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Temperature-related excess mortality in German cities at 2 °C and higher degrees of global warming
(2020)
Background: Investigating future changes in temperature-related mortality as a function of global mean temperature (GMT) rise allows for the evaluation of policy-relevant climate change targets. So far, only few studies have taken this approach, and, in particular, no such assessments exist for Germany, the most populated country of Europe.
Methods: We assess temperature-related mortality in 12 major German cities based on daily time-series of all-cause mortality and daily mean temperatures in the period 1993-2015, using distributed-lag non-linear models in a two-stage design. Resulting risk functions are applied to estimate excess mortality in terms of GMT rise relative to pre-industrial levels, assuming no change in demographics or population vulnerability.
Results: In the observational period, cold contributes stronger to temperature-related mortality than heat, with overall attributable fractions of 5.49% (95%CI: 3.82-7.19) and 0.81% (95%CI: 0.72-0.89), respectively. Future projections indicate that this pattern could be reversed under progressing global warming, with heat-related mortality starting to exceed cold-related mortality at 3 degrees C or higher GMT rise. Across cities, projected net increases in total temperature-related mortality were 0.45% (95%CI: -0.02-1.06) at 3 degrees C, 1.53% (95%CI: 0.96-2.06) at 4 degrees C, and 2.88% (95%CI: 1.60-4.10) at 5 degrees C, compared to today's warming level of 1 degrees C. By contrast, no significant difference was found between projected total temperature-related mortality at 2 degrees C versus 1 degrees C of GMT rise.
Conclusions: Our results can inform current adaptation policies aimed at buffering the health risks from increased heat exposure under climate change. They also allow for the evaluation of global mitigation efforts in terms of local health benefits in some of Germany's most populated cities.
Climate change, manifested by an increase in mean, minimum, and maximum temperatures and by more intense rainstorms, is becoming more evident in many regions. An important consequence of these changes may be an increase in landslides in high mountains. More research, however, is necessary to detect changes in landslide magnitude and frequency related to contemporary climate, particularly in alpine regions hosting glaciers, permafrost, and snow. These regions not only are sensitive to changes in both temperature and precipitation, but are also areas in which landslides are ubiquitous even under a stable climate. We analyze a series of catastrophic slope failures that occurred in the mountains of Europe, the Americas, and the Caucasus since the end of the 1990s. We distinguish between rock and ice avalanches, debris flows from de-glaciated areas, and landslides that involve dynamic interactions with glacial and river processes. Analysis of these events indicates several important controls on slope stability in high mountains, including: the non-linear response of firn and ice to warming; three-dimensional warming of subsurface bedrock and its relation to site geology; de-glaciation accompanied by exposure of new sediment; and combined short-term effects of precipitation and temperature. Based on several case studies, we propose that the following mechanisms can significantly alter landslide magnitude and frequency, and thus hazard, under warming conditions: (1) positive feedbacks acting on mass movement processes that after an initial climatic stimulus may evolve independently of climate change; (2) threshold behavior and tipping points in geomorphic systems; (3) storage of sediment and ice involving important lag-time effects.
BACKGROUND Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics.
RESULTS Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance.
CONCLUSION Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term. (c) 2014 Society of Chemical Industry
In dieser Arbeit werden Konzepte für die Diagnostik der großskaligen Zirkulation in der Troposphäre und Stratosphäre entwickelt. Der Fokus liegt dabei auf dem Energiehaushalt, auf der Wellenausbreitung und auf der Interaktion der atmosphärischen Wellen mit dem Grundstrom. Die Konzepte werden hergeleitet, wobei eine neue Form des lokalen Eliassen-Palm-Flusses unter Einbeziehung der Feuchte eingeführt wird. Angewendet wird die Diagnostik dann auf den Reanalysedatensatz ERA-Interim und einen durch beobachtete Meerestemperatur- und Eisdaten angetriebenen Lauf des ECHAM6 Atmosphärenmodells. Die diagnostischen Werkzeuge zur Analyse der großskaligen Zirkulation sind einerseits nützlich, um das Verständnis der Dynamik des Klimasystems weiter zu fördern. Andererseits kann das gewonnene Verständnis des Zusammenhangs von Energiequellen und -senken sowie deren Verknüpfung mit synoptischen und planetaren Wellensystemen und dem resultierenden Antrieb des Grundstroms auch verwendet werden, um Klimamodelle auf die korrekte Wiedergabe dieser Beobachtungen zu prüfen. Hier zeigt sich, dass die Abweichungen im untersuchten ECHAM6-Modelllauf bezüglich des Energiehaushalts klein sind, jedoch teils starke Abweichungen bezüglich der Ausbreitung von atmosphärischen Wellen existieren. Planetare Wellen zeigen allgemein zu große Intensitäten in den Eliassen-Palm-Flüssen, während innerhalb der Strahlströme der oberen Troposphäre der Antrieb des Grundstroms durch synoptische Wellen verfälscht ist, da deren vertikale Ausbreitung gegenüber den Beobachtungen verschoben ist. Untersucht wird auch der Einfluss von arktischen Meereisänderungen ausgehend vom Bedeckungsminimum im August/September bis in den Winter. Es werden starke positive Temperaturanomalien festgestellt, welche an der Oberfläche am größten sind. Diese führen vor allem im Herbst zur Intensivierung von synoptischen Systemen in den arktischen Breiten, da die Stabilität der troposphärischen Schichtung verringert ist. Im darauffolgenden Winter stellen sich barotrope bis in die Stratosphäre reichende Änderungen der großskaligen Zirkulation ein, welche auf Meereisänderungen zurückzuführen sind. Der meridionale Druckgradient sinkt und führt so zu einem Muster ähnlich einer negativen Phase der arktischen Oszillation in der Troposphäre und einem geschwächten Polarwirbel in der Stratosphäre. Diese Zusammenhänge werden ebenfalls in einem ECHAM6-Modelllauf untersucht, wobei vor allem der Erwärmungstrend in der Arktis zu gering ist. Die großskaligen Veränderungen im Winter können zum Teil auch im Modelllauf festgestellt werden, jedoch zeigen sich insbesondere in der Stratosphäre Abweichungen für die Periode mit der geringsten Eisausdehnung. Die vertikale Ausbreitung planetarer Wellen von der Troposphäre in die Stratosphäre ist in ECHAM6 mit sehr großen Abweichungen wiedergegeben. Somit stellt die Wellenausbreitung insgesamt den größten in dieser Arbeit festgestellten Mangel in ECHAM6 dar.
Organic matter characteristics in yedoma and thermokarst deposits on Baldwin Peninsula, west Alaska
(2018)
As Arctic warming continues and permafrost thaws, more soil and sedimentary organic matter (OM) will be decomposed in northern high latitudes. Still, uncertainties remain in the quality of the OM and the size of the organic carbon (OC) pools stored in different deposit types of permafrost landscapes. This study presents OM data from deep permafrost and lake deposits on the Baldwin Peninsula which is located in the southern portion of the continuous permafrost zone in west Alaska. Sediment samples from yedoma and drained thermokarst lake basin (DTLB) deposits as well as thermokarst lake sediments were analyzed for cryostratigraphical and biogeochemical parameters and their lipid biomarker composition to identify the below-ground OC pool size and OM quality of ice-rich permafrost on the Baldwin Peninsula. We provide the first detailed characterization of yedoma deposits on Baldwin Peninsula. We show that three-quarters of soil OC in the frozen deposits of the study region (total of 68 Mt) is stored in DTLB deposits (52 Mt) and one-quarter in the frozen yedoma deposits (16 Mt). The lake sediments contain a relatively small OC pool (4 Mt), but have the highest volumetric OC content (93 kgm(-3)) compared to the DTLB (35 kgm(-3)) and yedoma deposits (8 kgm(-3)), largely due to differences in the ground ice content. The biomarker analysis indicates that the OM in both yedoma and DTLB deposits is mainly of terrestrial origin. Nevertheless, the relatively high carbon preference index of plant leaf waxes in combination with a lack of a degradation trend with depth in the yedoma deposits indi-cates that OM stored in yedoma is less degraded than that stored in DTLB deposits. This suggests that OM in yedoma has a higher potential for decomposition upon thaw, despite the relatively small size of this pool. These findings show that the use of lipid biomarker analysis is valuable in the assessment of the potential future greenhouse gas emissions from thawing permafrost, especially because this area, close to the discontinuous permafrost boundary, is projected to thaw substantially within the 21st century.
The ongoing climate change is altering the living conditions for many organisms on this planet at an unprecedented pace. Hence, it is crucial for the survival of species to adapt to these changing conditions. In this dissertation Silene vulgaris is used as a model organism to understand the adaption strategies of widely distributed plant species to the current climate change. Especially plant species that possess a wide geographic range are expected to have a high phenotypic plasticity or to show genetic differentiation in response to the different climate conditions they grow in. However, they are often underrepresented in research.
In the greenhouse experiment presented in this thesis, I examined the phenotypic responses and plasticity in S. vulgaris to estimate its’ adaptation potential. Seeds from 25 wild European populations were collected along a latitudinal gradient and grown in a greenhouse under three different precipitation (65 mm, 75 mm, 90 mm) and two different temperature regimes (18°C, 21°C) that resembled a possible climate change scenario for central Europe. Afterwards different biomass and fecundity-related plant traits were measured.
The treatments significantly influenced the plants but did not reveal a latitudinal difference in response to climate treatments for most plant traits. The number of flowers per individual however, showed a stronger plasticity in northern European populations (e.g., Swedish populations) where numbers decreased more drastically with increased temperature and decreased precipitation.
To gain an even deeper understanding of the adaptation of S. vulgaris to climate change it is also important to reveal the underlying phylogeny of the sampled populations. Therefore, I analysed their population genetic structure through whole genome sequencing via ddRAD.
The sequencing revealed three major genetic clusters in the S. vulgaris populations sampled in Europe: one cluster comprised Southern European populations, one cluster Western European populations and another cluster contained central European populations. A following analysis of experimental trait responses among the clusters to the climate-change scenario showed that the genetic clusters significantly differed in biomass-related traits and in the days to flowering. However, half of the traits showed parallel response patterns to the experimental climate-change scenario.
