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ArcticBeach v1.0
(2022)
In the Arctic, air temperatures are increasing and sea ice is declining, resulting in larger waves and a longer open water season, all of which intensify the thaw and erosion of ice-rich coasts. Climate change has been shown to increase the rate of Arctic coastal erosion, causing problems for Arctic cultural heritage, existing industrial, military, and civil infrastructure, as well as changes in nearshore biogeochemistry. Numerical models that reproduce historical and project future Arctic erosion rates are necessary to understand how further climate change will affect these problems, and no such model yet exists to simulate the physics of erosion on a pan-Arctic scale. We have coupled a bathystrophic storm surge model to a simplified physical erosion model of a permafrost coastline. This Arctic erosion model, called ArcticBeach v1.0, is a first step toward a physical parameterization of Arctic shoreline erosion for larger-scale models. It is forced by wind speed and direction, wave period and height, sea surface temperature, all of which are masked during times of sea ice cover near the coastline. Model tuning requires observed historical retreat rates (at least one value), as well as rough nearshore bathymetry. These parameters are already available on a pan-Arctic scale. The model is validated at three study sites at 1) Drew Point (DP), Alaska, 2) Mamontovy Khayata (MK), Siberia, and 3) Veslebogen Cliffs, Svalbard. Simulated cumulative retreat rates for DP and MK respectively (169 and 170 m) over the time periods studied at each site (2007-2016, and 1995-2018) are found to the same order of magnitude as observed cumulative retreat (172 and 120 m). The rocky Veslebogen cliffs have small observed cumulative retreat rates (0.05 m over 2014-2016), and our model was also able to reproduce this same order of magnitude of retreat (0.08 m). Given the large differences in geomorphology between the study sites, this study provides a proof-of-concept that ArcticBeach v1.0 can be applied on very different permafrost coastlines. ArcticBeach v1.0 provides a promising starting point to project retreat of Arctic shorelines, or to evaluate historical retreat in places that have had few observations.
High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.
High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.
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.
Nature-based solutions (NBS) are seen as a promising adaptation measure that sustainably deals with diverse societal challenges, while simultaneously delivering multiple benefits. Nature-based solutions have been highlighted as a resilient and sustainable means of mitigating floods and other hazards globally. This study examined diverging conceptualizations of NBS, as well as the attitudinal (for example, emotions and beliefs) and contextual (for example, legal and political aspects) barriers and drivers of NBS for flood risks in South Korea. Semistructured interviews were conducted with 11 experts and focused on the topic of flood risk measures and NBS case studies. The analysis found 11 barriers and five drivers in the attitudinal domain, and 13 barriers and two drivers in the contextual domain. Most experts see direct monetary benefits as an important attitudinal factor for the public. Meanwhile, the cost-effectiveness of NBS and their capacity to cope with flood risks were deemed influential factors that could lead decision makers to opt for NBS. Among the contextual factors, insufficient systems to integrate NBS in practice and the ideologicalization of NBS policy were found to be peculiar barriers, which hinder consistent realization of initiatives and a long-term national plan for NBS. Understanding the barriers and drivers related to the mainstreaming of NBS is critical if we are to make the most of such solutions for society and nature. It is also essential that we have a shared definition, expectation, and vision of NBS.
Climate science today makes use of a variety of red globes to explore and communicate findings. These transform the iconography which informs this image: the idealised, even mythical vision of the blue, vulnerable and perfect marble is impaired by the application of the colours yellow and red. Since only predictions that employ a lot of red seem to exist, spectators are confronted with the message that the future Earth that might turn out as envisaged here is undesirable. Here intuitively powerful narrations of the end of the world may connect. By employing methods of art history and visual analysis, and building on examples from current Intergovernmental Panel on Climate Change reports and future scenario maps, this article explores how burning world images bear - intentionally or not - elements of horror and shock. My question explored here is as follows: should 'burning world' images be understood as a new and powerful cosmology?
