917 resultados para Inter-cycle Variability
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This conceptual paper aims to improve our understanding of how internationalised firms use outsourcing and offshoring strategies to manage knowledge and information through the life-cycle of integrated product-service solutions. More precisely, we identify the appropriate theoretical framework for this analysis and investigate through in-depth case studies how UK engineering firms organise, coordinate, and incentivise work that is executed in globally distributed teams. Our research focuses on their UK and India offices to study the organisation and governance of distributed teams. The research has several theoretical dimensions - organization; geography; time and knowledge - that it addresses as boundary challenges.
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There is evidence to suggest that insulin sensitivity may vary in response to changes in sex hormone levels. However, the results Of human studies designed to investigate changes in insulin sensitivity through the menstrual cycle have proved inconclusive. The aims of this Study were to 1) evaluate the impact of menstrual cycle phase on insulin sensitivity measures and 2) determine the variability Of insulin sensitivity measures within the same menstrual cycle phase. A controlled observational study of 13 healthy premenopausal women, not taking any hormone preparation and having regular menstrual cycles, was conducted. Insulin sensitivity (Si) and glucose effectiveness (Sg) were measured using an intravenous glucose tolerance test (IVGTT) with minimal model analysis. Additional Surrogate measures Of insulin sensitivity were calculated (homoeostasis model for insulin resistance [HOMA IR], quantitative insulin-to-glucose check index [QUICKI] and revised QUICKI [rQUICKI]), as well as plasma lipids. Each woman was tested in the luteal and follicular phases of her Menstrual cycle, and duplicate measures were taken in one phase of the cycle. No significant differences in insulin sensitivity (measured by the IVGTT or Surrogate markers) or plasma lipids were reported between the two phases of the menstrual cycle or between duplicate measures within the same phase. It was Concluded that variability in measures of insulin sensitivity were similar within and between menstrual phases.
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Purpose. Hyperopic retinal defocus (blur) is thought to be a cause of myopia. If the retinal image of an object is not clearly focused, the resulting blur is thought to cause the continuing lengthening of the eyeball during development causing a permanent refractive error. Both lag of accommodation, especially for near targets, and greater variability in the accommodative response, have been suggested as causes of increased hyperopic retinal blur. Previous studies of lag of accommodation show variable findings. In comparison, greater variability in the accommodative response has been demonstrated in adults with late onset myopia but has not been tested in children. This study looked at the lag and variability of accommodation in children with early onset myopia. Methods. Twenty-one myopic and 18 emmetropic children were tested. Dynamic measures of accommodation and pupil size were made using eccentric photorefraction (Power Refractor) while children viewed targets set at three different accommodative demands (0.25, 2, and 4 D). Results. We found no difference in accommodative lag between groups. However, the accommodative response was more variable in the myopes than emmetropes when viewing both the near (4 D) and far (0.25 D) targets. Since pupil size and variability also varied, we analyzed the data to determine whether this could account for the inter-group differences in accommodation variability. Variation in these factors was not found to be sufficient to explain these differences. Changes in the accommodative response variability with target distance were similar to patterns reported previously in adult emmetropes and late onset myopes. Conclusions. Children with early onset myopia demonstrate greater accommodative variability than emmetropic children, and have similar patterns of response to adult late onset myopes. This increased variability could result in an increase in retinal blur for both near and far targets. The role of accommodative variability in the etiology of myopia is discussed.