In addition to the potential geographic and genetic adaptation differences to climate change this dissertation also deals with the response differences between the sexes in S. vulgaris. As a gynodioecious species populations of S. vulgaris consist of female and hermaphrodite
individuals and the sexes can differ in their morphological traits which is known as sexual dimorphism. As climate change is becoming an important factor influencing plant morphology it remains unclear if and how different sexes may respond in sexually dimorphic species. To examine this question the sex of each individual plant was determined during the greenhouse experiment and the measured plant traits were analysed accordingly. In general, hermaphrodites had a higher number of flowers but a lower number of leaves than females. With regards to the climate change treatment, I found that hermaphrodites showed a milder negative response to higher temperatures in the number of flowers produced and in specific leaf area (SLA) compared to females.
Synthesis – The significant treatment response in Silene vulgaris, independent of population origin in most traits suggests a high degree of universal phenotypic plasticity. Also, the three European intraspecific genetic lineages detected showed comparable parallel response patterns in half of the traits suggesting considerable phenotypic plasticity. Hence, plasticity might represent a possible adaptation strategy of this widely distributed species during ongoing and future climatic changes. The results on sexual dimorphism show that females and hermaphrodites are differing mainly in their number of flowers and females are affected more strongly by the experimental climate-change scenario. These results provide a solid knowledge basis on the sexual dimorphism in S. vulgaris under climate change, but further research is needed to determine the long-term impact on the breeding system for the species.
In summary this dissertation provides a comprehensive insight into the adaptation mechanisms and consequences of a widely distributed and gynodioecious plant species and leverages our understanding of the impact of anthropogenic climate change on plants.
The adaptation of plants to future climatic conditions is crucial for their survival. Not surprisingly, phenotypic responses to climate change have already been observed in many plant populations. These responses may be due to evolutionary adaptive changes or phenotypic plasticity. Especially plant species with a wide geographic range are either expected to show genetic differentiation in response to differing climate conditions or to have a high phenotypic plasticity. We investigated phenotypic responses and plasticity as an estimate of the adaptive potential in the widespread species Silene vulgaris. In a greenhouse experiment, 25 European populations covering a geographic range from the Canary Islands to Sweden were exposed to three experimental precipitation and two temperature regimes mimicking a possible climate-change scenario for central Europe. We hypothesized that southern populations have a better performance under high temperature and drought conditions, as they are already adapted to a comparable environment. We found that our treatments significantly influenced the plants, but did not reveal a latitudinal difference in response to climate treatments for most plant traits. Only flower number showed a stronger plasticity in northern European populations (e.g. Swedish populations) where numbers decreased more drastically with increased temperature and decreased precipitation treatment. Synthesis. The significant treatment response in Silene vulgaris, independent of population origin - except for the number of flowers produced - suggests a high degree of universal phenotypic plasticity in this widely distributed species. This reflects the likely adaptation strategy of the species and forms the basis for a successful survival strategy during upcoming climatic changes. However, as flower number, a strongly fitness-related trait, decreased more strongly in northern populations under a climate-change scenario, there might be limits to adaptation even in this widespread, plastic species.
Cellulose delta O-18 is an index of leaf-to-air vapor pressure difference (VPD) in tropical plants
(2011)
Cellulose in plants contains oxygen that derives in most cases from precipitation. Because the stable oxygen isotope composition, delta O-18, of precipitation is associated with environmental conditions, cellulose delta O-18 should be as well. However, plant physiological models using delta O-18 suggest that cellulose delta O-18 is influenced by a complex mix of both climatic and physiological drivers. This influence complicates the interpretation of cellulose delta O-18 values in a paleo-context. Here, we combined empirical data analyses with mechanistic model simulations to i) quantify the impacts that the primary climatic drivers humidity (e(a)) and air temperature (T-air) have on cellulose delta O-18 values in different tropical ecosystems and ii) determine which environmental signal is dominating cellulose delta O-18 values. Our results revealed that e(a) and T-air equally influence cellulose delta O-18 values and that distinguishing which of these factors dominates the delta O-18 values of cellulose cannot be accomplished in the absence of additional environmental information. However, the individual impacts of e(a) and T-air on the delta O-18 values of cellulose can be integrated into a single index of plant-experienced atmospheric vapor demand: the leaf-to-air vapor pressure difference (VPD). We found a robust relationship between VPD and cellulose delta O-18 values in both empirical and modeled data in all ecosystems that we investigated. Our analysis revealed therefore that delta O-18 values in plant cellulose can be used as a proxy for VPD in tropical ecosystems. As VPD is an essential variable that determines the biogeochemical dynamics of ecosystems, our study has applications in ecological-, climate-, or forensic-sciences.
We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7–14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73–142$/tCO2 in 2020, rising to 92–181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.
Rainfall-intense summer monsoon seasons on the Indian subcontinent that are exceeding long-term averages cause widespread floods and landslides.
Here we show that the latest generation of coupled climate models robustly project an intensification of very rainfall-intense seasons (June-September).
Under the shared socioeconomic pathway SSP5-8.5, very wet monsoon seasons as observed in only 5 years in the period 1965-2015 are projected to occur 8 times more often in 2050-2100 in the multi-model average.
Under SSP2-4.5, these seasons become only a factor of 6 times more frequent, showing that even modest efforts to mitigate climate change can have a strong impact on the frequency of very strong rainfall seasons.
Besides, we find that the increasing risk of extreme seasonal rainfall is accompanied by a shift from days with light rainfall to days with moderate or heavy rainfall. Additionally, the number of wet days is projected to increase.
Meteorological extreme events have great potential for damaging railway infrastructure and posing risks to the safety of train passengers. In the future, climate change will presumably have serious implications on meteorological hazards in the Alpine region. Hence, attaining insights on future frequencies of meteorological extremes with relevance for the railway operation in Austria is required in the context of a comprehensive and sustainable natural hazard management plan of the railway operator. In this study, possible impacts of climate change on the frequencies of so-called critical meteorological conditions (CMCs) between the periods 1961-1990 and 2011-2040 are analyzed. Thresholds for such CMCs have been defined by the railway operator and used in its weather monitoring and early warning system. First, the seasonal climate change signals for air temperature and precipitation in Austria are described on the basis of an ensemble of high-resolution Regional Climate Model (RCM) simulations for Europe. Subsequently, the RCM-ensemble was used to investigate changes in the frequency of CMCs. Finally, the sensitivity of results is analyzed with varying threshold values for the CMCs. Results give robust indications for an all-season air temperature rise, but show no clear tendency in average precipitation. The frequency analyses reveal an increase in intense rainfall events and heat waves, whereas heavy snowfall and cold days are likely to decrease. Furthermore, results indicate that frequencies of CMCs are rather sensitive to changes of thresholds. It thus emphasizes the importance to carefully define, validate, andif neededto adapt the thresholds that are used in the weather monitoring and warning system of the railway operator. For this, continuous and standardized documentation of damaging events and near-misses is a pre-requisite.
Meteorological extreme events have great potential for damaging railway infrastructure and posing risks to the safety of train passengers. In the future, climate change will presumably have serious implications on meteorological hazards in the Alpine region. Hence, attaining insights on future frequencies of meteorological extremes with relevance for the railway operation in Austria is required in the context of a comprehensive and sustainable natural hazard management plan of the railway operator. In this study, possible impacts of climate change on the frequencies of so-called critical meteorological conditions (CMCs) between the periods 1961-1990 and 2011-2040 are analyzed. Thresholds for such CMCs have been defined by the railway operator and used in its weather monitoring and early warning system. First, the seasonal climate change signals for air temperature and precipitation in Austria are described on the basis of an ensemble of high-resolution Regional Climate Model (RCM) simulations for Europe. Subsequently, the RCM-ensemble was used to investigate changes in the frequency of CMCs. Finally, the sensitivity of results is analyzed with varying threshold values for the CMCs. Results give robust indications for an all-season air temperature rise, but show no clear tendency in average precipitation. The frequency analyses reveal an increase in intense rainfall events and heat waves, whereas heavy snowfall and cold days are likely to decrease. Furthermore, results indicate that frequencies of CMCs are rather sensitive to changes of thresholds. It thus emphasizes the importance to carefully define, validate, andif neededto adapt the thresholds that are used in the weather monitoring and warning system of the railway operator. For this, continuous and standardized documentation of damaging events and near-misses is a pre-requisite.
River floods are among the most devastating natural hazards worldwide. As their generation is highly dependent on climatic conditions, their magnitude and frequency are projected to be affected by future climate change. Therefore, it is crucial to study the ways in which a changing climate will, and already has, influenced flood generation, and thereby flood hazard. Additionally, it is important to understand how other human influences - specifically altered land cover - affect flood hazard at the catchment scale.
The ways in which flood generation is influenced by climatic and land cover conditions differ substantially in different regions. The spatial variability of these effects needs to be taken into account by using consistent datasets across large scales as well as applying methods that can reflect this heterogeneity. Therefore, in the first study of this cumulative thesis a complex network approach is used to find 10 clusters of similar flood behavior among 4390 catchments in the conterminous United States. By using a consistent set of 31 hydro-climatological and land cover variables, and training a separate Random Forest model for each of the clusters, the regional controls on flood magnitude trends between 1960-2010 are detected. It is shown that changes in rainfall are the most important drivers of these trends, while they are regionally controlled by land cover conditions.
While climate change is most commonly associated with flood magnitude trends, it has been shown to also influence flood timing. This can lead to trends in the size of the area across which floods occur simultaneously, the flood synchrony scale. The second study is an analysis of data from 3872 European streamflow gauges and shows that flood synchrony scales have increased in Western Europe and decreased in Eastern Europe. These changes are attributed to changes in flood generation, especially a decreasing relevance of snowmelt. Additionally, the analysis shows that both the absolute values and the trends of flood magnitudes and flood synchrony scales are positively correlated. If these trends persist in the future and are not accounted for, the combined increases of flood magnitudes and flood synchrony scales can exceed the capacities of disaster relief organizations and insurers.
Hazard cascades are an additional way through which climate change can influence different aspects of flood hazard. The 2019/2020 wildfires in Australia, which were preceded by an unprecedented drought and extinguished by extreme rainfall that led to local flooding, present an opportunity to study the effects of multiple preceding hazards on flood hazard. All these hazards are individually affected by climate change, additionally complicating the interactions within the cascade. By estimating and analyzing the burn severity, rainfall magnitude, soil erosion and stream turbidity in differently affected tributaries of the Manning River catchment, the third study shows that even low magnitude floods can pose a substantial hazard within a cascade.