Carbon storage capacity of semi-arid grassland soils and sequestration potentials in northern China
(2015)
Organic carbon (OC) sequestration in degraded semi-arid environments by improved soil management is assumed to contribute substantially to climate change mitigation. However, information about the soil organic carbon (SOC) sequestration potential in steppe soils and their current saturation status remains unknown. In this study, we estimated the OC storage capacity of semi-arid grassland soils on the basis of remote, natural steppe fragments in northern China. Based on the maximum OC saturation of silt and clay particles <20m, OC sequestration potentials of degraded steppe soils (grazing land, arable land, eroded areas) were estimated. The analysis of natural grassland soils revealed a strong linear regression between the proportion of the fine fraction and its OC content, confirming the importance of silt and clay particles for OC stabilization in steppe soils. This relationship was similar to derived regressions in temperate and tropical soils but on a lower level, probably due to a lower C input and different clay mineralogy. In relation to the estimated OC storage capacity, degraded steppe soils showed a high OC saturation of 78-85% despite massive SOC losses due to unsustainable land use. As a result, the potential of degraded grassland soils to sequester additional OC was generally low. This can be related to a relatively high contribution of labile SOC, which is preferentially lost in the course of soil degradation. Moreover, wind erosion leads to substantial loss of silt and clay particles and consequently results in a direct loss of the ability to stabilize additional OC. Our findings indicate that the SOC loss in semi-arid environments induced by intensive land use is largely irreversible. Observed SOC increases after improved land management mainly result in an accumulation of labile SOC prone to land use/climate changes and therefore cannot be regarded as contribution to long-term OC sequestration.
Strong waves in the mid-latitude circulation have been linked to extreme surface weather and thus changes in waviness could have serious consequences for society. Several theories have been proposed which could alter waviness, including tropical sea surface temperature anomalies or rapid climate change in the Arctic. However, so far it remains unclear whether any changes in waviness have actually occurred. Here we propose a novel meandering index which captures the maximum waviness in geopotential height contours at any given day, using all information of the full spatial position of each contour. Data are analysed on different time scale (from daily to 11 day running means) and both on hemispheric and regional scales. Using quantile regressions, we analyse how seasonal distributions of this index have changed over 1979-2015. The most robust changes are detected for autumn which has seen a pronounced increase in strongly meandering patterns at the hemispheric level as well as over the Eurasian sector. In summer for both the hemisphere and the Eurasian sector, significant downward trends in meandering are detected on daily timescales which is consistent with the recently reported decrease in summer storm track activity. The American sector shows the strongest increase in meandering in the warm season: in particular for 11 day running mean data, indicating enhanced amplitudes of quasi-stationary waves. Our findings have implications for both the occurrence of recent cold spells and persistent heat waves in the mid-latitudes.
In the wake of 21st century, humanity witnessed a phenomenal raise of urban agglomerations as powerhouses for innovation and socioeconomic growth. Driving much of national (and in few instances even global) economy, such a gargantuan raise of cities is also accompanied by subsequent increase in energy, resource consumption and waste generation. Much of anthropogenic transformation of Earth's environment in terms of environmental pollution at local level to planetary scale in the form of climate change is currently taking place in cities. Projected to be crucibles for entire humanity by the end of this century, the ultimate fate of humanity predominantly lies in the hands of technological innovation, urbanites' attitudes towards energy/resource consumption and development pathways undertaken by current and future cities. Considering the unparalleled energy, resource consumption and emissions currently attributed to global cities, this thesis addresses these issues from an efficiency point of view. More specifically, this thesis addresses the influence of population size, density, economic geography and technology in improving urban greenhouse gas (GHG) emission efficiency and identifies the factors leading to improved eco-efficiency in cities. In order to investigate the in uence of these factors in improving emission and resource efficiency in cities, a multitude of freely available datasets were coupled with some novel methodologies and analytical approaches in this thesis.