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We compare the variability of the Atlantic meridional overturning circulation (AMOC) as simulated by the coupled climate models of the RAPID project, which cover a wide range of resolution and complexity, and observed by the RAPID/MOCHA array at about 26N. We analyse variability on a range of timescales. In models of all resolutions there is substantial variability on timescales of a few days; in most AOGCMs the amplitude of the variability is of somewhat larger magnitude than that observed by the RAPID array, while the amplitude of the simulated annual cycle is similar to observations. A dynamical decomposition shows that in the models, as in observations, the AMOC is predominantly geostrophic (driven by pressure and sea-level gradients), with both geostrophic and Ekman contributions to variability, the latter being exaggerated and the former underrepresented in models. Other ageostrophic terms, neglected in the observational estimate, are small but not negligible. In many RAPID models and in models of the Coupled Model Intercomparison Project Phase 3 (CMIP3), interannual variability of the maximum of the AMOC wherever it lies, which is a commonly used model index, is similar to interannual variability in the AMOC at 26N. Annual volume and heat transport timeseries at the same latitude are well-correlated within 15-45N, indicating the climatic importance of the AMOC. In the RAPID and CMIP3 models, we show that the AMOC is correlated over considerable distances in latitude, but not the whole extent of the north Atlantic; consequently interannual variability of the AMOC at 50N is not well-correlated with the AMOC at 26N.
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The stratospheric climate and variability from simulations of sixteen chemistry‐climate models is evaluated. On average the polar night jet is well reproduced though its variability is less well reproduced with a large spread between models. Polar temperature biases are less than 5 K except in the Southern Hemisphere (SH) lower stratosphere in spring. The accumulated area of low temperatures responsible for polar stratospheric cloud formation is accurately reproduced for the Antarctic but underestimated for the Arctic. The shape and position of the polar vortex is well simulated, as is the tropical upwelling in the lower stratosphere. There is a wide model spread in the frequency of major sudden stratospheric warnings (SSWs), late biases in the breakup of the SH vortex, and a weak annual cycle in the zonal wind in the tropical upper stratosphere. Quantitatively, “metrics” indicate a wide spread in model performance for most diagnostics with systematic biases in many, and poorer performance in the SH than in the Northern Hemisphere (NH). Correlations were found in the SH between errors in the final warming, polar temperatures, the leading mode of variability, and jet strength, and in the NH between errors in polar temperatures, frequency of major SSWs, and jet strength. Models with a stronger QBO have stronger tropical upwelling and a colder NH vortex. Both the qualitative and quantitative analysis indicate a number of common and long‐standing model problems, particularly related to the simulation of the SH and stratospheric variability.
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We have examined the atmospheric water cycle of both Polar Regions, pole wards of 60°N and 60°S, using the ERA-Interim re-analysis and high-resolution simulations with the ECHAM5 model for both the present and future climate based on the IPCC, A1B scenario, representative of the last three decades of the 21st century. The annual precipitation in ERA-Interim amounts to ~17000 km3 and is more or less the same in the Arctic and the Antarctic, but it is composed differently. In the Arctic the annual evaporation is some 8000 km3 but some 3000 km3 less in the Antarctica where the net horizontal transport is correspondingly larger. The net water transport of the model is more intense than in ERA-Interim, in the Arctic the difference is 2.5% and in the Antarctic it is 6.2%. Precipitation and net horizontal transport in the Arctic has a maximum in August and September. Evaporation peaks in June and July. The seasonal cycle is similar in Antarctica with the highest precipitation in the austral autumn. The largest net transport occurs at the end of the major extra-tropical storm tracks in the Northern Hemisphere such as the eastern Pacific and eastern north Atlantic. The variability of the model is virtually identical to that of the re-analysis and there are no changes in variability between the present climate and the climate at the end of the 21st century when normalized with the higher level of moisture. The changes from year to year are substantial with the 20 and 30-year records being generally too short to identify robust trends in the hydrological cycle. In the A1B climate scenario the strength of the water cycle increases by some 25% in the Arctic and by 19% in the Antarctica, as measured by annual precipitation. The increase in the net horizontal transport is 29% and 22% respectively, and the increase in evaporation correspondingly less. The net transport follows closely the Clausius-Clapeyron relation. There is 2 a minor change in the annual cycle of the Arctic atmospheric water cycle with the maximum transport and precipitation occurring later in the year. There is a small imbalance of some 4-6% between the net transport and precipitation minus evaporation. We suggest that this is mainly due to the fact the transport is calculated from instantaneous 6-hourly data while precipitation and evaporation is accumulated over a 6 hour period. The residual difference is proportionally similar for all experiments and hardly varies from year to year.