This thesis shows that humanity is affecting flood hazard in multiple ways with spatially and temporarily varying consequences, many of which were previously neglected (e.g. flood synchrony scale, hazard cascades). To allow for informed decision making in risk management and climate change adaptation, it will be crucial to study these aspects across the globe and to project their trajectories into the future. The presented methods can depict the complex interactions of different flood drivers and their spatial variability, providing a basis for the assessment of future flood hazard changes. The role of land cover should be considered more in future flood risk modelling and management studies, while holistic, transferable frameworks for hazard cascade assessment will need to be designed.
Deforestation is currently a widespread phenomenon and a growing environmental concern in the era of rapid climate change.
In temperate regions, it is challenging to quantify the impacts of deforestation on the catchment dynamics and downstream aquatic ecosystems such as reservoirs and disentangle these from direct climate change impacts, let alone project future changes to inform management.
Here, we tackled this issue by investigating a unique catchment-reservoir system with two reservoirs in distinct trophic states (meso- and eutrophic), both of which drain into the largest drinking water reservoir in Germany.
Due to the prolonged droughts in 2015-2018, the catchment of the mesotrophic reservoir lost an unprecedented area of forest (exponential increase since 2015 and ca. 17.1% loss in 2020 alone).
We coupled catchment nutrient exports (HYPE) and reservoir ecosystem dynamics (GOTM-WET) models using a process-based modeling approach. The coupled model was validated with datasets spanning periods of rapid deforestation, which makes our future projections highly robust.
Results show that in a short-term time scale (by 2035), increasing nutrient flux from the catchment due to vast deforestation (80% loss) can turn the mesotrophic reservoir into a eutrophic state as its counterpart.
Our results emphasize the more prominent impacts of deforestation than the direct impact of climate warming in impairment of water quality and ecological services to downstream aquatic ecosystems. Therefore, we propose to evaluate the impact of climate change on temperate reservoirs by incorporating a time scale-dependent context, highlighting the indirect impact of deforestation in the short-term scale. In the long-term scale (e.g. to 2100), a guiding hypothesis for future research may be that indirect effects (e.g., as mediated by catchment dynamics) are as important as the direct effects of climate warming on aquatic ecosystems.
Model-Based attribution of high-resolution streamflow trends in two alpine basins of Western Austria
(2017)
Several trend studies have shown that hydrological conditions are changing considerably in the Alpine region. However, the reasons for these changes are only partially understood and trend analyses alone are not able to shed much light. Hydrological modelling is one possible way to identify the trend drivers, i.e., to attribute the detected streamflow trends, given that the model captures all important processes causing the trends. We modelled the hydrological conditions for two alpine catchments in western Austria (a large, mostly lower-altitude catchment with wide valley plains and a nested high-altitude, glaciated headwater catchment) with the distributed, physically-oriented WaSiM-ETH model, which includes a dynamical glacier module. The model was calibrated in a transient mode, i.e., not only on several standard goodness measures and glacier extents, but also in such a way that the simulated streamflow trends fit with the observed ones during the investigation period 1980 to 2007. With this approach, it was possible to separate streamflow components, identify the trends of flow components, and study their relation to trends in atmospheric variables. In addition to trends in annual averages, highly resolved trends for each Julian day were derived, since they proved powerful in an earlier, data-based attribution study. We were able to show that annual and highly resolved trends can be modelled sufficiently well. The results provide a holistic, year-round picture of the drivers of alpine streamflow changes: Higher-altitude catchments are strongly affected by earlier firn melt and snowmelt in spring and increased ice melt throughout the ablation season. Changes in lower-altitude areas are mostly caused by earlier and lower snowmelt volumes. All highly resolved trends in streamflow and its components show an explicit similarity to the local temperature trends. Finally, results indicate that evapotranspiration has been increasing in the lower altitudes during the study period.
Extreme weather events like heatwaves and floods severely affect societies with impacts ranging from economic damages to losses in human lifes. Global warming caused by anthropogenic greenhouse gas emissions is expected to increase their frequency and intensity, particularly in the warm season. Next to these thermodynamic changes, climate change might also impact the large scale atmospheric circulation.Such dynamic changes might additionally act on the occurence of extreme weather events, but involved mechanisms are often highly non-linear. Therefore, large uncertainty exists on the exact nature of these changes and the related risks to society. Particularly in the densely populated mid-latitudes weather patterns are governed by the large scale circulation like the jet-streams and storm tracks. Extreme weather in this region is often related to persistent weather systems associated with a strongly meandering jet-stream. Such meanders are called Rossby waves. Under specific conditions they can become slow moving, stretched around the entire hemisphere and generate simultaneaous heat- and rainfall extremes in far-away regions.
This thesis aims at enhancing the understanding of synoptic-scale, circumglobal Rossby waves and the associated risks of dynamical changes to society. More specific, the analyses investigate their relation to extreme weather, regions at risk, under which conditions they are generated, and the influence of anthropogenic climate change on those conditions now, in the past and in the future.
I find that circumglobal Rossby waves promoted simultaneous occuring weather extremes across the northern hemisphere in several recent summers. Further, I present evidence that they are often linked to quasiresonant-amplification of planetary waves. These events include the 2003 European heatwave and the Moscow heatwave of 2010. This non-linear mechanism acts on the upper level flow through trapping and amplification of stationary synoptic scale waves. I show that this resonance mechanism acts in both hemispheres and is related to extreme weather. A main finding is that circumglobal Rossby waves primarily occur as two specific teleconnection patterns associated with a wave 5 and wave 7 pattern in the northern hemisphere, likely due to the favourable longitudinal distance of prominent mountain ridges here. Furthermore, I identify those regions which are particularly at risk: The central United States, western Europe and the Ukraine/Russian region. Moreover, I present evidence that the wave 7 pattern has and extreme weather in these regions. My results suggest that the increase in frequency can be linked to favourable changes in large scale temperature gradients, which I show to be largely underestimated by model simulations. Using surface temperature fingerprint as proxy for investigating historic and future model ensembles, evidence is presented that anthropogenic warming has likely increased the probability for the occurence of circumglobal Rossby waves. Further it is shown that this might lead to a doubling of such events until the end of the century under a high-emission scenario.
Overall, this thesis establishes several atmosphere-dynamical pathways by which changes in large scale temperature gradients might link to persistent boreal summer weather. It highlights the societal risks associated with the increasing occurence of a newly discovered Rossby wave teleconnection pattern, which has the potential to cause simultaneaous heat-extremes in the mid-latitudinal bread-basket regions. In addition, it provides further evidence that the traditional picture by which quasi-stationary Rossby waves occur only in the low wavenumber regime, should be reconsidered.
Projected scenarios of climate change involve general predictions about the likely changes to the magnitude and frequency of landslides, particularly as a consequence of altered precipitation and temperature regimes. Whether such landslide response to contemporary or past climate change may be captured in differing scaling statistics of landslide size distributions and the erosion rates derived thereof remains debated. We test this notion with simple Monte Carlo and bootstrap simulations of statistical models commonly used to characterize empirical landslide size distributions. Our results show that significant changes to total volumes contained in such inventories may be masked by statistically indistinguishable scaling parameters, critically depending on, among others, the size of the largest of landslides recorded. Conversely, comparable model parameter values may obscure significant, i.e. more than twofold, changes to landslide occurrence, and thus inferred rates of hillslope denudation and sediment delivery to drainage networks. A time series of some of Earth's largest mass movements reveals clustering near and partly before the last glacial-interglacial transition and a distinct step-over from white noise to temporal clustering around this period. However, elucidating whether this is a distinct signal of first-order climate-change impact on slope stability or simply coincides with a transition from short-term statistical noise to long-term steady-state conditions remains an important research challenge.
Many semi-arid regions are characterised by water scarcity and vulnerability of natural resources, pronounced climatic variability and social stress. Integrated studies including climatotogy, hydrology, and socio-econornic studies are required both for analysing the dynamic natural conditions and to assess possible strategies to make semi-arid regions Less vulnerable to the present and changing climate. The model introduced here dynamically describes the retationships between climate forcing, water availability, agriculture and selected societal processes. The model has been tailored to simulate the rather complex situation in the semi-and north-eastern Brazil in a quantitative manner including the sensitivity to external forcing, such as climate change. The selected results presented show the general functioning of the integrated model, with a primary focus on climate change impacts. It becomes evident that due to Large differences in regional climate scenarios, it is still impossible to give quantitative values for the most probable development, e.g., to assign probabilities to the simulated results. However, it becomes clear that water is a very crucial factor, and that an efficient and ecologically sound water management is a key question for the further development of that semi-arid region. The simulation results show that, independent of the differences in climate change scenarios, rain-fed farming is more vulnerable to drought impacts compared to irrigated farming. However, the capacity of irrigation and other water infrastructure systems to enhance resilience in respect to climatic fluctuations is significantly constrained given a significant negative precipitation trend. (c) 2005 Elsevier B.V. All rights reserved.
