On the variability of return periods of European winter precipitation extremes over the last three centuries

We investigate the changes of extreme European winter (December-February) precipitation back to 1700 and show for various European regions that return periods of extremely wet and dry winters are subject to significant changes both before and after the onset of anthropogenic influences. Generally, winter precipitation has become more extreme. We also examine the spatial pattern of the changes of the extremes covering the last 300 years where data quality is sufficient. Over central and Eastern Europe dry winters occurred more frequently during the 18th and the second part of the 19th century relative to 1951–2000. Dry winters were less frequent during both the 18th and 19th century over the British Isles and the Mediterranean. Wet winters have been less abundant during the last three centuries compared to 1951–2000 except during the early 18th century in central Europe. Although winter precipitation extremes are affected by climate change, no obvious connection of these changes was found to solar, volcanic or anthropogenic forcing. However, physically meaningful interpretation with atmospheric circulation changes was possible.

Climate variability of the mid- and high-latitudes of the Southern Hemisphere in ensemble simulations from 1500 to 2000 AD

To increase the sparse knowledge of long-term Southern Hemisphere (SH) climate variability, we assess an ensemble of 4 transient simulations over the last 500 yr performed with a state-of-the-art atmosphere ocean general circulation model. The model is forced with reconstructions of solar irradiance, greenhouse gas (GHG) and volcanic aerosol concentrations. A 1990 control simulation shows that the model is able to represent the Southern Annular Mode (SAM), and to some extent the South Pacific Dipole (SPD) and the Zonal Wave 3 (ZW3). During the past 500 yr we find that SPD and ZW3 variability remain stable, whereas SAM shows a significant shift towards its positive state during the 20th century. Regional temperatures over South America are strongly influenced by changing both GHG concentrations and volcanic eruptions, whereas precipitation shows no significant response to the varying external forcing. For temperature this stands in contrast to proxy records, suggesting that SH climate is dominated by internal variability rather than external forcing. The underlying dynamics of the temperature changes generally point to a combination of several modes, thus, hampering the possibilities of regional reconstructing the modes from proxy records. The linear imprint of the external forcing is as expected, i.e. a warming for increase in the combined solar and GHG forcing and a cooling after volcanic eruptions. Dynamically, only the increase in SAM with increased combined forcing is simulated.

1200 years of decadal-scale variability of Mediterranean vegetation and climate at Pantelleria Island, Italy

A new sedimentary sequence from Lago di Venere on Pantelleria Island, located in the Strait of Sicily between Tunisia and Sicily was recovered. The lake is located in the coastal infra-Mediterranean vegetation belt at 2 m a.s.l. Pollen, charcoal and sedimentological analyses are used to explore linkages among vegetation, fire and climate at a decadal scale over the past 1200 years. A dry period from ad 800 to 1000 that corresponds to the ‘Medieval Warm Period’ (WMP) is inferred from sedimentological analysis. The high content of carbonate recorded in this period suggests a dry phase, when the ratio of evaporation/precipitation was high. During this period the island was dominated by thermophilous and drought-tolerant taxa, such as Quercus ilex, Olea, Pistacia and Juniperus. A marked shift in the sediment properties is recorded at ad 1000, when carbonate content became very low suggesting wetter conditions until ad 1850–1900. Broadly, this period coincides with the ‘Little Ice Age’ (LIA), which was characterized by wetter and colder conditions in Europe. During this time rather mesic conifers (i.e. Pinus pinaster), shrubs and herbs (e.g. Erica arborea and Selaginella denticulata) expanded, whereas more drought-adapted species (e.g. Q. ilex) declined. Charcoal data suggest enhanced fire activity during the LIA probably as a consequence of anthropogenic burning and/or more flammable fuel (e.g. resinous Pinus biomass). The last century was characterized by a shift to high carbonate content, indicating a change towards drier conditions, and re-expansion of Q. ilex and Olea. The post-LIA warming is in agreement with historical documents and meteorological time series. Vegetation dynamics were co-determined by agricultural activities on the island. Anthropogenic indicators (e.g. Cerealia-type, Sporormiella) reveal the importance of crops and grazing on the island. Our pollen data suggest that extensive logging caused the local extinction of deciduous Quercus pubescens around ad1750.

The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink

The growth rate of atmospheric carbondioxide(CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO 2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.

Temporal variability of damage potential on roads as a conceptual contribution towards a short-term avalanche risk simulation

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.

Variability of lung function predicts loss of asthma control following withdrawal of inhaled corticosteroid treatment

BACKGROUND One aspect of a multidimensional approach to understanding asthma as a complex dynamic disease is to study how lung function varies with time. Variability measures of lung function have been shown to predict response to beta(2)-agonist treatment. An investigation was conducted to determine whether mean, coefficient of variation (CV) or autocorrelation, a measure of short-term memory, of peak expiratory flow (PEF) could predict loss of asthma control following withdrawal of regular inhaled corticosteroid (ICS) treatment, using data from a previous study. METHODS 87 adult patients with mild to moderate asthma who had been taking ICS at a constant dose for at least 6 months were monitored for 2-4 weeks. ICS was then withdrawn and monitoring continued until loss of control occurred as per predefined criteria. Twice-daily PEF was recorded during monitoring. Associations between loss of control and mean, CV and autocorrelation of morning PEF within 2 weeks pre- and post-ICS withdrawal were assessed using Cox regression analysis. Predictive utility was assessed using receiver operator characteristics. RESULTS 53 out of 87 patients had sufficient PEF data over the required analysis period. The mean (389 vs 370 l/min, p<0.0001) and CV (4.5% vs 5.6%, p=0.007) but not autocorrelation of PEF changed significantly from prewithdrawal to postwithdrawal in subjects who subsequently lost control, and were unaltered in those who did not. These changes were related to time to loss of control. CV was the most consistent predictor, with similar sensitivity and sensitivity to exhaled nitric oxide. CONCLUSION A simple, easy to obtain variability measure of daily lung function such as the CV may predict loss of asthma control within the first 2 weeks of ICS withdrawal.

A multi-center study: Intra-scan and inter-scan variability of diffusion spectrum imaging

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

Variability of growth in children starting antiretroviral treatment in southern Africa

Poor growth is an indication for antiretroviral therapy (ART) and a criterion for treatment failure. We examined variability in growth response to ART in 12 programs in Malawi, Zambia, Zimbabwe, Mozambique, and South Africa.