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We compare the variability of the Atlantic meridional overturning circulation (AMOC) as simulated by the coupled climate models of the RAPID project, which cover a wide range of resolution and complexity, and observed by the RAPID/MOCHA array at about 26N. We analyse variability on a range of timescales, from five-daily to interannual. In models of all resolutions there is substantial variability on timescales of a few days; in most AOGCMs the amplitude of the variability is of somewhat larger magnitude than that observed by the RAPID array, while the time-mean is within about 10% of the observational estimate. The amplitude of the simulated annual cycle is similar to observations, but the shape of the annual cycle shows a spread among the models. A dynamical decomposition shows that in the models, as in observations, the AMOC is predominantly geostrophic (driven by pressure and sea-level gradients), with both geostrophic and Ekman contributions to variability, the latter being exaggerated and the former underrepresented in models. Other ageostrophic terms, neglected in the observational estimate, are small but not negligible. The time-mean of the western boundary current near the latitude of the RAPID/MOCHA array has a much wider model spread than the AMOC does, indicating large differences among models in the simulation of the wind-driven gyre circulation, and its variability is unrealistically small in the models. In many RAPID models and in models of the Coupled Model Intercomparison Project Phase 3 (CMIP3), interannual variability of the maximum of the AMOC wherever it lies, which is a commonly used model index, is similar to interannual variability in the AMOC at 26N. Annual volume and heat transport timeseries at the same latitude are well-correlated within 15--45N, indicating the climatic importance of the AMOC. In the RAPID and CMIP3 models, we show that the AMOC is correlated over considerable distances in latitude, but not the whole extent of the north Atlantic; consequently interannual variability of the AMOC at 50N, where it is particularly relevant to European climate, is not well-correlated with that of the AMOC at 26N, where it is monitored by the RAPID/MOCHA array.
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The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.
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In this study, 40-yr ECMWF Re-Analysis (ERA-40) data are used for the description of the seasonal cycle and the interannual variability of the westerly jet in the Tibetan Plateau region. To complement results based on the analysis of monthly mean horizontal wind speeds, an occurrence-based jet climatology is constructed by identifying the locations of the jet axes at 6-hourly intervals throughout 1958–2001. Thus, a dataset describing the highly transient and localized features of jet variability is obtained. During winter and summer the westerly jet is located, respectively, to the south and north of the Tibetan Plateau. During the spring and autumn seasons there are jet transitions from south to north and vice versa. The median dates for these transitions are 28 April and 12 October. The spring transition is associated with large interannual variations, while the fall transition occurs more reliably within a 3-week period. The strength of the jet exhibits a peculiar seasonal cycle. During northward migration in April/May, the jet intensity weakens and its latitudinal position varies largely. In some springs, there are several transitions and split configurations occur before the jet settles in its northern summer position. In June, a well-defined and unusually strong jet reappears at the northern flanks of the Tibetan Plateau. In autumn, the jet gradually but reliably recedes to the south and is typically more intense than in spring. The jet transitions between the two preferred locations follow the seasonal latitudinal migration of the jet in the Northern Hemisphere. An analysis of interannual variations shows the statistical relationship between the strength of the summer jet, the tropospheric meridional temperature gradient, and the all-India rainfall series. Both this analysis and results from previous studies point to the particular dynamical relevance of the onsetting Indian summer monsoon precipitation and the associated diabatic heating for the formation of the strong summer jet. Finally, an example is provided that illustrates the climatological significance of the jet in terms of the covariation between the jet location and the spatial precipitation distribution in central Asia.