Merging the well-established Kaya Identity to the recently developed urban scaling laws, an Urban Kaya Relation is developed to identify whether large cities are more emission efficient and the intrinsic factors leading to such (in)efficiency. Applying Urban Kaya Relation to a global dataset of 61 cities in 12 countries, this thesis identifed that large cities in developed regions of the world will bring emission efficiency gains because of the better technologies implemented in these cities to produce and utilize energy consumption while the opposite is the case for cities in developing regions. Large cities in developing countries are less efficient mainly because of their affluence and lack of efficient technologies. Apart from the in uence of population size on emission efficiency, this thesis identified the crucial role played by population density in improving building and on-road transport sector related emission efficiency in cities. This is achieved by applying the City Clustering Algorithm (CCA) on two different gridded land use datasets and a standard emission inventory to attribute these sectoral emissions to all inhabited settlements in the USA. Results show that doubling the population density would entail a reduction in the total CO2 emissions in buildings and on-road sectors typically by at least 42 %. Irrespective of their population size and density, cities are often blamed for their intensive resource consumption that threatens not only local but also global sustainability. This thesis merged the concept of urban metabolism with benchmarking and identified cities which are eco-efficient. These cities enable better socioeconomic conditions while being less burden to the environment. Three environmental burden indicators (annual average NO2 concentration, per capita waste generation and water consumption) and two socioeconomic indicators (GDP per capita and employment ratio) for 88 most populous European cities are considered in this study. Using two different non-parametric ranking methods namely regression residual ranking and Data Envelopment Analysis (DEA), eco-efficient cities and their determining factors are identified. This in-depth analysis revealed that mature cities with well-established economic structures such as Munich, Stockholm and Oslo are eco-efficient. Further, correlations between objective eco-efficiency ranking with each of the indicator rankings and the ranking of urbanites' subjective perception about quality of life are analyzed. This analysis revealed that urbanites' perception about quality of life is not merely confined to the socioeconomic well-being but rather to their combination with lower environmental burden.
In summary, the findings of this dissertation has three general conclusions for improving emission and ecological efficiency in cities. Firstly, large cities in emerging nations face a huge challenge with respect to improving their emission efficiency. The task in front of these cities is threefold: (1) deploying efficient technologies for the generation of electricity and improvement of public transportation to unlock their leap frogging potential, (2) addressing the issue of energy poverty and (3) ensuring that these cities do not develop similar energy consumption patterns with infrastructure lock-in behavior similar to those of cities in developed regions. Secondly, the on-going urban sprawl as a global phenomenon will decrease the emission efficiency within the building and transportation sector. Therefore, local policy makers should identify adequate fiscal and land use policies to curb urban sprawl. Lastly, since mature cities with well-established economic structures are more eco-efficient and urbanites' perception re ects its combination with decreasing environmental burden; there is a need to adopt and implement strategies which enable socioeconomic growth in cities whilst decreasing their environment burden.
Agriculture is one of the most important human activities providing food and more agricultural goods for seven billion people around the world and is of special importance in sub-Saharan Africa. The majority of people depends on the agricultural sector for their livelihoods and will suffer from negative climate change impacts on agriculture until the middle and end of the 21st century, even more if weak governments, economic crises or violent conflicts endanger the countries’ food security. The impact of temperature increases and changing precipitation patterns on agricultural vegetation motivated this thesis in the first place. Analyzing the potentials of reducing negative climate change impacts by adapting crop management to changing climate is a second objective of the thesis. As a precondition for simulating climate change impacts on agricultural crops with a global crop model first the timing of sowing in the tropics was improved and validated as this is an important factor determining the length and timing of the crops´ development phases, the occurrence of water stress and final crop yield. Crop yields are projected to decline in most regions which is evident from the results of this thesis, but the uncertainties that exist in climate projections and in the efficiency of adaptation options because of political, economical or institutional obstacles have to be considered. The effect of temperature increases and changing precipitation patterns on crop yields can be analyzed separately and varies in space across the continent. Southern Africa is clearly the region most susceptible to climate change, especially to precipitation changes. The Sahel north of 13° N and parts of Eastern Africa with short growing seasons below 120 days and limited wet season precipitation of less than 500 mm are also vulnerable to precipitation changes while in most other part of East and Central Africa, in contrast, the effect of temperature increase on crops overbalances the precipitation effect and is most pronounced in a band stretching from Angola to Ethiopia in the 2060s. The results of this thesis confirm the findings from previous studies on the magnitude of climate change impact on crops in sub-Saharan Africa but beyond that helps to understand the drivers of these changes and the potential of certain management strategies for adaptation in more detail. Crop yield changes depend on the initial growing conditions, on the magnitude of climate change, and on the crop, cropping system and adaptive capacity of African farmers which is only now evident from this comprehensive study for sub-Saharan Africa. Furthermore this study improves the representation of tropical cropping systems in a global crop model and considers the major food crops cultivated in sub-Saharan Africa and climate change impacts throughout the continent.
