Extreme precipitation events in the Mediterranean area have been defined by different percentile-based indices of extreme precipitation for autumn and winter: the number of events exceeding the 95th ...percentile of daily precipitation, percentage, total amount, and mean daily intensity of precipitation from these events. Results from statistical downscaling applying canonical correlation analysis as well as from dynamical downscaling using the regional climate model REMO are mapped for the 1961-1990 baseline period as well as for the magnitude of change for the future time slice 2021-2050 in relation to the former period. Direct output of the coupled global circulation model ECHAM5 is used as an additional source of information. A qualitative comparison of the two different downscaling techniques indicates that under the present climate both the dynamical and the statistical techniques have skill to reproduce extreme precipitation in the Mediterranean area. A good representation of the frequency of extreme precipitation events arises from the statistical downscaling approach, whereas the intensity of such events is adequately modelled by the dynamical downscaling. Concerning the change of extreme precipitation in the Mediterranean area until the mid-21st century, it is projected that the frequency of extreme precipitation events will decrease in most parts of the Mediterranean area in autumn and winter. The change of the mean intensity of such events shows a rather heterogeneous pattern with intensity increases in winter most likely at topographical elevations exposed to the West, where the uplift of humid air profits by the increase of atmospheric moisture under climate change conditions. For the precipitation total from events exceeding the 95th percentile of daily precipitation, widespread decreases are indicated in autumn, whereas in winter increases occur over the western part of the Iberian Peninsula and southern France, and reductions over southern Turkey, the eastern Mediterranean area, parts of Italy and some North African regions.
Climate change projections are subject to uncertainty arising from climate model deficiencies, unknown initial conditions and scenario assumptions. In the IPCC reports and many other publications ...climate changes and uncertainty ranges are usually displayed in terms of multi-model ensemble means and confidence intervals, respectively. In this study, we present a more quantitative assessment and statistical testing of climate change signals in the light of uncertainty. The approach is based on a two-way analysis of variance, referring to 24 climate models from the CMIP3 multi-model ensemble, and extents over the 21st century. The method also distinguishes between different climate variables, time scales and emission scenarios and is combined with a simple bias correction algorithm.
The Mediterranean region has been chosen as a case study because it represents an assumed hot spot of future climate change, where temperature is projected to rise substantially and precipitation may decrease dramatically by the end of the 21st century. It is found that future temperature variations are mainly determined by radiative forcing, accounting for up to 60% of total variability, especially in the western Mediterranean Basin. In contrast, future precipitation variability is almost completely attributable to model uncertainty and model internal variability, both being important in more or less equal shares. This general finding is slightly depending on the prescribed emission scenario and strictly sensitive to the considered time scale. In contrast to precipitation, the temperature signal can be enhanced noticeably when bias-correcting the models' climatology during the 20th century: the greenhouse signal then accounts for up to 75% of total temperature variability in the regional mean.
•We present a quantitative assessment of climate change signals.•The Mediterranean hot spot region has been chosen as a case study.•Future temperature variations are mainly determined by radiative forcing.•Precipitation changes are attributable to model uncertainty and internal variability.•Bias correction enhances the temperature signal up to 75% of explained variance.
Besides dynamical downscaling by regional climate models, statistical downscaling (SD) is a major tool to derive climate change projections on regional or even local scales. For the Mediterranean ...area, an increasing number of downscaling studies based on different statistical techniques have been published in the last two decades with a broad range of sometimes differing results relating to different variables and regional domains. This paper gives a short review of these Mediterranean downscaling studies mainly considering the following two aspects: (1) what kind of progress has been realized in this field since the early 1990s? The review addresses the inclusion of extremes in downscaling assessments, the development of probabilistic approaches, the extension of predictor sets, the use of ensembles for both dynamical model simulations and statistical model assessments, the consideration of non-stationarities in the predictor–predictand relationships, and some advances related to synoptic downscaling. (2) What are the main regional climate change signals in the Mediterranean area, considering agreed and controversial points also with respect to dynamical models? Best accordance among future projections can be found in seasonal temperatures with lower rates of warming in winter and spring, and, in most cases, higher ones in summer and autumn. Different results are obtained for the intra-annual range of extreme temperatures, but high-temperature conditions are generally expected to increase. Regarding seasonal precipitation, predominant reductions are indicated for spring, summer, and autumn. For winter, however, projections are distinctly different (GCMs: rainfall decrease; RCMs: increase only in the northernmost parts of the Mediterranean region; SD: widespread increases in the northern and western parts in several studies). Different results are obtained for rainfall extremes, but the entire precipitation distribution tends to shift towards higher
and
lower values. Apart from some sub-regional deviations, there is a predominant increase in future dry period durations. For near-surface winds, only a few studies are available, and they project some decline mainly for the winter season.