Global heat adaptation among urban populations and its evolution under different climate futures
(2022)
Heat and increasing ambient temperatures under climate change represent a serious threat to human health in cities. Heat exposure has been studied extensively at a global scale. Studies comparing a defined temperature threshold with the future daytime temperature during a certain period of time, had concluded an increase in threat to human health. Such findings however do not explicitly account for possible changes in future human heat adaptation and might even overestimate heat exposure. Thus, heat adaptation and its development is still unclear. Human heat adaptation refers to the local temperature to which populations are adjusted to. It can be inferred from the lowest point of the U- or V-shaped heat-mortality relationship (HMR), the Minimum Mortality Temperature (MMT). While epidemiological studies inform on the MMT at the city scale for case studies, a general model applicable at the global scale to infer on temporal change in MMTs had not yet been realised. The conventional approach depends on data availability, their robustness, and on the access to daily mortality records at the city scale. Thorough analysis however must account for future changes in the MMT as heat adaptation happens partially passively. Human heat adaptation consists of two aspects: (1) the intensity of the heat hazard that is still tolerated by human populations, meaning the heat burden they can bear and (2) the wealth-induced technological, social and behavioural measures that can be employed to avoid heat exposure. The objective of this thesis is to investigate and quantify human heat adaptation among urban populations at a global scale under the current climate and to project future adaptation under climate change until the end of the century. To date, this has not yet been accomplished. The evaluation of global heat adaptation among urban populations and its evolution under climate change comprises three levels of analysis. First, using the example of Germany, the MMT is calculated at the city level by applying the conventional method. Second, this thesis compiles a data pool of 400 urban MMTs to develop and train a new model capable of estimating MMTs on the basis of physical and socio-economic city characteristics using multivariate non-linear multivariate regression. The MMT is successfully described as a function of the current climate, the topography and the socio-economic standard, independently of daily mortality data for cities around the world. The city-specific MMT estimates represents a measure of human heat adaptation among the urban population. In a final third analysis, the model to derive human heat adaptation was adjusted to be driven by projected climate and socio-economic variables for the future. This allowed for estimation of the MMT and its change for 3 820 cities worldwide for different combinations of climate trajectories and socio-economic pathways until 2100. The knowledge on the evolution of heat adaptation in the future is a novelty as mostly heat exposure and its future development had been researched. In this work, changes in heat adaptation and exposure were analysed jointly. A wide range of possible health-related outcomes up to 2100 was the result, of which two scenarios with the highest socio-economic developments but opposing strong warming levels were highlighted for comparison. Strong economic growth based upon fossil fuel exploitation is associated with a high gain in heat adaptation, but may not be able to compensate for the associated negative health effects due to increased heat exposure in 30% to 40% of the cities investigated caused by severe climate change. A slightly less strong, but sustainable growth brings moderate gains in heat adaptation but a lower heat exposure and exposure reductions in 80% to 84% of the cities in terms of frequency (number of days exceeding the MMT) and intensity (magnitude of the MMT exceedance) due to a milder global warming. Choosing a 2 ° C compatible development by 2100 would therefore lower the risk of heat-related mortality at the end of the century. In summary, this thesis makes diverse and multidisciplinary contributions to a deeper understanding of human adaptation to heat under the current and the future climate. It is one of the first studies to carry out a systematic and statistical analysis of urban characteristics which are useful as MMT drivers to establish a generalised model of human heat adaptation, applicable at the global level. A broad range of possible heat-related health options for various future scenarios was shown for the first time. This work is of relevance for the assessment of heat-health impacts in regions where mortality data are not accessible or missing. The results are useful for health care planning at the meso- and macro-level and to urban- and climate change adaptation planning. Lastly, beyond having met the posed objective, this thesis advances research towards a global future impact assessment of heat on human health by providing an alternative method of MMT estimation, that is spatially and temporally flexible in its application.
Weather extremes pose a persistent threat to society on multiple layers. Besides an average of ~37,000 deaths per year, climate-related disasters cause destroyed properties and impaired economic activities, eroding people's livelihoods and prosperity. While global temperature rises – caused by anthropogenic greenhouse gas emissions – the direct impacts of climatic extreme events increase and will further intensify without proper adaptation measures. Additionally, weather extremes do not only have local direct effects. Resulting economic repercussions can propagate either upstream or downstream along trade chains causing indirect effects. One approach to analyze these indirect effects within the complex global supply network is the agent-based model Acclimate. Using and extending this loss-propagation model, I focus in this thesis on three aspects of the relation between weather extremes and economic repercussions.
First, extreme weather events cause direct impacts on local economic performance. I compute daily local direct output loss time series of heat stress, river floods, tropical cyclones, and their consecutive occurrence using (near-future) climate projection ensembles. These regional impacts are estimated based on physical drivers and local productivity distribution. Direct effects of the aforementioned disaster categories are widely heterogeneous concerning regional and temporal distribution. As well, their intensity changes differently under future warming. Focusing on the hurricane-impacted capital, I find that long-term growth losses increase with higher heterogeneity of a shock ensemble.
Second, repercussions are sectorally and regionally distributed via economic ripples within the trading network, causing higher-order effects. I use Acclimate to identify three phases of those economic ripples. Furthermore, I compute indirect impacts and analyze overall regional and global production and consumption changes. Regarding heat stress, global consumer losses double while direct output losses increase by a factor 1.5 between 2000 – 2039. In my research I identify the effect of economic ripple resonance and introduce it to climate impact research. This effect occurs if economic ripples of consecutive disasters overlap, which increases economic responses such as an enhancement of consumption losses. These loss enhancements can even be more amplified with increasing direct output losses, e.g. caused by climate crises.
Transport disruptions can cause economic repercussions as well. For this, I extend the model Acclimate with a geographical transportation route and expand the decision horizon of economic agents. Using this, I show that policy-induced sudden trade restrictions (e.g. a no-deal Brexit) can significantly reduce the longer-term economic prosperity of affected regions. Analyses of transportation disruptions in typhoon seasons indicate that severely affected regions must reduce production as demand falls during a storm. Substituting suppliers may compensate for fluctuations at the beginning of the storm, which fails for prolonged disruptions.
Third, possible coping mechanisms and adaptation strategies arise from direct and indirect economic responses to weather extremes. Analyzing annual trade changes due to typhoon-induced transport disruptions depict that overall exports rise. This trade resilience increases with higher network node diversification. Further, my research shows that a basic insurance scheme may diminish hurricane-induced long-term growth losses due to faster reconstruction in disasters aftermaths. I find that insurance coverage could be an economically reasonable coping scheme towards higher losses caused by the climate crisis. Indirect effects within the global economic network from weather extremes indicate further adaptation possibilities. For one, diversifying linkages reduce the hazard of sharp price increases. Next to this, close economic interconnections with regions that do not share the same extreme weather season can be economically beneficial in the medium run. Furthermore, economic ripple resonance effects should be considered while computing costs. Overall, an increase in local adaptation measures reduces economic ripples within the trade network and possible losses elsewhere. In conclusion, adaptation measures are necessary and potential present, but it seems rather not possible to avoid all direct or indirect losses.
As I show in this thesis, dynamical modeling gives valuable insights into how direct and indirect economic impacts arise from different categories of weather extremes. Further, it highlights the importance of resolving individual extremes and reflecting amplifying effects caused by incomplete recovery or consecutive disasters.
The most complex but potentially most severe impacts of climate change are caused by extreme weather events. In a globally connected economy, damages can cause remote perturbations and cascading consequences-a ripple effect along supply chains. Here we show an economic ripple resonance that amplifies losses when consecutive or overlapping weather extremes and their repercussions interact. This amounts to an average amplification of 21% for climate-induced heat stress, river floods, and tropical cyclones. Modeling the temporal evolution of 1.8 million trade relations between >7000 regional economic sectors, we find that the regional responses to future extremes are strongly heterogeneous also in their resonance behavior. The induced effect on welfare varies between gains due to increased demand in some regions and losses due to demand or supply shortages in others. Within the current global supply network, the ripple resonance effect of extreme weather is strongest in high-income economies-an important effect to consider when evaluating past and future economic climate impacts.
Global Circulation Models of climate predict not only a change of annual precipitation amounts but also a shift in the daily distribution. To improve the understanding of the importance of daily rain pattern for annual plant communities, which represent a large portion of semi-natural vegetation in the Middle East, I used a detailed, spatially explicit model. The model explicitly considers water storage in the soil and has been parameterized and validated with data collected in field experiments in Israel and data from the literature. I manipulated daily rainfall variability by increasing the mean daily rain intensity on rainy days (MDI, rain volume/day) and decreasing intervals between rainy days while keeping the mean annual amount constant. In factorial combination, I also increased mean annual precipitation (MAP). I considered five climatic regions characterized by 100, 300, 450, 600, and 800 mm MAP. Increasing MDI decreased establishment when MAP was >250 mm but increased establishment at more arid sites. The negative effect of increasing MDI was compensated by increasing mortality with increasing MDI in dry and typical Mediterranean regions (c. 360–720 mm MAP). These effects were strongly tied to water availability in upper and lower soil layers and modified by competition among seedlings and adults. Increasing MAP generally increased water availability, establishment, and density. The order of magnitudes of MDI and MAP effects overlapped partially so that their combined effect is important for projections of climate change effects on annual vegetation. The effect size of MAP and MDI followed a sigmoid curve along the MAP gradient indicating that the semi-arid region (≈300 mm MAP) is the most sensitive to precipitation change with regard to annual communitie
This contribution describes a generator of stochastic time series of daily precipitation for the interior of Israel from c. 90 to 900 mm mean annual precipitation (MAP) as a tool for studies of daily rain variability. The probability of rainfall on a given day of the year is described by a regular Gaussian peak curve function. The amount of rain is drawn randomly from an exponential distribution whose mean is the daily mean rain amount (averaged across years for each day of the year) described by a flattened Gaussian peak curve. Parameters for the curves have been calculated from monthly aggregated, long-term rain records from seven meteorological stations. Parameters for arbitrary points on the MAP gradient are calculated from a regression equation with MAP as the only independent variable. The simple structure of the generator allows it to produce time series with daily rain patterns that are projected under climate change scenarios and simultaneously control MAP. Increasing within-year variability of daily precipitation amounts also increases among-year variability of MAP as predicted by global circulation models. Thus, the time series incorporate important characteristics for climate change research and represent a flexible tool for simulations of daily vegetation or surface hydrology dynamics.
Small livestock is an important resource for rural human populations in dry climates. How strongly will climate change affect the capacity of the rangeland? We used hierarchical modelling to scale quantitatively the growth of shrubs and annual plants, the main food of sheep and goats, to the landscape extent in the eastern Mediterranean region. Without grazing, productivity increased in a sigmoid way with mean annual precipitation. Grazing reduced productivity more strongly the drier the landscape. At a point just under the stocking capacity of the vegetation, productivity declined precipitously with more intense grazing due to a lack of seed production of annuals. We repeated simulations with precipitation patterns projected by two contrasting IPCC scenarios. Compared to results based on historic patterns, productivity and stocking capacity did not differ in most cases. Thus, grazing intensity remains the stronger impact on landscape productivity in this dry region even in the future.