The energy sector is both affected by climate change and a key sector for climate protection measures. Energy security is the backbone of our modern society and guarantees the functioning of most critical infrastructure. Thus, decision makers and energy suppliers of different countries should be familiar with the factors that increase or decrease the susceptibility of their electricity sector to climate change. Susceptibility means socioeconomic and structural characteristics of the electricity sector that affect the demand for and supply of electricity under climate change. Moreover, the relevant stakeholders are supposed to know whether the given national energy and climate targets are feasible and what needs to be done in order to meet these targets. In this regard, a focus should be on the residential building sector as it is one of the largest energy consumers and therefore emitters of anthropogenic CO 2 worldwide.
This dissertation addresses the first aspect, namely the susceptibility of the electricity sector, by developing a ranked index which allows for quantitative comparison of the electricity sector susceptibility of 21 European countries based on 14 influencing factors. Such a ranking has not been completed to date. We applied a sensitivity analysis to test the relative effect of each influencing factor on the susceptibility index ranking. We also discuss reasons for the ranking position and thus the susceptibility of selected countries. The second objective, namely the impact of climate change on the energy demand of buildings, is tackled by means of a new model with which the heating and cooling energy demand of residential buildings can be estimated. We exemplarily applied the model to Germany and the Netherlands. It considers projections of future changes in population, climate and the insulation standards of buildings, whereas most of the existing studies only take into account fewer than three different factors that influence the future energy demand of buildings. Furthermore, we developed a comprehensive retrofitting algorithm with which the total residential building stock can be modeled for the first time for each year in the past and future.
The study confirms that there is no correlation between the geographical location of a country and its position in the electricity sector susceptibility ranking. Moreover, we found no pronounced pattern of susceptibility influencing factors between countries that ranked higher or lower in the index. We illustrate that Luxembourg, Greece, Slovakia and Italy are the countries with the highest electricity sector susceptibility. The electricity sectors of Norway, the Czech Republic, Portugal and Denmark were found to be least susceptible to climate change. Knowledge about the most important factors for the poor and good ranking positions of these countries is crucial for finding adequate adaptation measures to reduce the susceptibility of the electricity sector. Therefore, these factors are described within this study.
We show that the heating energy demand of residential buildings will strongly decrease in both Germany and the Netherlands in the future. The analysis for the Netherlands focused on the regional level and a finer temporal resolution which revealed strong variations in the future heating energy demand changes by province and by month. In the German study, we additionally investigated the future cooling energy demand and could demonstrate that it will only slightly increase up to the middle of this century. Thus, increases in the cooling energy demand are not expected to offset reductions in heating energy demand. The main factor for substantial heating energy demand reductions is the retrofitting of buildings. We are the first to show that the given German and Dutch energy and climate targets in the building sector can only be met if the annual retrofitting rates are substantially increased. The current rate of only about 1 % of the total building stock per year is insufficient for reaching a nearly zero-energy demand of all residential buildings by the middle of this century. To reach this target, it would need to be at least tripled. To sum up, this thesis emphasizes that country-specific characteristics are decisive for the electricity sector susceptibility of European countries. It also shows for different scenarios how much energy is needed in the future to heat and cool residential buildings. With this information, existing climate mitigation and adaptation measures can be justified or new actions encouraged.
