917 resultados para Inter-cycle Variability
Resumo:
There is growing interest in the role of gastrointestinal (GI) pathology and clinical expression of autism. Recent studies have demonstrated differences in the faecal clostridial populations harboured by autistic and non-autistic children. The potential of Lactobacillus plantarum WCSF1 (a probiotic) to modulate the gut microbiota of autistic subjects was investigated during a double-blind, placebo-controlled, crossover-designed feeding study. The faecal microbiota, gut function and behaviour scores of subjects were examined throughout the 12-week study. Lactobacillus plantarum WCFS1 feeding significantly increased Lab158 counts (lactobacilli and enterococci group) and significantly reduced Erec482 counts (Clostridium cluster XIVa) compared to placebo. Probiotic feeding also resulted in significant differences in the stool consistency compared to placebo and behaviour scores (total score and scores for some subscales) compared to baseline. The major finding of this work was the importance of study protocol in relation to the specific considerations of this subject population, with an extremely high dropout rate seen (predominantly during the baseline period). Furthermore, the relatively high inter-individual variability observed suggests that subsequent studies should use defined subgroups of autistic spectrum disorders, such as regressive or late-onset autism. In summary, the current study has highlighted the potential benefit of L. plantarum WCFS1 probiotic feeding in autistic individuals.
Resumo:
A quarter of a century of daily rainfall data from the Global Telecommunications System are used to define the temporal and spatial variability of the start of the wet season over Africa and surrounding extreme south of Europe and parts of the Middle East. From 1978 to 2002, the start of the wet season arrived later in the year for the majority of the region, as time progressed. In some parts of the continent, there was an annual increase in the start date of up to 4 days per year. On average, the start of the wet season arrived 9–21 days later from 1978 to 2002, depending on the threshold used to define the start of the rains (varying from 10–30 mm over 2 days, with no dry period in the following 10 days). It is noted that the inter-annual variability of the start of the wet season is high with the range of start dates varying on average from 116 to 142 days dependent on the threshold used to determine the start date. These results may have important implications for agriculturists on all levels (from the individual farmer to those responsible for regional food supply), as knowledge of potential future climate changes starts to play an increasingly important role in the agricultural decision-making process, such as sowing and harvesting times.
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A new database of weather and circulation type catalogs is presented comprising 17 automated classification methods and five subjective classifications. It was compiled within COST Action 733 "Harmonisation and Applications of Weather Type Classifications for European regions" in order to evaluate different methods for weather and circulation type classification. This paper gives a technical description of the included methods using a new conceptual categorization for classification methods reflecting the strategy for the definition of types. Methods using predefined types include manual and threshold based classifications while methods producing types derived from the input data include those based on eigenvector techniques, leader algorithms and optimization algorithms. In order to allow direct comparisons between the methods, the circulation input data and the methods' configuration were harmonized for producing a subset of standard catalogs of the automated methods. The harmonization includes the data source, the climatic parameters used, the classification period as well as the spatial domain and the number of types. Frequency based characteristics of the resulting catalogs are presented, including variation of class sizes, persistence, seasonal and inter-annual variability as well as trends of the annual frequency time series. The methodological concept of the classifications is partly reflected by these properties of the resulting catalogs. It is shown that the types of subjective classifications compared to automated methods show higher persistence, inter-annual variation and long-term trends. Among the automated classifications optimization methods show a tendency for longer persistence and higher seasonal variation. However, it is also concluded that the distance metric used and the data preprocessing play at least an equally important role for the properties of the resulting classification compared to the algorithm used for type definition and assignment.
Resumo:
For the first time, vertical column measurements of (HNO3) above the Arctic Stratospheric Ozone Observatory (AStrO) at Eureka (80N, 86W), Canada, have been made during polar night using lunar spectra recorded with a Fourier Transform Infrared (FTIR) spectrometer, from October 2001 to March 2002. AStrO is part of the primary Arctic station of the Network for the Detection of Stratospheric Change (NDSC). These measurements were compared with FTIR measurements at two other NDSC Arctic sites: Thule, Greenland (76.5N, 68.8W) and Kiruna, Sweden (67.8N, 20.4E). The measurements were also compared with two atmospheric models: the Canadian Middle Atmosphere Model (CMAM) and SLIMCAT. This is the first time that CMAM HNO3 columns have been compared with observations in the Arctic. Eureka lunar measurements are in good agreement with solar ones made with the same instrument. Eureka and Thule HNO3 columns are consistent within measurement error. Differences among HNO3 columns measured at Kiruna and those measured at Eureka and Thule can be explained on the basis of the available sunlight hours and the polar vortex location. The comparison of CMAM HNO3 columns with Eureka and Kiruna data shows good agreement, considering CMAM small inter-annual variability. The warm 2001/02 winter with almost no Polar Stratospheric Clouds (PSCs) makes the comparison of the warm climate version of CMAM with these observations a good test for CMAM under no PSC conditions. SLIMCAT captures the magnitude of HNO3 columns at Eureka, and the day-to-day variability, but generally reports higher HNO3 columns than the CMAM climatological mean columns.