Reproductive development of grapevine and berry composition are both strongly influenced by temperature. To date, the molecular mechanisms involved in grapevine berries response to high temperatures are poorly understood. Unlike recent data that addressed the effects on berry development of elevated temperatures applied at the whole plant level, the present work particularly focuses on the fruit responses triggered by direct exposure to heat treatment (HT). In the context of climate change, this work focusing on temperature effect at the microclimate level is of particular interest as it can help to better understand the consequences of leaf removal (a common viticultural practice) on berry development. HT (+8 degrees C) was locally applied to clusters from Cabernet Sauvignon fruiting cuttings at three different developmental stages (middle green, veraison and middle ripening). Samples were collected 1, 7, and 14 days after treatment and used for metabolic and transcriptomic analyses. The results showed dramatic and specific biochemical and transcriptomic changes in heat exposed berries, depending on the developmental stage and the stress duration. When applied at the herbaceous stage, HT delayed the onset of veraison. Heating also strongly altered the berry concentration of amino acids and organic acids (e.g., phenylalanine, raminobutyric acid and malate) and decreased the anthocyanin content at maturity. These physiological alterations could be partly explained by the deep remodeling of transcriptome in heated berries. More than 7000 genes were deregulated in at least one of the nine experimental conditions. The most affected processes belong to the categories "stress responses," protein metabolism" and "secondary metabolism," highlighting the intrinsic capacity of grape berries to perceive HT and to build adaptive responses. Additionally, important changes in processes related to "transport," "hormone" and "cell wall" might contribute to the postponing of veraison. Finally, opposite effects depending on heating duration were observed for genes encoding enzymes of the general phenylpropanoid pathway, suggesting that the HI induced decrease in anthocyanin content may result from a combination of transcript abundance and product degradation.
The weather in Eurasia, Australia, and North and South America is largely controlled by the strength and position of extratropical storm tracks. Future climate change will likely affect these storm tracks and the associated transport of energy, momentum, and water vapour. Many recent studies have analyzed how storm tracks will change under climate change, and how these changes are related to atmospheric dynamics. However, there are still discrepancies between different studies on how storm tracks will change under future climate scenarios. Here, we show that under global warming the CMIP5 ensemble of coupled climate models projects only little relative changes in vertically averaged mid-latitude mean storm track activity during the northern winter, but agree in projecting a substantial decrease during summer. Seasonal changes in the Southern Hemisphere show the opposite behaviour, with an intensification in winter and no change during summer. These distinct seasonal changes in northern summer and southern winter storm tracks lead to an amplified seasonal cycle in a future climate. Similar changes are seen in the mid-latitude mean Eady growth rate maximum, a measure that combines changes in vertical shear and static stability based on baroclinic instability theory. Regression analysis between changes in the storm tracks and changes in the maximum Eady growth rate reveal that most models agree in a positive association between the two quantities over mid-latitude regions.
The global climate crisis is significantly contributing to changing ecosystems, loss of biodiversity and is putting numerous species on the verge of extinction. In principle, many species are able to adapt to changing conditions or shift their habitats to more suitable regions. However, change is progressing faster than some species can adjust, or potential adaptation is blocked and disrupted by direct and indirect human action. Unsustainable anthropogenic land use in particular is one of the driving factors, besides global heating, for these ecologically critical developments. Precisely because land use is anthropogenic, it is also a factor that could be quickly and immediately corrected by human action.
In this thesis, I therefore assess the impact of three climate change scenarios of increasing intensity in combination with differently scheduled mowing regimes on the long-term development and dispersal success of insects in Northwest German grasslands. The large marsh grasshopper (LMG, Stethophyma grossum, Linné 1758) is used as a species of reference for the analyses. It inhabits wet meadows and marshes and has a limited, yet fairly good ability to disperse. Mowing and climate conditions affect the development and mortality of the LMG differently depending on its life stage.
The specifically developed simulation model HiLEG (High-resolution Large Environmental
Gradient) serves as a tool for investigating and projecting viability and dispersal success under different climate conditions and land use scenarios. It is a spatially explicit, stage- and cohort-based model that can be individually configured to represent the life cycle and characteristics of terrestrial insect species, as well as high-resolution environmental data and the occurrence of external disturbances. HiLEG is a freely available and adjustable software that can be used to support conservation planning in cultivated grasslands.
In the three case studies of this thesis, I explore various aspects related to the structure of simulation models per se, their importance in conservation planning in general, and insights regarding the LMG in particular. It became apparent that the detailed resolution of model processes and components is crucial to project the long-term effect of spatially and temporally confined events. Taking into account conservation measures at the regional level has further proven relevant, especially in light of the climate crisis. I found that the LMG is benefiting from global warming in principle, but continues to be constrained by harmful mowing regimes. Land use measures could, however, be adapted in such a way that they allow the expansion and establishment of the LMG without overly affecting agricultural yields.
Overall, simulation models like HiLEG can make an important contribution and add value
to conservation planning and policy-making. Properly used, simulation results shed light
on aspects that might be overlooked by subjective judgment and the experience of individual stakeholders. Even though it is in the nature of models that they are subject to limitations and only represent fragments of reality, this should not keep stakeholders from using them, as long as these limitations are clearly communicated. Similar to HiLEG, models could further be designed in such a way that not only the parameterization can be adjusted as required, but also the implementation itself can be improved and changed as desired. This openness and flexibility should become more widespread in the development of simulation models.
In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60-year periods (2020-2079) on a fine temporal (daily) and high spatial (250 x 250 m(2)) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.
Global mean sea level has been steadily rising over the last century, is projected to increase by the end of this century, and will continue to rise beyond the year 2100 unless the current global mean temperature trend is reversed. Inertia in the climate and global carbon system, however, causes the global mean temperature to decline slowly even after greenhouse gas emissions have ceased, raising the question of how much sea-level commitment is expected for different levels of global mean temperature increase above preindustrial levels. Although sea-level rise over the last century has been dominated by ocean warming and loss of glaciers, the sensitivity suggested from records of past sea levels indicates important contributions should also be expected from the Greenland and Antarctic Ice Sheets. Uncertainties in the paleo-reconstructions, however, necessitate additional strategies to better constrain the sea-level commitment. Here we combine paleo-evidence with simulations from physical models to estimate the future sea-level commitment on a multimillennial time scale and compute associated regional sea-level patterns. Oceanic thermal expansion and the Antarctic Ice Sheet contribute quasi-linearly, with 0.4 m degrees C-1 and 1.2 m degrees C-1 of warming, respectively. The saturation of the contribution from glaciers is overcompensated by the nonlinear response of the Greenland Ice Sheet. As a consequence we are committed to a sea-level rise of approximately 2.3 m degrees C-1 within the next 2,000 y. Considering the lifetime of anthropogenic greenhouse gases, this imposes the need for fundamental adaptation strategies on multicentennial time scales.
Natural gas hydrates are ice-like crystalline compounds containing water cavities that trap natural gas molecules like methane (CH4), which is a potent greenhouse gas with high energy density. The Mallik site at the Mackenzie Delta in the Canadian Arctic contains a large volume of technically recoverable CH4 hydrate beneath the base of the permafrost. Understanding how the sub-permafrost hydrate is distributed can aid in searching for the ideal locations for deploying CH4 production wells to develop the hydrate as a cleaner alternative to crude oil or coal. Globally, atmospheric warming driving permafrost thaw results in sub-permafrost hydrate dissociation, releasing CH4 into the atmosphere to intensify global warming. It is therefore crucial to evaluate the potential risk of hydrate dissociation due to permafrost degradation. To quantitatively predict hydrate distribution and volume in complex sub-permafrost environments, a numerical framework was developed to simulate sub-permafrost hydrate formation by coupling the equilibrium CH4-hydrate formation approach with a fluid flow and transport simulator (TRANSPORTSE). In addition, integrating the equations of state describing ice melting and forming with TRANSPORTSE enabled this framework to simulate the permafrost evolution during the sub-permafrost hydrate formation. A modified sub-permafrost hydrate formation mechanism for the Mallik site is presented in this study. According to this mechanism, the CH4-rich fluids have been vertically transported since the Late Pleistocene from deep overpressurized zones via geologic fault networks to form the observed hydrate deposits in the Kugmallit–Mackenzie Bay Sequences. The established numerical framework was verified by a benchmark of hydrate formation via dissolved methane. Model calibration was performed based on laboratory data measured during a multi-stage hydrate formation experiment undertaken in the LArge scale Reservoir Simulator (LARS). As the temporal and spatial evolution of simulated and observed hydrate saturation matched well, the LARS model was therefore validated. This laboratory-scale model was then upscaled to a field-scale 2D model generated from a seismic transect across the Mallik site. The simulation confirmed the feasibility of the introduced sub-permafrost hydrate formation mechanism by demonstrating consistency with field observations. The 2D model was extended to the first 3D model of the Mallik site by using well-logs and seismic profiles, to investigate the geologic controls on the spatial hydrate distribution. An assessment of this simulation revealed the hydraulic contribution of each geological element, including relevant fault networks and sedimentary sequences. Based on the simulation results, the observed heterogeneous distribution of sub-permafrost hydrate resulted from the combined factors of the source-gas generation rate, subsurface temperature, and the permeability of geologic elements. Analysis of the results revealed that the Mallik permafrost was heated by 0.8–1.3 °C, induced by the global temperature increase of 0.44 °C and accelerated by Arctic amplification from the early 1970s to the mid-2000s. This study presents a numerical framework that can be applied to study the formation of the permafrost-hydrate system from laboratory to field scales, across timescales ranging from hours to millions of years. Overall, these simulations deepen the knowledge about the dominant factors controlling the spatial hydrate distribution in sub-permafrost environments with heterogeneous geologic elements. The framework can support improving the design of hydrate formation experiments and provide valuable contributions to future industrial hydrate exploration and exploitation activities.
The Mackenzie Delta (MD) is a permafrost-bearing region along the coasts of the Canadian Arctic which exhibits high sub-permafrost gas hydrate (GH) reserves. The GH occurring at the Mallik site in the MD is dominated by thermogenic methane (CH4), which migrated from deep conventional hydrocarbon reservoirs, very likely through the present fault systems. Therefore, it is assumed that fluid flow transports dissolved CH4 upward and out of the deeper overpressurized reservoirs via the existing polygonal fault system and then forms the GH accumulations in the Kugmallit-Mackenzie Bay Sequences. We investigate the feasibility of this mechanism with a thermo-hydraulic-chemical numerical model, representing a cross section of the Mallik site. We present the first simulations that consider permafrost formation and thawing, as well as the formation of GH accumulations sourced from the upward migrating CH4-rich formation fluid. The simulation results show that temperature distribution, as well as the thickness and base of the ice-bearing permafrost are consistent with corresponding field observations. The primary driver for the spatial GH distribution is the permeability of the host sediments. Thus, the hypothesis on GH formation by dissolved CH4 originating from deeper geological reservoirs is successfully validated. Furthermore, our results demonstrate that the permafrost has been substantially heated to 0.8-1.3 degrees C, triggered by the global temperature increase of about 0.44 degrees C and further enhanced by the Arctic Amplification effect at the Mallik site from the early 1970s to the mid-2000s.