Die Anpassung von Sektoren an veränderte klimatische Bedingungen erfordert ein Verständnis von regionalen Vulnerabilitäten. Vulnerabilität ist als Funktion von Sensitivität und Exposition, welche potentielle Auswirkungen des Klimawandels darstellen, und der Anpassungsfähigkeit von Systemen definiert. Vulnerabilitätsstudien, die diese Komponenten quantifizieren, sind zu einem wichtigen Werkzeug in der Klimawissenschaft geworden. Allerdings besteht von der wissenschaftlichen Perspektive aus gesehen Uneinigkeit darüber, wie diese Definition in Studien umgesetzt werden soll. Ausdiesem Konflikt ergeben sich viele Herausforderungen, vor allem bezüglich der Quantifizierung und Aggregierung der einzelnen Komponenten und deren angemessenen Komplexitätsniveaus. Die vorliegende Dissertation hat daher zum Ziel die Anwendbarkeit des Vulnerabilitätskonzepts voranzubringen, indem es in eine systematische Struktur übersetzt wird. Dies beinhaltet alle Komponenten und schlägt für jede Klimaauswirkung (z.B. Sturzfluten) eine Beschreibung des vulnerablen Systems vor (z.B. Siedlungen), welches direkt mit einer bestimmten Richtung eines relevanten klimatischen Stimulus in Verbindung gebracht wird (z.B. stärkere Auswirkungen bei Zunahme der Starkregentage). Bezüglich der herausfordernden Prozedur der Aggregierung werden zwei alternative Methoden, die einen sektorübergreifenden Überblick ermöglichen, vorgestellt und deren Vor- und Nachteile diskutiert. Anschließend wird die entwickelte Struktur einer Vulnerabilitätsstudie mittels eines indikatorbasierten und deduktiven Ansatzes beispielhaft für Gemeinden in Nordrhein-Westfalen in Deutschland angewandt. Eine Übertragbarkeit auf andere Regionen ist dennoch möglich. Die Quantifizierung für die Gemeinden stützt sich dabei auf Informationen aus der Literatur. Da für viele Sektoren keine geeigneten Indikatoren vorhanden waren, werden in dieser Arbeit neue Indikatoren entwickelt und angewandt, beispielsweise für den Forst- oder Gesundheitssektor. Allerdings stellen fehlende empirische Daten bezüglich relevanter Schwellenwerte eine Lücke dar, beispielsweise welche Stärke von Klimaänderungen eine signifikante Auswirkung hervorruft. Dies führt dazu, dass die Studie nur relative Aussagen zum Grad der Vulnerabilität jeder Gemeinde im Vergleich zum Rest des Bundeslandes machen kann. Um diese Lücke zu füllen, wird für den Forstsektor beispielhaft die heutige und zukünftige Sturmwurfgefahr von Wäldern berechnet. Zu diesem Zweck werden die Eigenschaften der Wälder mit empirischen Schadensdaten eines vergangenen Sturmereignisses in Verbindung gebracht. Der sich daraus ergebende Sensitivitätswert wird anschließend mit den Windverhältnissen verknüpft. Sektorübergreifende Vulnerabilitätsstudien erfordern beträchtliche Ressourcen, was oft deren Anwendbarkeit erschwert. In einem nächsten Schritt wird daher das Potential einer Vereinfachung der Komplexität anhand zweier sektoraler Beispiele untersucht. Um das Auftreten von Waldbränden vorherzusagen, stehen zahlreiche meteorologische Indices zur Verfügung, welche eine Spannbreite unterschiedlicher Komplexitäten aufweisen. Bezüglich der Anzahl monatlicher Waldbrände weist die relative Luftfeuchtigkeit für die meisten deutschen Bundesländer eine bessere Vorhersagekraft als komplexere Indices auf. Dies ist er Fall, obgleich sie selbst als Eingangsvariable für die komplexeren Indices verwendet wird. Mit Hilfe dieses einzelnen meteorologischen Faktors kann also die Waldbrandgefahr in deutschen Region ausreichend genau ausgedrückt werden, was die Ressourceneffizienz von Studien erhöht. Die Methodenkomplexität wird auf ähnliche Weise hinsichtlich