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A number of transient climate runs simulating the last 120kyr have been carried out using FAMOUS, a fast atmosphere-ocean general circulation model (AOGCM). This is the first time such experiments have been done with a full AOGCM, providing a three-dimensional simulation of both atmosphere and ocean over this period. Our simulation thus includes internally generated temporal variability over periods from days to millennia, and physical, detailed representations of important processes such as clouds and precipitation. Although the model is fast, computational restrictions mean that the rate of change of the forcings has been increased by a factor of 10, making each experiment 12kyr long. Atmospheric greenhouse gases (GHGs), northern hemisphere ice sheets and variations in solar radiation arising from changes in the Earth's orbit are treated as forcing factors, and are applied either separately or combined in different experiments. The long-term temperature changes on Antarctica match well with reconstructions derived from ice-core data, as does variability on timescales longer than 10 kyr. Last Glacial Maximum (LGM) cooling on Greenland is reasonably well simulated, although our simulations, which lack ice-sheet meltwater forcing, do not reproduce the abrupt, millennial scale climate shifts seen in northern hemisphere climate proxies or their slower southern hemisphere counterparts. The spatial pattern of sea surface cooling at the LGM matches proxy reconstructions reasonably well. There is significant anti-correlated variability in the strengths of the Atlantic Meridional Overturning Circulation (AMOC) and the Antarctic Circumpolar Current (ACC) on timescales greater than 10kyr in our experiments. We find that GHG forcing weakens the AMOC and strengthens the ACC, whilst the presence of northern hemisphere ice-sheets strengthens the AMOC and weakens the ACC. The structure of the AMOC at the LGM is found to be sensitive to the details of the ice-sheet reconstruction used. The precessional component of the orbital forcing induces ~20kyr oscillations in the AMOC and ACC, whose amplitude is mediated by changes in the eccentricity of the Earth's orbit. These forcing influences combine, to first order, in a linear fashion to produce the mean climate and ocean variability seen in the run with all forcings.
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We present an intercomparison and verification analysis of 20 GCMs (Global Circulation Models) included in the 4th IPCC assessment report regarding their representation of the hydrological cycle on the Danube river basin for 1961–2000 and for the 2161–2200 SRESA1B scenario runs. The basin-scale properties of the hydrological cycle are computed by spatially integrating the precipitation, evaporation, and runoff fields using the Voronoi-Thiessen tessellation formalism. The span of the model- simulated mean annual water balances is of the same order of magnitude of the observed Danube discharge of the Delta; the true value is within the range simulated by the models. Some land components seem to have deficiencies since there are cases of violation of water conservation when annual means are considered. The overall performance and the degree of agreement of the GCMs are comparable to those of the RCMs (Regional Climate Models) analyzed in a previous work, in spite of the much higher resolution and common nesting of the RCMs. The reanalyses are shown to feature several inconsistencies and cannot be used as a verification benchmark for the hydrological cycle in the Danubian region. In the scenario runs, for basically all models the water balance decreases, whereas its interannual variability increases. Changes in the strength of the hydrological cycle are not consistent among models: it is confirmed that capturing the impact of climate change on the hydrological cycle is not an easy task over land areas. Moreover, in several cases we find that qualitatively different behaviors emerge among the models: the ensemble mean does not represent any sort of average model, and often it falls between the models’ clusters.
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Observations of noctilucent clouds have revealed a surprising coupling between the winter stratosphere and the summer polar mesopause region. In spite of the great distance involved, this inter-hemispheric link has been suggested to be the principal reason for both the year-to-year variability and the hemispheric differences in the frequency of occurrence of these high-altitude clouds. In this study, we investigate the dynamical influence of the winter stratosphere on the summer mesosphere using simulations from the vertically extended version of the Canadian Middle Atmosphere Model (CMAM). We find that for both Northern and Southern Hemispheres, variability in the summer polar mesopause region from one year to another can be traced back to the planetary-wave flux entering the winter stratosphere. The teleconnection pattern is the same for both positive and negative wave-flux anomalies. Using a composite analysis to isolate the events, it is argued that the mechanism for interhemispheric coupling is a feedback between summer mesosphere gravity-wave drag (GWD) and zonal wind, which is induced by an anomaly in mesospheric cross-equatorial flow, the latter arising from the anomaly in winter hemisphere GWD induced by the anomaly in stratospheric conditions.