The amount of terrestrial particulate organic matter (t-POM) entering lakes is predicted to increase as a result of climate change. This may especially alter the structure and functioning of ecosystems in small, shallow lakes which can rapidly shift from a clear-water, macrophyte-dominated into a turbid, phytoplankton-dominated state. We used the integrative ecosystem model PCLake to predict how rising t-POM inputs affect the resilience of the clear-water state. PCLake links a pelagic and benthic food chain with abiotic components by a number of direct and indirect effects. We focused on three pathways (zoobenthos, zooplankton, light availability) by which elevated t-POM inputs (with and without additional nutrients) may modify the critical nutrient loading thresholds at which a clear-water lake becomes turbid and vice versa. Our model results show that (1) increased zoobenthos biomass due to the enhanced food availability results in more benthivorous fish which reduce light availability due to bioturbation, (2) zooplankton biomass does not change, but suspended t-POM reduces the consumption of autochthonous particulate organic matter which increases the turbidity, and (3) the suspended t-POM reduces the light availability for submerged macrophytes. Therefore, light availability is the key process that is indirectly or directly changed by t-POM input. This strikingly resembles the deteriorating effect of terrestrial dissolved organic matter on the light climate of lakes. In all scenarios, the resilience of the clear-water state is reduced thus making the turbid state more likely at a given nutrient loading. Therefore, our study suggests that rising t-POM input can add to the effects of climate warming making reductions in nutrient loadings even more urgent.
Mountain ecosystems are commonly regarded as being highly sensitive to global change. Due to the system complexity and multifaceted interacting drivers, however, understanding current responses and predicting future changes in these ecosystems is extremely difficult. We aim to discuss potential effects of global change on mountain ecosystems and give examples of the underlying response mechanisms as they are understood at present. Based on the development of scientific global change research in mountains and its recent structures, we identify future research needs, highlighting the major lack and the importance of integrated studies that implement multi-factor, multi-method, multi-scale, and interdisciplinary research.
Sustainable management of semi-arid African savannas under environmental and political change
(2012)
Drylands cover about 40% of the earth’s land surface and provide the basis for the livelihoods of 38% of the global human population. Worldwide, these ecosystems are prone to heavy degradation. Increasing levels of dryland degradation result a strong decline of ecosystem services. In addition, in highly variable semi-arid environments changing future environmental conditions will potentially have severe consequences for productivity and ecosystem dynamics. Hence, global efforts have to be made to understand the particular causes and consequences of dryland degradation and to promote sustainable management options for semi-arid and arid ecosystems in a changing world. Here I particularly address the problem of semi-arid savanna degradation, which mostly occurs in form of woody plant encroachment. At this, I aim at finding viable sustainable management strategies and improving the general understanding of semi-arid savanna vegetation dynamics under conditions of extensive livestock production. Moreover, the influence of external forces, i.e. environmental change and land reform, on the use of savanna vegetation and on the ecosystem response to this land use is assessed. Based on this I identify conditions and strategies that facilitate a sustainable use of semi-arid savanna rangelands in a changing world. I extended an eco-hydrological model to simulate rangeland vegetation dynamics for a typical semi-arid savanna in eastern Namibia. In particular, I identified the response of semi-arid savanna vegetation to different land use strategies (including fire management) also with regard to different predicted precipitation, temperature and CO2 regimes. Not only environmental but also economic and political constraints like e.g. land reform programmes are shaping rangeland management strategies. Hence, I aimed at understanding the effects of the ongoing process of land reform in southern Africa on land use and the semi-arid savanna vegetation. Therefore, I developed and implemented an agent-based ecological-economic modelling tool for interactive role plays with land users. This tool was applied in an interdisciplinary empirical study to identify general patterns of management decisions and the between-farm cooperation of land reform beneficiaries in eastern Namibia. The eco-hydrological simulations revealed that the future dynamics of semi-arid savanna vegetation strongly depend on the respective climate change scenario. In particular, I found that the capacity of the system to sustain domestic livestock production will strongly depend on changes in the amount and temporal distribution of precipitation. In addition, my simulations revealed that shrub encroachment will become less likely under future climatic conditions although positive effects of CO2 on woody plant growth and transpiration have been considered. While earlier studies predicted a further increase in shrub encroachment due to increased levels of atmospheric CO2, my contrary finding is based on the negative impacts of temperature increase on the drought sensitive seedling germination and establishment of woody plant species. Further simulation experiments revealed that prescribed fires are an efficient tool for semi-arid rangeland management, since they suppress woody plant seedling establishment. The strategies tested have increased the long term productivity of the savanna in terms of livestock production and decreased the risk for shrub encroachment (i.e. savanna degradation). This finding refutes the views promoted by existing studies, which state that fires are of minor importance for the vegetation dynamics of semi-arid and arid savannas. Again, the difference in predictions is related to the bottleneck at the seedling establishment stage of woody plants, which has not been sufficiently considered in earlier studies. The ecological-economic role plays with Namibian land reform beneficiaries showed that the farmers made their decisions with regard to herd size adjustments according to economic but not according to environmental variables. Hence, they do not manage opportunistically by tracking grass biomass availability but rather apply conservative management strategies with low stocking rates. This implies that under the given circumstances the management of these farmers will not per se cause (or further worsen) the problem of savanna degradation and shrub encroachment due to overgrazing. However, as my results indicate that this management strategy is rather based on high financial pressure, it is not an indicator for successful rangeland management. Rather, farmers struggle hard to make any positive revenue from their farming business and the success of the Namibian land reform is currently disputable. The role-plays also revealed that cooperation between farmers is difficult even though obligatory due to the often small farm sizes. I thus propose that cooperation needs to be facilitated to improve the success of land reform beneficiaries.
Environmental drivers interactively affect individual tree growth across temperate European forests
(2018)
Forecasting the growth of tree species to future environmental changes requires abetter understanding of its determinants. Tree growth is known to respond to global‐change drivers such as climate change or atmospheric deposition, as well as to localland‐use drivers such as forest management. Yet, large geographical scale studiesexamining interactive growth responses to multiple global‐change drivers are relativelyscarce and rarely consider management effects. Here, we assessed the interactiveeffects of three global‐change drivers (temperature, precipitation and nitrogen deposi-tion) on individual tree growth of three study species (Quercus robur/petraea, Fagus syl-vatica and Fraxinus excelsior). We sampled trees along spatial environmental gradientsacross Europe and accounted for the effects of management for Quercus. We collectedincrement cores from 267 trees distributed over 151 plots in 19 forest regions andcharacterized their neighbouring environment to take into account potentially confounding factors such as tree size, competition, soil conditions and elevation. Wedemonstrate that growth responds interactively to global‐change drivers, with species ‐specific sensitivities to the combined factors. Simultaneously high levels of precipita-tion and deposition benefited Fraxinus, but negatively affected Quercus’ growth, high-lighting species‐specific interactive tree growth responses to combined drivers. ForFagus, a stronger growth response to higher temperatures was found when precipita-tion was also higher, illustrating the potential negative effects of drought stress underwarming for this species. Furthermore, we show that past forest management canmodulate the effects of changing temperatures on Quercus’ growth; individuals in plotswith a coppicing history showed stronger growth responses to higher temperatures.Overall, our findings highlight how tree growth can be interactively determined by glo-bal‐change drivers, and how these growth responses might be modulated by past for-est management. By showing future growth changes for scenarios of environmentalchange, we stress the importance of considering multiple drivers, including past man-agement and their interactions, when predicting tree growth.
Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential. Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573 lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate change provide preliminary targets for development of climate change conservation management and mitigation strategies.
In a changing world, phytoplankton communities face a large variety of challenges including altered light regimes. These alterations are caused by more pronounced stratification due to rising temperatures, enhanced eutrophication, and browning of lakes. Community responses toward these effects can emerge as alterations in physiology, biomass, biochemical composition, or diversity. In this study, we addressed the combined effects of changes in light and nutrient conditions on community responses. In particular, we investigated how light intensity and variability under two nutrient conditions influence (1) fast responses such as adjustments in photosynthesis, (2) intermediate responses such as pigment adaptation and (3) slow responses such as changes in community biomass and species composition. Therefore, we exposed communities consisting of five phytoplankton species belonging to different taxonomic groups to two constant and two variable light intensity treatments combined with two levels of phosphorus supply. The tested phytoplankton communities exhibited increased fast reactions of photosynthetic processes to light variability and light intensity. The adjustment of their light harvesting mechanisms via community pigment composition was not affected by light intensity, variability, or nutrient supply. However, pigment specific effects of light intensity, light variability, and nutrient supply on the proportion of the respective pigments were detected. Biomass was positively affected by higher light intensity and nutrient concentrations while the direction of the effect of variability was modulated by light intensity. Light variability had a negative impact on biomass at low, but a positive impact at high light intensity. The effects on community composition were species specific. Generally, the proportion of green algae was higher under high light intensity, whereas the cyanobacterium performed better under low light conditions. In addition to that, the diatom and the cryptophyte performed better with high nutrient supply while the green algae as well as the cyanobacterium performed better at low nutrient conditions. This shows that light intensity, light variability, and nutrient supply interactively affect communities. Furthermore, the responses are highly species and pigment specific, thus to clarify the effects of climate change a deeper understanding of the effects of light variability and species interactions within communities is important.