der Anwendung des ökohydrologischen Modells SWIM für die Region Brandenburg untersucht. Die interannuellen Bodenwasserwerte, welche durch dieses Modell simuliert werden, können nur unzureichend durch ein einfacheres statistisches Modell, welches auf denselben Eingangsdaten aufbaut, abgebildet werden. Innerhalb eines Zeithorizonts von Jahrzehnten, kann der statistische Ansatz jedoch das Bodenwasser zufriedenstellend abbilden und zeigt eine Dominanz der Bodeneigenschaft Feldkapazität. Dies deutet darauf hin, dass die Komplexität im Hinblick auf die Anzahl der Eingangsvariablen für langfristige Berechnungen reduziert werden kann. Allerdings sind die Aussagen durch fehlende beobachtete Bodenwasserwerte zur Validierung beschränkt. Die vorliegenden Studien zur Vulnerabilität und ihren Komponenten haben gezeigt, dass eine Anwendung noch immer wissenschaftlich herausfordernd ist. Folgt man der hier verwendeten Vulnerabilitätsdefinition, treten zahlreiche Probleme bei der Implementierung in regionalen Studien auf. Mit dieser Dissertation wurden Fortschritte bezüglich der aufgezeigten Lücken bisheriger Studien erzielt, indem eine systematische Struktur für die Beschreibung und Aggregierung von Vulnerabilitätskomponenten erarbeitet wurde. Hierfür wurden mehrere Ansätze diskutiert, die jedoch Vor- und Nachteile besitzen. Diese sollten vor der Anwendung von zukünftigen Studien daher ebenfalls sorgfältig abgewogen werden. Darüber hinaus hat sich gezeigt, dass ein Potential besteht einige Ansätze zu vereinfachen, jedoch sind hierfür weitere Untersuchungen nötig. Insgesamt konnte die Dissertation die Anwendung von Vulnerabilitätsstudien als Werkzeug zur Unterstützung von Anpassungsmaßnahmen stärken.
Many agriculture-based economies are increasingly under stress from climate change and socio-economic pressures. The excessive exploitation of natural resources still represents the standard procedure to achieve socio-economic development. In the area of the Moulouya river basin, Morocco, natural water availability represents a key resource for all economic activities. Agriculture represents the most important sector, and frequently occurring water deficits are aggravated by climate change. On the basis of historical trends taken from CRU TS 2.1, this paper analyses the impact of climate change on the per capita water availability under inclusion of population trends. The Climatic Water Balance (CWB) shows a significant decrease for the winter period, causing adverse effects for the main agricultural season. Further, moisture losses due to increasing evapotranspiration rates indicate problems for the annual water budget and groundwater recharge. The per capita blue water availability falls below a minimum threshold of 500 m(3) per year, denoting a high regional vulnerability to increasing water scarcity assuming a no-response scenario. Regional development focusing on the water-intense sectors of agriculture and tourism appears to be at risk. Institutional capacities and policies need to address the problem, and the prompt implementation of innovative water production and efficiency measures is recommended.
More than a billion people rely on water from rivers sourced in High Mountain Asia (HMA), a significant portion of which is derived from snow and glacier melt. Rural communities are heavily dependent on the consistency of runoff, and are highly vulnerable to shifts in their local environment brought on by climate change. Despite this dependence, the impacts of climate change in HMA remain poorly constrained due to poor process understanding, complex terrain, and insufficiently dense in-situ measurements.