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Red meat consumption causes a dose-dependent increase in fecal apparent total N-nitroso compounds (ATNC). The genotoxic effects of these ATNCs were investigated using two different Comet assay protocols to determine the genotoxicity of fecal water samples. Fecal water samples were obtained from two studies of a total of 21 individuals fed diets containing different amounts of red meat, protein, heme, and iron. The first protocol incubated the samples with HT-29 cells for 5 min at 4 degrees C, whereas the second protocol used a longer exposure time of 30 min and a higher incubation temperature of 37 degrees C. DNA strand breaks were quantified by the tail moment (DNA in the comet tail multiplied by the comet tail length). The results of the two Comet assay protocols were significantly correlated (r = 0.35, P = 0.003), however, only the second protocol resulted in detectable levels of DNA damage. Inter-individual effects were variable and there was no effect on fecal water genotoxicity by diet (P > 0.20), mean transit time (P = 0.588), or weight (P = 0.705). However, there was a highly significant effect of age (P = 0.019). There was no significant correlation between concentrations of ATNCs in fecal homogenates and fecal water genotoxicity (r = 0.04, P = 0.74). ATNC levels were lower in fecal water samples (272 microg/kg) compared to that of fecal homogenate samples (895 microg/kg) (P < 0.0001). Failure to find dietary effects on fecal water genotoxicity may therefore be attributed to individual variability and low levels of ATNCs in fecal water samples.
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Tropical-extratropical cloud band systems over southern Africa, known as tropical temperate troughs (TTTs), are known to contribute substantially to South African summer rainfall. This study performs a comprehensive assessment of the seasonal cycle and rainfall contribution of TTTs by using a novel object-based strategy that explicitly tracks these systems for their full life cycle. The methodology incorporates a simple assignment of station rainfall data to each event, thereby creating a database containing detailed rainfall characteristics for each TTT. This is used to explore the importance of TTTs for rain days and climatological rainfall totals in October–March. Average contributions range from 30 to 60 % with substantial spatial heterogeneity observed. TTT rainfall contributions over the Highveld and eastern escarpment are lower than expected. A short analysis of TTT rainfall variability indicates TTTs provide substantial, but not dominant, intraseasonal and interannual variability in station rainfall totals. TTTs are however responsible for a high proportion of heavy rainfall days. Of 52 extreme rainfall events in the 1979–1999 period, 30 are associated with these tropical-extratropical interactions. Cut-off lows were included in the evolution of 6 of these TTTs. The study concludes with an analysis of the question: does the Madden-Julian Oscillation influence the intensity of TTT rainfall over South Africa? Results suggest a weak but significant suppression (enhancement) of intensity during phase 1(6).
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Robust and physically understandable responses of the global atmospheric water cycle to a warming climate are presented. By considering interannual responses to changes in surface temperature (T), observations and AMIP5 simulations agree on an increase in column integrated water vapor at the rate 7 %/K (in line with the ClausiusClapeyron equation) and of precipitation at the rate 2-3 %/K (in line with energetic constraints). Using simple and complex climate models, we demonstrate that radiative forcing by greenhouse gases is currently suppressing global precipitation (P) at ~ -0.15 %/decade. Along with natural variability, this can explain why observed trends in global P over the period 1988-2008 are close to zero. Regional responses in the global water cycle are strongly constrained by changes in moisture fluxes. Model simulations show an increased moisture flux into the tropical wet region at 900 hPa and an enhanced outflow (of smaller magnitude) at around 600 hPa with warming. Moisture transport explains an increase in P in the wet tropical regions and small or negative changes in the dry regions of the subtropics in CMIP5 simulations of a warming climate. For AMIP5 simulations and satellite observations, the heaviest 5-day rainfall totals increase in intensity at ~15 %/K over the ocean with reductions at all percentiles over land. The climate change response in CMIP5 simulations shows consistent increases in P over ocean and land for the highest intensities, close to the Clausius-Clapeyron scaling of 7 %/K, while P declines for the lowest percentiles, indicating that interannual variability over land may not be a good proxy for climate change. The local changes in precipitation and its extremes are highly dependent upon small shifts in the large-scale atmospheric circulation and regional feedbacks.