Meteorological factors seem to influence stroke incidence, however, the complex association between weather and stroke remains unclear. Possible explanations from the literature do not categorize ...into subdivisions of ischemic strokes, only have small patient numbers, or refer to a selection of isolated weather elements without investigating weather changes and more.
In this exploratory trial, almost 18,000 stroke cases from a single stroke center in Southern Germany were analyzed from 2006 to 2015 and classified into the main subgroups of strokes and subdivisions of ischemic stroke etiologies applying the Trial of Org 10172 in Acute Stroke Treatment classification. For each stroke event, the air mass classification was determined from a subset of 7 air mass categories. Relative excess morbidities were derived for the 7 different air mass categories, taking into account the day of the event and up to 2 and 5 days preceding the stroke event.
Statistically significant findings (α ≤0.1) reveal that dry tropical air masses were associated with a lower/higher risk for hemorrhagic (HEM)/macroangiopathic strokes (MAS), respectively. Dry polar air masses were associated with a higher risk for intracerebral bleedings and lower risk for ischemic stroke subtypes. Moist air masses were associated with a reduced incidence of MAS. A strong temperature increase 5 days prior to the event was associated with a lower risk of HEM strokes. Temperature increases were associated with lower risks for MAS and cardio-embolic strokes. Significant temperature decreases were associated with a higher risk of MAS.
Temperature effects were dependent on both air masses and temperature changes within 5 days prior to the event and were associated with statistically relevant changes in stroke incidence. Decisive factors such as etiology, age, sex, and risk factors were also taken into account.
Higher incidences of asthma during thunderstorms can pose a serious health risk. In this study, we estimate the thunderstorm asthma risk using statistical methods, with special focus on Bavaria, ...Southern Germany. In this approach, a dataset of asthma-related emergency cases for the study region is combined with meteorological variables and aeroallergen data to identify statistical relationships between the occurrence of asthma (predictand) and different environmental parameters (set of predictors). On the one hand, the results provide evidence for a weak but significant relationship between atmospheric stability indices and asthma emergencies in the region, but also show that currently thunderstorm asthma is not a major concern in Bavaria due to overall low incidences. As thunderstorm asthma can have severe consequences for allergic patients, the presented approach can be important for the development of emergency strategies in regions affected by thunderstorm asthma and under present and future climate change conditions.
In the Iberian Peninsula the raise of temperatures has been notable from mid-1970s to mid-2000s, especially in spring and summer. This study analyses spatial and temporal relationships between ...extreme temperatures and atmospheric circulation types (CTs) defined over the Iberian Peninsula (IP) in these seasons. Station series (29) of maximum and minimum temperature are considered, starting from 1905 until 2006. The CTs (9 for spring and 8 for summer) are derived by a cluster method applied to daily mean SLP grids covering the period 1850–2003. Changes in the seasonal frequency of extreme temperatures and of CTs are analysed. Subsequently, the CTs are examined for their effectiveness in leading to moderately extreme temperatures (at each location) using an index that measures the contribution to extreme days with respect to the contribution to non-extreme days. Correlation between regional extreme series and CTs frequency is also tested.
In spring, the decrease in cold nights, which is notable in the 1970s onwards, can be partially attributable to a downtrend in the frequency of Northerly flow. High frequency of Anticyclone in North Iberia in the 1980s and 1990s has contributed to an increase in warm days in West and North stations. To the SE quadrant of the IP, a great part of warm days is related to south-westerly flow, (both) presenting a higher frequency in the 1950s and the 1960s.