In a changing world, phytoplankton communities face a large variety of challenges including altered light regimes. These alterations are caused by more pronounced stratification due to rising temperatures, enhanced eutrophication, and browning of lakes. Community responses toward these effects can emerge as alterations in physiology, biomass, biochemical composition, or diversity. In this study, we addressed the combined effects of changes in light and nutrient conditions on community responses. In particular, we investigated how light intensity and variability under two nutrient conditions influence (1) fast responses such as adjustments in photosynthesis, (2) intermediate responses such as pigment adaptation and (3) slow responses such as changes in community biomass and species composition. Therefore, we exposed communities consisting of five phytoplankton species belonging to different taxonomic groups to two constant and two variable light intensity treatments combined with two levels of phosphorus supply. The tested phytoplankton communities exhibited increased fast reactions of photosynthetic processes to light variability and light intensity. The adjustment of their light harvesting mechanisms via community pigment composition was not affected by light intensity, variability, or nutrient supply. However, pigment specific effects of light intensity, light variability, and nutrient supply on the proportion of the respective pigments were detected. Biomass was positively affected by higher light intensity and nutrient concentrations while the direction of the effect of variability was modulated by light intensity. Light variability had a negative impact on biomass at low, but a positive impact at high light intensity. The effects on community composition were species specific. Generally, the proportion of green algae was higher under high light intensity, whereas the cyanobacterium performed better under low light conditions. In addition to that, the diatom and the cryptophyte performed better with high nutrient supply while the green algae as well as the cyanobacterium performed better at low nutrient conditions. This shows that light intensity, light variability, and nutrient supply interactively affect communities. Furthermore, the responses are highly species and pigment specific, thus to clarify the effects of climate change a deeper understanding of the effects of light variability and species interactions within communities is important.
In a changing world, phytoplankton communities face a large variety of challenges including altered light regimes. These alterations are caused by more pronounced stratification due to rising temperatures, enhanced eutrophication, and browning of lakes. Community responses toward these effects can emerge as alterations in physiology, biomass, biochemical composition, or diversity. In this study, we addressed the combined effects of changes in light and nutrient conditions on community responses. In particular, we investigated how light intensity and variability under two nutrient conditions influence (1) fast responses such as adjustments in photosynthesis, (2) intermediate responses such as pigment adaptation and (3) slow responses such as changes in community biomass and species composition. Therefore, we exposed communities consisting of five phytoplankton species belonging to different taxonomic groups to two constant and two variable light intensity treatments combined with two levels of phosphorus supply. The tested phytoplankton communities exhibited increased fast reactions of photosynthetic processes to light variability and light intensity. The adjustment of their light harvesting mechanisms via community pigment composition was not affected by light intensity, variability, or nutrient supply. However, pigment specific effects of light intensity, light variability, and nutrient supply on the proportion of the respective pigments were detected. Biomass was positively affected by higher light intensity and nutrient concentrations while the direction of the effect of variability was modulated by light intensity. Light variability had a negative impact on biomass at low, but a positive impact at high light intensity. The effects on community composition were species specific. Generally, the proportion of green algae was higher under high light intensity, whereas the cyanobacterium performed better under low light conditions. In addition to that, the diatom and the cryptophyte performed better with high nutrient supply while the green algae as well as the cyanobacterium performed better at low nutrient conditions. This shows that light intensity, light variability, and nutrient supply interactively affect communities. Furthermore, the responses are highly species and pigment specific, thus to clarify the effects of climate change a deeper understanding of the effects of light variability and species interactions within communities is important.
Floods and debris flows in small Alpine torrent catchments (<10km(2)) arise from a combination of critical antecedent system state conditions and mostly convective precipitation events with high precipitation intensities. Thus, climate change may influence the magnitude-frequency relationship of extreme events twofold: by a modification of the occurrence probabilities of critical hydrological system conditions and by a change of event precipitation characteristics. Three small Alpine catchments in different altitudes in Western Austria (Ruggbach, Brixenbach and Langentalbach catchment) were investigated by both field experiments and process-based simulation. Rainfall-runoff model (HQsim) runs driven by localized climate scenarios (CNRM-RM4.5/ARPEGE, MPI-REMO/ECHAM5 and ICTP-RegCM3/ECHAM5) were used in order to estimate future frequencies of stormflow triggering system state conditions. According to the differing altitudes of the study catchments, two effects of climate change on the hydrological systems can be observed. On one hand, the seasonal system state conditions of medium altitude catchments are most strongly affected by air temperature-controlled processes such as the development of the winter snow cover as well as evapotranspiration. On the other hand, the unglaciated high-altitude catchment is less sensitive to climate change-induced shifts regarding days with critical antecedent soil moisture and desiccated litter layer due to its elevation-related small proportion of sensitive areas. For the period 2071-2100, the number of days with critical antecedent soil moisture content will be significantly reduced to about 60% or even less in summer in all catchments. In contrast, the number of days with dried-out litter layers causing hydrophobic effects will increase by up to 8%-11% of the days in the two lower altitude catchments. The intensity analyses of heavy precipitation events indicate a clear increase in rain intensities of up to 10%.
Flood risk is impacted by a range of physical and socio-economic processes. Hence, the quantification of flood risk ideally considers the complete flood risk chain, from atmospheric processes through catchment and river system processes to damage mechanisms in the affected areas. Although it is generally accepted that a multitude of changes along the risk chain can occur and impact flood risk, there is a lack of knowledge of how and to what extent changes in influencing factors propagate through the chain and finally affect flood risk. To fill this gap, we present a comprehensive sensitivity analysis which considers changes in all risk components, i.e. changes in climate, catchment, river system, land use, assets, and vulnerability. The application of this framework to the mesoscale Mulde catchment in Germany shows that flood risk can vary dramatically as a consequence of plausible change scenarios. It further reveals that components that have not received much attention, such as changes in dike systems or in vulnerability, may outweigh changes in often investigated components, such as climate. Although the specific results are conditional on the case study area and the selected assumptions, they emphasize the need for a broader consideration of potential drivers of change in a comprehensive way. Hence, our approach contributes to a better understanding of how the different risk components influence the overall flood risk.
Due to anthropogenic greenhouse gas emissions, Earth’s average surface temperature is steadily increasing. As a consequence, many weather extremes are likely to become more frequent and intense. This poses a threat to natural and human systems, with local impacts capable of destroying exposed assets and infrastructure, and disrupting economic and societal activity. Yet, these effects are not locally confined to the directly affected regions, as they can trigger indirect economic repercussions through loss propagation along supply chains. As a result, local extremes yield a potentially global economic response. To build economic resilience and design effective adaptation measures that mitigate adverse socio-economic impacts of ongoing climate change, it is crucial to gain a comprehensive understanding of indirect impacts and the underlying economic mechanisms.
Presenting six articles in this thesis, I contribute towards this understanding. To this end, I expand on local impacts under current and future climate, the resulting global economic response, as well as the methods and tools to analyze this response.
Starting with a traditional assessment of weather extremes under climate change, the first article investigates extreme snowfall in the Northern Hemisphere until the end of the century. Analyzing an ensemble of global climate model projections reveals an increase of the most extreme snowfall, while mean snowfall decreases.
Assessing repercussions beyond local impacts, I employ numerical simulations to compute indirect economic effects from weather extremes with the numerical agent-based shock propagation model Acclimate. This model is used in conjunction with the recently emerged storyline framework, which involves analyzing the impacts of a particular reference extreme event and comparing them to impacts in plausible counterfactual scenarios under various climate or socio-economic conditions. Using this approach, I introduce three primary storylines that shed light on the complex mechanisms underlying economic loss propagation.
In the second and third articles of this thesis, I analyze storylines for the historical Hurricanes Sandy (2012) and Harvey (2017) in the USA. For this, I first estimate local economic output losses and then simulate the resulting global economic response with Acclimate. The storyline for Hurricane Sandy thereby focuses on global consumption price anomalies and the resulting changes in consumption. I find that the local economic disruption leads to a global wave-like economic price ripple, with upstream effects propagating in the supplier direction and downstream effects in the buyer direction. Initially, an upstream demand reduction causes consumption price decreases, followed by a downstream supply shortage and increasing prices, before the anomalies decay in a normalization phase. A dominant upstream or downstream effect leads to net consumption gains or losses of a region, respectively. Moreover, I demonstrate that a longer direct economic shock intensifies the downstream effect for many regions, leading to an overall consumption loss.
The third article of my thesis builds upon the developed loss estimation method by incorporating projections to future global warming levels. I use these projections to explore how the global production response to Hurricane Harvey would change under further increased global warming. The results show that, while the USA is able to nationally offset direct losses in the reference configuration, other countries have to compensate for increasing shares of counterfactual future losses. This compensation is mainly achieved by large exporting countries, but gradually shifts towards smaller regions. These findings not only highlight the economy’s ability to flexibly mitigate disaster losses to a certain extent, but also reveal the vulnerability and economic disadvantage of regions that are exposed to extreme weather events.
The storyline in the fourth article of my thesis investigates the interaction between global economic stress and the propagation of losses from weather extremes. I examine indirect impacts of weather extremes — tropical cyclones, heat stress, and river floods — worldwide under two different economic conditions: an unstressed economy and a globally stressed economy, as seen during the Covid-19 pandemic. I demonstrate that the adverse effects of weather extremes on global consumption are strongly amplified when the economy is under stress. Specifically, consumption losses in the USA and China double and triple, respectively, due to the global economy’s decreased capacity for disaster loss compensation. An aggravated scarcity intensifies the price response, causing consumption losses to increase.
Advancing on the methods and tools used here, the final two articles in my thesis extend the agent-based model Acclimate and formalize the storyline approach. With the model extension described in the fifth article, regional consumers make rational choices on the goods bought such that their utility is maximized under a constrained budget. In an out-of-equilibrium economy, these rational consumers are shown to temporarily increase consumption of certain goods in spite of rising prices.
The sixth article of my thesis proposes a formalization of the storyline framework, drawing on multiple studies including storylines presented in this thesis. The proposed guideline defines eight central elements that can be used to construct a storyline.
Overall, this thesis contributes towards a better understanding of economic repercussions of weather extremes. It achieves this by providing assessments of local direct impacts, highlighting mechanisms and impacts of loss propagation, and advancing on methods and tools used.
Signals for 2 degrees C
(2019)
The targets of the Paris Agreement make it necessary to redirect finance flows towards sustainable, low-carbon infrastructures and technologies. Currently, the potential of institutional investors to help finance this transition is widely discussed. Thus, this paper takes a closer look at influence factors for green investment decisions of large European insurance companies. With a mix of qualitative and quantitative methods, the importance of policy, market and civil society signals is evaluated. In summary, respondents favor measures that promote green investment, such as feed-in tariffs or adjustments of capital charges for green assets, over ones that make carbon-intensive investments less attractive, such as the phase-out of fossil fuel subsidies or a carbon price. While investors currently see a low impact of the carbon price, they rank a substantial reform as an important signal for the future. Respondents also emphasize that policy signals have to be coherent and credible to coordinate expectations.