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The atmospheric response to the evolution of the global sea surface temperatures from 1979 to 1992 is studied using the Max-Planck-Institut 19 level atmospheric general circulation model, ECHAM3 at T 42 resolution. Five separate 14-year integrations are performed and results are presented for each individual realization and for the ensemble-averaged response. The results are compared to a 30-year control integration using a climate monthly mean state of the sea surface temperatures and to analysis data. It is found that the ECHAM3 model, by and large, does reproduce the observed response pattern to El Nin˜o and La Nin˜a. During the El Nin˜ o events, the subtropical jet streams in both hemispheres are intensified and displaced equatorward, and there is a tendency towards weak upper easterlies over the equator. The Southern Oscillation is a very stable feature of the integrations and is accurately reproduced in all experiments. The inter-annual variability at middle- and high-latitudes, on the other hand, is strongly dominated by chaotic dynamics, and the tropical SST forcing only modulates the atmospheric circulation. The potential predictability of the model is investigated for six different regions. Signal to noise ratio is large in most parts of the tropical belt, of medium strength in the western hemisphere and generally small over the European area. The ENSO signal is most pronounced during the boreal spring. A particularly strong signal in the precipitation field in the extratropics during spring can be found over the southern United States. Western Canada is normally warmer during the warm ENSO phase, while northern Europe is warmer than normal during the ENSO cold phase. The reason is advection of warm air due to a more intense Pacific low than normal during the warm ENSO phase and a more intense Icelandic low than normal during the cold ENSO phase, respectively.
Resumo:
A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multimodel mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISSPUCCINI)and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23Wm−2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of −0.08Wm−2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of −0.05Wm−2, but which is within the stated range of −0.15 to +0.05Wm−2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1Wm−2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/).
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Sainfoin (Onobrychis viciifolia) is a condensed tannin (CT)-containing legume and has anthelmintic potential against gastrointestinal nematodes of ruminants. This study investigated in vitro effects of acetone/water extracts and derived CT fractions from different types of sainfoin (i.e. accessions) against larvae of Cooperia oncophora and Ostertagia ostertagi by applying the larval feeding inhibition assay (LFIA). Seven sainfoin accessions were extracted and tested with L1 larvae at 10 and 40 μg extract/ml. In addition, CT in extracts from 4 accessions were fractionated according to polymer size and tested by LFIA at two concentrations (2 and 10 μg CT fraction/ml). All sainfoin extracts caused significant inhibition of L1-feeding of both C. oncophora and O. ostertagi with varying intensity compared to the control (phosphate buffered saline). For both nematode species the in vitro effect was positively correlated with CT content in the extracts, but not with any of the structural CT parameters. In contrast, the 16 CT fractions revealed significant correlations between in vitro effect and CT content, polymer size (mean degree of polymerisation, mDP) and monomeric composition (prodelphinidin percentage, % PD). These differences between crude extracts and purified fractions may stem from the fact that extracts contain complex CT mixtures, which may mask and thus suppress CT structural effects. This study provides the first indication that, apart from CT and % PD content, polymer size also contributes to anthelmintic activity of CTs. The results, therefore, suggest that the inter-accession variability in CT content and composition needs to be taken into account in future plant breeding programmes which seek to enhance the anthelmintic properties of sainfoin
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Dissolved organic carbon (DOC) in acid-sensitive upland waters is dominated by allochthonous inputs from organic-rich soils, yet inter-site variability in soil DOC release to changes in acidity has received scant attention in spite of the reported differences between locations in surface water DOC trends over the last few decades. In a previous paper, we demonstrated that pH-related retention of DOC in O horizon soils was influenced by acid-base status, particularly the exchangeable Al content. In the present paper, we investigate the effect of sulphate additions (0–437 μeq l−1) on DOC release in the mineral B horizon soils from the same locations. Dissolved organic carbon release decreased with declining pH in all soils, although the shape of the pH-DOC relationships differed between locations, reflecting the multiple factors controlling DOC mobility. The release of DOC decreased by 32–91% in the treatment with the largest acid input (437 μeq l−1), with the greatest decreases occurring in soils with very small % base saturation (BS, <3%) and/or large capacity for sulphate (SO42−) retention (up to 35% of added SO42−). The greatest DOC release occurred in the soil with the largest initial base status (12% BS). These results support our earlier conclusions that differences in acid-base status between soils alter the sensitivity of DOC release to similar sulphur deposition declines. However,superimposed on this is the capacity of mineral soils to sorb DOC and SO42−, and more work is needed to determine the fate of sorbed DOC under conditions of increasing pH and decreasing SO42−.
