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Local climate change risk assessments (LCCRAs) are best supported by a quantitative integration of physical hazards, exposures and vulnerabilities that includes the characterization of uncertainties. We propose to use Bayesian Networks (BNs) for this task and show how to integrate freely-available output of multiple global hydrological models (GHMs) into BNs, in order to probabilistically assess risks for water supply. Projected relative changes in hydrological variables computed by three GHMs driven by the output of four global climate models were processed using MATLAB, taking into account local information on water availability and use. A roadmap to set up BNs and apply probability distributions of risk levels under historic and future climate and water use was co-developed with experts from the Maghreb (Tunisia, Algeria, Morocco) who positively evaluated the BN application for LCCRAs. We conclude that the presented approach is suitable for application in the many LCCRAs necessary for successful adaptation to climate change world-wide.
New particle formation in the upper free troposphere is a major global source of cloud condensation nuclei (CCN)1,2,3,4. However, the precursor vapours that drive the process are not well understood. With experiments performed under upper tropospheric conditions in the CERN CLOUD chamber, we show that nitric acid, sulfuric acid and ammonia form particles synergistically, at rates that are orders of magnitude faster than those from any two of the three components. The importance of this mechanism depends on the availability of ammonia, which was previously thought to be efficiently scavenged by cloud droplets during convection. However, surprisingly high concentrations of ammonia and ammonium nitrate have recently been observed in the upper troposphere over the Asian monsoon region5,6. Once particles have formed, co-condensation of ammonia and abundant nitric acid alone is sufficient to drive rapid growth to CCN sizes with only trace sulfate. Moreover, our measurements show that these CCN are also highly efficient ice nucleating particles—comparable to desert dust. Our model simulations confirm that ammonia is efficiently convected aloft during the Asian monsoon, driving rapid, multi-acid HNO3–H2SO4–NH3 nucleation in the upper troposphere and producing ice nucleating particles that spread across the mid-latitude Northern Hemisphere.
The calcareous substrate of spring-fed fens makes them unique islands of biodiversity, hosting endangered, vulnerable, and protected vascular plants. Hence, spring-fed fens ecosystems require special conservation attention because many of them are destroyed (e.g. drained, forested) and it is extremely difficult or even impossible to restore the unique hydrogeological and geochemical conditions enabling their function. The long-term perspective of paleoecological studies allows indication of former wetland ecosystem states and provides understanding of their development over millennia. To examine the late Holocene dynamics of a calcareous spring-fed fen (Raganu Mire) ecosystem on the Baltic Sea coast (Latvia) in relation to environmental changes, substrate and human activity, we have undertaken high-resolution analyses of plant macrofossils, pollen, mollusc, stable carbon (δ13C) and oxygen (δ18O) isotopes combined with radiocarbon dating (AMS) in three coring locations. Our study revealed that peat deposits began accumulating ca. 7000 cal. yr BP and calcareous deposits (tufa) from 1450 cal. yr BP, coinciding with regional hydrological changes. Several fire events occurred between 4000 and 1600 cal. yr BP, which appeared to have had a limited effect on local vegetation. The most significant changes in the forest and peatland ecosystems were at 3200 cal. yr BP associated with a dry climate stage and high fire activity, and then between 1400 and 500 cal. yr BP potentially associated with temperature changes during the Medieval Climate Anomaly (MCA) and Little Ice Age. Hydrological disturbances in the peatland catchment from 1400 cal. yr BP were most likely strengthened by human activity (deforestation) in this region. The relationship between the development of this peatland and changes in its catchment area, such as land cover changes or fluctuations in groundwater levels, suggest that protection and restoration of spring-fed fen ecosystems should also include the surrounding catchment. The presence of calcareous sediments, as well as appropriate temperature and local hydrological conditions appear to be the most crucial factors controlling Cladium marisus populations in our site - currently at the eastern limit of its distribution in Europe.
A list of authors and their affiliations appears at the end of the paper New-particle formation is a major contributor to urban smog, but how it occurs in cities is often puzzling. If the growth rates of urban particles are similar to those found in cleaner environments (1–10 nanometres per hour), then existing understanding suggests that new urban particles should be rapidly scavenged by the high concentration of pre-existing particles. Here we show, through experiments performed under atmospheric conditions in the CLOUD chamber at CERN, that below about +5 degrees Celsius, nitric acid and ammonia vapours can condense onto freshly nucleated particles as small as a few nanometres in diameter. Moreover, when it is cold enough (below −15 degrees Celsius), nitric acid and ammonia can nucleate directly through an acid–base stabilization mechanism to form ammonium nitrate particles. Given that these vapours are often one thousand times more abundant than sulfuric acid, the resulting particle growth rates can be extremely high, reaching well above 100 nanometres per hour. However, these high growth rates require the gas-particle ammonium nitrate system to be out of equilibrium in order to sustain gas-phase supersaturations. In view of the strong temperature dependence that we measure for the gas-phase supersaturations, we expect such transient conditions to occur in inhomogeneous urban settings, especially in wintertime, driven by vertical mixing and by strong local sources such as traffic. Even though rapid growth from nitric acid and ammonia condensation may last for only a few minutes, it is nonetheless fast enough to shepherd freshly nucleated particles through the smallest size range where they are most vulnerable to scavenging loss, thus greatly increasing their survival probability. We also expect nitric acid and ammonia nucleation and rapid growth to be important in the relatively clean and cold upper free troposphere, where ammonia can be convected from the continental boundary layer and nitric acid is abundant from electrical storms.
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
This study examines the urban heat island (UHI) of Brussels, for both current (2000–2009) and projected future (2060–2069) climate conditions, by employing very high resolution (250 m) modelling experiments, using the urban boundary layer climate model UrbClim. Meteorological parameters that are related to the intensity of the UHI are identified and it is investigated how these parameters and the magnitude of the UHI evolve for two plausible trajectories for future climate conditions. UHI intensity is found to be strongly correlated to the inversion strength in the lowest 100 m of the atmosphere. The results for the future scenarios indicate that the magnitude of the UHI is expected to decrease slightly due to global warming. This can be attributed to the increased incoming longwave radiation, caused by higher air temperature and humidity values. The presence of the UHI also has a significant impact on the frequency of extreme temperature events in the city area, both in present and future climates, and exacerbates the impact of climate change on the urban population as the amount of heat wave days in the city increases twice as fast as in the rural surroundings.
Observed global and European spatiotemporal related fields of surface air temperature, mean-sea-level pressure and precipitation are analyzed statistically with respect to their response to external forcing factors such as anthropogenic greenhouse gases, anthropogenic sulfate aerosol, solar variations and explosive volcanism, and known internal climate mechanisms such as the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). As a first step, a principal component analysis (PCA) is applied to the observed spatiotemporal related fields to obtain spatial patterns with linear independent temporal structure. In a second step, the time series of each of the spatial patterns is subject to a stepwise regression analysis in order to separate it into signals of the external forcing factors and internal climate mechanisms as listed above as well as the residuals. Finally a back-transformation leads to the spatiotemporally related patterns of all these signals being intercompared. Two kinds of significance tests are applied to the anthropogenic signals. First, it is tested whether the anthropogenic signal is significant compared with the complete residual variance including natural variability. This test answers the question whether a significant anthropogenic climate change is visible in the observed data. As a second test the anthropogenic signal is tested with respect to the climate noise component only. This test answers the question whether the anthropogenic signal is significant among others in the observed data. Using both tests, regions can be specified where the anthropogenic influence is visible (second test) and regions where the anthropogenic influence has already significantly changed climate (first test).