The Arctic environments constitute rich and dynamic ecosystems, dominated by microorganisms extremely well adapted to survive and function under severe conditions. A range of physiological adaptations allow the microbiota in these habitats to withstand low temperatures, low water and nutrient availability, high levels of UV radiation, etc. In addition, other adaptations of clear competitive nature are directed at not only surviving but thriving in these environments, by disrupting the metabolism of neighboring cells and affecting intermicrobial communication. Since Arctic microbes are bioindicators which amplify climate alterations in the environment, the Arctic region presents the opportunity to study local microbiota and carry out research about interesting, potentially virulent phenotypes that could be dispersed into other habitats around the globe as a consequence of accelerating climate change. In this context, exploration of Arctic habitats as well as descriptions of the microbes inhabiting them are abundant but microbial competitive strategies commonly associated with virulence and pathogens are rarely reported. In this project, environmental samples from the Arctic region were collected and microorganisms (bacteria and fungi) were isolated. The clinical relevance of these microorganisms was assessed by observing the following virulence markers: ability to grow at a range of temperatures, expression of antimicrobial resistance and production of hemolysins. The aim of this project is to determine the frequency and relevance of these characteristics in an effort to understand microbial adaptations in habitats threatened by climate change. The isolates obtained and described here were able to grow at a range of temperatures, in some cases more than 30 °C higher than their original isolation temperature. A considerable number of them consistently expressed compounds capable of lysing sheep and bovine erythrocytes on blood agar at different incubation temperatures. Ethanolic extracts of these bacteria were able to cause rapid and complete lysis of erythrocyte suspensions and might even be hemolytic when assayed on human blood. In silico analyses showed a variety of resistance elements, some of them novel, against natural and synthetic antimicrobial compounds. In vitro experiments against a number of antimicrobial compounds showed resistance phenotypes belonging to wild-type populations and some non-wild type which clearly denote human influence in the acquisition of antimicrobial resistance. The results of this project demonstrate the presence of virulence-associated factors expressed by microorganisms of natural, non-clinical environments. This study contains some of the first reports, to the best of our knowledge, of hemolytic microbes isolated from the Arctic region. In addition, it provides additional information about the presence and expression of intrinsic and acquired antimicrobial resistance in environmental isolates, contributing to the understanding of the evolution of relevant pathogenic species and opportunistic pathogens. Finally, this study highlights some of the potential risks associated with changes in the polar regions (habitat melting and destruction, ecosystem transition and re-colonization) as important indirect consequences of global warming and altered climatic conditions around the planet.
The Arctic ecosystem, a reservoir of genetic microbial diversity, represents a virtually unlimited source of microorganisms that could interact with human beings. Despite continuous exploration of Arctic habitats and description of their microbial communities, bacterial phenotypes commonly associated with pathogenicity, such as hemolytic activity, have rarely been reported. In this study, samples of snow, fresh and marine water, soil, and sediment from several habitats in the Arctic archipelago of Svalbard were collected during Summer, 2017. Bacterial isolates were obtained after incubation on oligotrophic media at different temperatures and their hemolytic potential was assessed on sheep blood agar plates. Partial (alpha) or true (beta) hemolysis was observed in 32 out of 78 bacterial species. Genes expressing cytolytic compounds, such as hemolysins, likely increase the general fitness of the producing microorganisms and confer a competitive advantage over the availability of nutrients in natural habitats. In environmental species, the nutrient-acquisition function of these compounds presumably precedes their function as toxins for mammalian erythrocytes. However, in the light of global warming, the presence of hemolytic bacteria in Arctic environments highlights the possible risks associated with these microorganisms in the event of habitat melting/destruction, ecosystem transition, and re-colonization.
The work is designed to investigate the impacts and sensitivity of climate change on water resources, droughts and hydropower production in Malawi, the South-Eastern region which is highly vulnerable to climate change. It is observed that rainfall is decreasing and temperature is increasing which calls for the understanding of what these changes may impact the water resources, drought occurrences and hydropower generation in the region. The study is conducted in the Greater Lake Malawi Basin (Lake Malawi and Shire River Basins) and is divided into three projects. The first study is assessing the variability and trends of both meteorological and hydrological droughts from 1970-2013 in Lake Malawi and Shire River basins using the standardized precipitation index (SPI) and standardized precipitation and evaporation Index (SPEI) for meteorological droughts and the lake level change index (LLCI) for hydrological droughts. And later the relationship of the meteorological and hydrological droughts is established.
While the second study extends the drought analysis into the future by examining the potential future meteorological water balance and associated drought characteristics such as the drought intensity (DI), drought months (DM), and drought events (DE) in the Greater Lake Malawi Basin. The sensitivity of drought to changes of rainfall and temperature is also assessed using the scenario-neutral approach. The climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021–2050 and 2071–2100 are used. The study also investigates the effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble in reproducing observed drought characteristics as compared to raw climate projections.
The sensitivity of key hydrologic variables and hydropower generation to climate change in Lake Malawi and Shire River basins is assessed in third study. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Similar to second study, the scenario-neutral approach is also applied to determine the sensitivity of climate change on water resources more particularly Lake Malawi level and Shire River flow which later helps to estimate the hydropower production susceptibility.
Results suggest that meteorological droughts are increasing due to a decrease in precipitation which is exacerbated by an increase in temperature (potential evapotranspiration). The hydrological system of Lake Malawi seems to have a >24-month memory towards meteorological conditions since the 36-months SPEI can predict hydrological droughts ten-months in advance. The study has found the critical lake level that would trigger hydrological drought to be 474.1 m.a.s.l.
Despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher DI and longer events (DM). DI is projected to increase between +25% and +50% during 2021-2050 and between +131% and +388% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, DE is decreasing. Projected droughts based on RCP8.5 are 1.7 times more severe than droughts based on RCP4.5.
It is also found that an annual temperature increase of 1°C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi’s water budget. Meanwhile, a +5% (-5%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows on Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5°C (3.5°C) and -20% (-15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021–2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071–2100.
The findings are later linked to global policies more particularly the United Nations Framework Convention on Climate Change (UNFCCC)’s Paris Agreement and the United Nations (UN)’s Sustainable Development Goals (SDGs), and how the failure to adhere the restriction of temperature increase below the global limit of 1.5°C will affect drought and the water resources in Malawi consequently impact the hydropower production. As a result, the achievement of most of the SDGs will be compromised.
The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change. The information generation is important for decision making more especially supporting the climate action required to fight against climate change. The frequency of extreme climate events due to climate change has reached the climate emergency as saving lives and livelihoods require urgent action.
The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021–2050) and far-term period (2071–2100) with reference to 1976–2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021–2050 and between +131 and +388% during 2071–2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.
The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021-2050) and far-term period (2071-2100) with reference to 1976-2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021-2050 and between +131 and +388% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.
The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021–2050) and far-term period (2071–2100) with reference to 1976–2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021–2050 and between +131 and +388% during 2071–2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.
In den letzten drei Jahrzehnten wurden in einigen Seen und Feuchtgebieten in bewaldeten Einzugsgebieten Nordost-Brandenburgs sinkende Wasserstände beobachtet. In diesen Gebieten bestimmt die Grundwasserneubildung im Einzugsgebiet maßgeblich das Wasserdargebot der Seen und Feuchtgebiete, die deshalb hier als grundwasserabhängige Landschaftselemente bezeichnet werden. Somit weisen die sinkenden Wasserstände auf einen Rückgang der wegen des geringen Niederschlagsdargebotes ohnehin schon geringen Grundwasserneubildung hin. Die Höhe der Grundwasserneubildung ist neben den hydroklimatischen Randbedingungen auch von der Landnutzung abhängig. Veränderungen in der Waldvegetation und der hydroklimatischen Randbedingungen bewirken Änderungen der Grundwasserneubildung und beeinflussen somit auch den Wasserhaushalt der Seen und Feuchtgebiete. Aktuell wird die Waldvegetation durch Kiefernmonokulturen dominiert, mit im Vergleich zu anderen Baumarten höherer Evapotranspiration. Entwicklungen in der Forstwirtschaft streben die Verringerung von Kiefernmonokulturen an. Diese sollen langfristig auf geeigneten Standorten durch Laubmischwälder ersetzt werden. Dadurch lassen sich eine geringere Evapotranspiration und damit eine höhere Grundwasserneubildung erreichen. In der vorliegenden Arbeit werden am Beispiel des Redernswalder Sees und des Briesensees die Ursachen der beobachteten sinkenden Wasserstände analysiert. Ihre Wasserstände nahmen in den letzten 25 Jahren um mehr als 3 Meter ab. Weiterhin wird untersucht, wie die erwarteten Klimaänderungen und Veränderungen in der Waldbewirtschaftung die zukünftige Grundwasserneubildung und den Wasserhaushalt von Seen beeinflussen können. Die Entwicklung der Grundwasserneubildung im Untersuchungsgebiet wurde mit dem Wasserhaushaltsmodell WaSiM-ETH simuliert. Die Analyse der Wechselwirkungen der Seen mit dem regionalen quartären Grundwasserleitersystem erfolgte mit dem 3D-Grundwassermodell FEFLOW. Mögliche zukünftige Veränderungen der Grundwasserneubildung und der Seewasserstände durch Klimaänderungen und Waldumbau wurden mit Szenarienrechnungen bis zum Jahr 2100 analysiert. Die modellgestützte Analyse zeigte, dass die beobachteten abnehmenden Wasserstände zu etwa gleichen Anteilen durch Veränderungen der hydroklimatischen Randbedingungen sowie durch Veränderungen in der Waldvegetation und damit abnehmenden Grundwasserneubildungsraten zu erklären sind. Die zukünftigen Entwicklungen der Grundwasserneubildung und der Wasserstände sind geprägt von sich ändernden hydroklimatischen Randbedingungen und einem sukzessiven Wandel der Kiefernbestände zu Laubwäldern. Der Waldumbau hat positive Wirkungen auf die Grundwasserneubildung und damit auf die Wasserstände. Damit können die Einflüsse des eingesetzten REMO-A1B-Klimaszenarios zum Ende des Modellzeitraumes durch den Waldumbau nicht kompensiert werden, das Sinken des Wasserstandes wird jedoch wesentlich reduziert. Bei dem moderateren REMO-B1-Klimaszenario werden die Wasserstände des Jahres 2008 durch den Waldumbau bis zum Jahr 2100 überschritten.