Resumo:
Analysis of single forcing runs from CMIP5 (the fifth Coupled Model Intercomparison Project) simulations shows that the mid-twentieth century temperature hiatus, and the coincident decrease in precipitation, is likely to have been influenced strongly by anthropogenic aerosol forcing. Models that include a representation of the indirect effect of aerosol better reproduce inter-decadal variability in historical global-mean near-surface temperatures, particularly the cooling in the 1950s and 1960s, compared to models with representation of the aerosol direct effect only. Models with the indirect effect also show a more pronounced decrease in precipitation during this period, which is in better agreement with observations, and greater inter-decadal variability in the inter-hemispheric temperature difference. This study demonstrates the importance of representing aerosols, and their indirect effects, in general circulation models, and suggests that inter-model diversity in aerosol burden and representation of aerosol–cloud interaction can produce substantial variation in simulations of climate variability on multi decadal timescales.
Resumo:
Temperature and precipitation are major forcing factors influencing grapevine phenology and yield, as well as wine quality. Bioclimatic indices describing the suitability of a particular region for wine production are a commonly used tool for viticultural zoning. For this research these indices were computed for Europe by using the E-OBS gridded daily temperature and precipitation data set for the period from 1950 to 2009. Results showed strong regional contrasts based on the different index patterns and reproduced the wide diversity of local conditions that largely explain the quality and diversity of grapevines being grown across Europe. Owing to the strong inter-annual variability in the indices, a trend analysis and a principal component analysis were applied together with an assessment of their mean patterns. Significant trends were identified in the Winkler and Huglin indices, particularly for southwestern Europe. Four statistically significant orthogonal modes of variability were isolated for the Huglin index (HI), jointly representing 82% of the total variance in Europe. The leading mode was largely dominant (48% of variance) and mainly reflected the observed historical long-term changes. The other 3 modes corresponded to regional dipoles within Europe. Despite the relevance of local and regional climatic characteristics to grapevines, it was demonstrated via canonical correlation analysis that the observed inter-annual variability of the HI was strongly controlled by the large-scale atmospheric circulation during the growing season (April to September).
Resumo:
BACKGROUND: Evidence suggests the wide variation in platelet response within the population is genetically controlled. Unraveling the complex relationship between sequence variation and platelet phenotype requires accurate and reproducible measurement of platelet response. OBJECTIVE: To develop a methodology suitable for measuring signaling pathway-specific platelet phenotype, to use this to measure platelet response in a large cohort, and to demonstrate the effect size of sequence variation in a relevant model gene. METHODS: Three established platelet assays were evaluated: mobilization of [Ca(2+)](i), aggregometry and flow cytometry, each in response to adenosine 5'-diphosphate (ADP) or the glycoprotein (GP) VI-specific crosslinked collagen-related peptide (CRP). Flow cytometric measurement of fibrinogen binding and P-selectin expression in response to a single, intermediate dose of each agonist gave the best combination of reproducibility and inter-individual variability and was used to measure the platelet response in 506 healthy volunteers. Pathway specificity was ensured by blocking the main subsidiary signaling pathways. RESULTS: Individuals were identified who were hypo- or hyper-responders for both pathways, or who had differential responses to the two agonists, or between outcomes. 89 individuals, retested three months later using the same methodology, showed high concordance between the two visits in all four assays (r(2) = 0.872, 0.868, 0.766 and 0.549); all subjects retaining their phenotype at recall. The effect of sequence variation at the GP6 locus accounted for approximately 35% of the variation in the CRP-XL response. CONCLUSION: Genotyping-phenotype association studies in a well-characterized, large cohort provides a powerful strategy to measure the effect of sequence variation in genes regulating the platelet response.
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Projected changes in the extra-tropical wintertime storm tracks are investigated using the multi-model ensembles from both the third and fifth phases of the World Climate Research Programme's Coupled Model Intercomparison Project (CMIP3 and CMIP5). The aim is to characterize the magnitude of the storm track responses relative to their present-day year-to-year variability. For the experiments considered, the ‘middle-of-the-road’ scenarios in each CMIP, there are regions of the Northern Hemisphere where the responses of up to 40% of the models exceed half of the inter-annual variability, and for the Southern Hemisphere there are regions where up to 60% of the model responses exceed half of the inter-annual variability.
Resumo:
We have incorporated a semi-mechanistic isoprene emission module into the JULES land-surface scheme, as a first step towards a modelling tool that can be applied for studies of vegetation – atmospheric chemistry interactions, including chemistry-climate feedbacks. Here, we evaluate the coupled model against local above-canopy isoprene emission flux measurements from six flux tower sites as well as satellite-derived estimates of isoprene emission over tropical South America and east and south Asia. The model simulates diurnal variability well: correlation coefficients are significant (at the 95 % level) for all flux tower sites. The model reproduces day-to-day variability with significant correlations (at the 95 % confidence level) at four of the six flux tower sites. At the UMBS site, a complete set of seasonal observations is available for two years (2000 and 2002). The model reproduces the seasonal pattern of emission during 2002, but does less well in the year 2000. The model overestimates observed emissions at all sites, which is partially because it does not include isoprene loss through the canopy. Comparison with the satellite-derived isoprene-emission estimates suggests that the model simulates the main spatial patterns, seasonal and inter-annual variability over tropical regions. The model yields a global annual isoprene emission of 535 ± 9 TgC yr−1 during the 1990s, 78 % of which from forested areas.
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Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.
Resumo:
Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.