyll a time series at each location is used to separate the inshore upwelling region from offshore and oligotrophic areas. An objective method for estimating the timing of bloom initiation is used to construct a map of the mean bloom start date. Interannual variability in bloom timing and magnitude is investigated in four regions: 45 degrees N - 50 degrees N, 40 degrees N - 45 degrees N, 35 degrees N - 40 degrees N and 20 degrees N - 35 degrees N. Daily satellite derived wind data ( QuikSCAT) allow the timing of the first episode of persistently upwelling favorable winds to be estimated. Bloom initiation generally coincides with the onset of upwelling winds ( +/- 15 days). South of similar to 35 degrees N, where winds are southward year-round, the timing of increased chlorophyll concentration corresponds closely to timing of the seasonal increase in upwelling intensity. A 1-D model and satellite derived photosynthetically available radiation data are used to estimate time series of depth- averaged irradiance. In the far north of the region (> 46 degrees N) light is shown to limit phytoplankton growth in early spring. In 2005 the spring bloom in the northern regions (> 35 degrees N) had a "false start''. A sharp increase in chl a in February quickly receded, and a sustained increase in biomass was delayed until July. We hypothesize that this resulted in a mismatch in timing of food availability to higher trophic levels.

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Abundance of the Ommastrephes bartramii winter-spring cohort fluctuated greatly from 1995 to 2004. To understand how abundance was influenced by sea surface conditions, we examined the variations in the proportion of thermal habitats with favourable sea surface temperature (SST). The SST data of both the spawning and feeding grounds were used to calculate the monthly proportion of favourable-SST areas (PFSSTA). Catch per fishing day per fishing boat (catch per unit effort, CPUE) of the Chinese mainland squid-jigging fleet was used as squid abundance index. The relationships between CPUE and monthly PFSSTA at spawning and feeding grounds were analyzed, and the relationship between CPUE and selected PFSSTA was quantified with a multiple linear regression model. Results showed that February PFSSTA at the spawning ground and August to November PFSSTA at the feeding ground could account for about 60% of the variability in O. bartramii abundance between 1995 and 2004, that February was the most important period influencing squid recruitment during the spawning season, and that feeding ground PFSSTA during the fishing season would influence CPUE by causing squid to aggregate. Our forecast model was found to perform well when we compared the model-predicted CPUEs and the average CPUEs observed during August to November in 2005 and 2006 from the Chinese squid-jigging fishery.

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Climate variability drives significant changes in the physical state of the North Pacific, and there may be important impacts of this variability on the upper ocean carbon balance across the basin. We address this issue by considering the response of seven biogeochemical ocean models to climate variability in the North Pacific. The models' upper ocean pCO(2) and air-sea CO(2) flux respond similarly to climate variability on seasonal to decadal timescales. Modeled seasonal cycles of pCO(2) and its temperature- and non-temperature-driven components at three contrasting oceanographic sites capture the basic features found in observations (Takahashi et al., 2002, 2006; Keeling et al., 2004; Brix et al., 2004). However, particularly in the Western Subarctic Gyre, the models have difficulty representing the temporal structure of the total pCO(2) seasonal cycle because it results from the difference of these two large and opposing components. In all but one model, the air-sea CO(2) flux interannual variability (1 sigma) in the North Pacific is smaller ( ranges across models from 0.03 to 0.11 PgC/yr) than in the Tropical Pacific ( ranges across models from 0.08 to 0.19 PgC/yr), and the time series of the first or second EOF of the air-sea CO(2) flux has a significant correlation with the Pacific Decadal Oscillation (PDO). Though air-sea CO(2) flux anomalies are correlated with the PDO, their magnitudes are small ( up to +/- 0.025 PgC/yr ( 1 sigma)). Flux anomalies are damped because anomalies in the key drivers of pCO(2) ( temperature, dissolved inorganic carbon (DIC), and alkalinity) are all of similar magnitude and have strongly opposing effects that damp total pCO(2) anomalies.