In summer warm nights increased remarkably to the SE and SW, and may be in part related to uptrends in Iberian thermal low pattern (1950–2003) and North Atlantic Anticyclone (1850–2003) respectively. Warm days have increased remarkably to the NE especially in the 1990s and 2000s, but this is not found to be related to changes in CTs' frequency.
Furthermore, the existence of within type changes (variations in Tmax, Tmin and extreme indices within the CTs) points to the identification of other physical factors operating on inter-annual to multidecadal time scales. Thus, the consideration of Sea Surface Temperature (SST) of the East Atlantic Ocean and Iberian soil moisture conditions (by means of a drought index) helps to explain the evolution of extreme temperatures.
► Atmospheric circulation types and temperature extremes in the Iberian Peninsula in spring and summer are examined. ► South-westerly flow (more frequent in 1950s–1960s) and anticyclone extended to North Iberia (also in 1990s) are connected to increases in warm days. ► A decrease in Northerly flow in spring explains less frequency of cold nights. ► Changes in temperature extremes within the circulation types from 1905 to 2003 indicate that other factors such as SST or drought conditions have had an impact on temperature.
The behaviour of precipitation and maximum temperature extremes in the Mediterranean area under climate change conditions is analysed in the present study. In this context, the ability of synoptic ...downscaling techniques in combination with extreme value statistics for dealing with extremes is investigated. Analyses are based upon a set of long-term station time series in the whole Mediterranean area. At first, a station-specific ensemble approach for model validation was developed which includes (1) the downscaling of daily precipitation and maximum temperature values from the large-scale atmospheric circulation via analogue method and (2) the fitting of extremes by generalized Pareto distribution (GPD). Model uncertainties are quantified as confidence intervals derived from the ensemble distributions of GPD-related return values and described by a new metric called “ratio of overlapping”. Model performance for extreme precipitation is highest in winter, whereas the best models for maximum temperature extremes are set up in autumn. Valid models are applied to a 30-year period at the end of the twenty-first century (2070–2099) by means of ECHAM5/MPI-OM general circulation model data for IPCC SRES B1 scenario. The most distinctive future changes are observed in autumn in terms of a strong reduction of precipitation extremes in Northwest Iberia and the Northern Central Mediterranean area as well as a simultaneous distinct increase of maximum temperature extremes in Southwestern Iberia and the Central and Southeastern Mediterranean regions. These signals are checked for changes in the underlying dynamical processes using extreme-related circulation classifications. The most important finding connected to future changes of precipitation extremes in the Northwestern Mediterranean area is a reduction of southerly displaced deep North Atlantic cyclones in 2070–2099 as associated with a strengthened North Atlantic Oscillation. Thus, the here estimated future changes of extreme precipitation are in line with the discourse about the influence of North Atlantic circulation variability on the changing climate in Europe.
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Summary
Arsenic, a highly cytotoxic and cancerogenic metalloid, is brought into the biosphere through geochemical sources and anthropogenic activities. A global biogeochemical arsenic ...biotransformation cycle exists in which inorganic arsenic species are transformed into organoarsenicals, which are subsequently mineralized again into inorganic arsenic compounds. Microorganisms contribute to this biotransformation process greatly and one of the organoarsenicals synthesized and degraded in this cycle is arsenobetaine. Its nitrogen‐containing homologue glycine betaine is probably the most frequently used compatible solute on Earth. Arsenobetaine is found in marine and terrestrial habitats and even in deep‐sea hydrothermal vent ecosystems. Despite its ubiquitous occurrence, the biological function of arsenobetaine has not been comprehensively addressed. Using Bacillus subtilis as a well‐understood platform for the study of microbial osmostress adjustment systems, we ascribe here to arsenobetaine both a protective function against high osmolarity and a cytoprotective role against extremes in low and high growth temperatures. We define a biosynthetic route for arsenobetaine from the precursor arsenocholine that relies on enzymes and genetic regulatory circuits for glycine betaine formation from choline, identify the uptake systems for arsenobetaine and arsenocholine, and describe crystal structures of ligand‐binding proteins from the OpuA and OpuB ABC transporters complexed with either arsenobetaine or arsenocholine.
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