HMA's glaciers contain more frozen water than any region outside of the poles. Their extensive retreat is a highly visible and much studied marker of regional and global climate change. However, in many catchments, snow and snowmelt represent a much larger fraction of the yearly water budget than glacial meltwaters. Despite their importance, climate-related changes in HMA's snow resources have not been well studied.
Changes in the volume and distribution of snowpack have complex and extensive impacts on both local and global climates. Eurasian snow cover has been shown to impact the strength and direction of the Indian Summer Monsoon -- which is responsible for much of the precipitation over the Indian Subcontinent -- by modulating earth-surface heating. Shifts in the timing of snowmelt have been shown to limit the productivity of major rangelands, reduce streamflow, modify sediment transport, and impact the spread of vector-borne diseases. However, a large-scale regional study of climate impacts on snow resources had yet to be undertaken.
Passive Microwave (PM) remote sensing is a well-established empirical method of studying snow resources over large areas. Since 1987, there have been consistent daily global PM measurements which can be used to derive an estimate of snow depth, and hence snow-water equivalent (SWE) -- the amount of water stored in snowpack. The SWE estimation algorithms were originally developed for flat and even terrain -- such as the Russian and Canadian Arctic -- and have rarely been used in complex terrain such as HMA.
This dissertation first examines factors present in HMA that could impact the reliability of SWE estimates. Forest cover, absolute snow depth, long-term average wind speeds, and hillslope angle were found to be the strongest controls on SWE measurement reliability. While forest density and snow depth are factors accounted for in modern SWE retrieval algorithms, wind speed and hillslope angle are not. Despite uncertainty in absolute SWE measurements and differences in the magnitude of SWE retrievals between sensors, single-instrument SWE time series were found to be internally consistent and suitable for trend analysis.
Building on this finding, this dissertation tracks changes in SWE across HMA using a statistical decomposition technique. An aggregate decrease in SWE was found (10.6 mm/yr), despite large spatial and seasonal heterogeneities. Winter SWE increased in almost half of HMA, despite general negative trends throughout the rest of the year. The elevation distribution of these negative trends indicates that while changes in SWE have likely impacted glaciers in the region, climate change impacts on these two pieces of the cryosphere are somewhat distinct.
Following the discussion of relative changes in SWE, this dissertation explores changes in the timing of the snowmelt season in HMA using a newly developed algorithm. The algorithm is shown to accurately track the onset and end of the snowmelt season (70% within 5 days of a control dataset, 89% within 10). Using a 29-year time series, changes in the onset, end, and duration of snowmelt are examined. While nearly the entirety of HMA has experienced an earlier end to the snowmelt season, large regions of HMA have seen a later start to the snowmelt season. Snowmelt periods have also decreased in almost all of HMA, indicating that the snowmelt season is generally shortening and ending earlier across HMA.
By examining shifts in both the spatio-temporal distribution of SWE and the timing of the snowmelt season across HMA, we provide a detailed accounting of changes in HMA's snow resources. The overall trend in HMA is towards less SWE storage and a shorter snowmelt season. However, long-term and regional trends conceal distinct seasonal, temporal, and spatial heterogeneity, indicating that changes in snow resources are strongly controlled by local climate and topography, and that inter-annual variability plays a significant role in HMA's snow regime.
Arctic and alpine treelines worldwide differ in their reactions to climate change. A northward advance of or densification within the treeline ecotone will likely influence climate-vegetation feedback mechanisms. In our study, which was conducted in the Taimyr Depression in the North Siberian Lowlands, w present a combined field-and model-based approach helping us to better understand the population processes involved in the responses of the whole treeline ecotone, spanning from closed forest to single-tree tundra, to climate warming. Using information on stand structure, tree age, and seed quality and quantity from seven sites, we investigate effects of intra-specific competition and seed availability on the specific impact of recent climate warming on larch stands. Field data show that tree density is highest in the forest-tundra, and average tree size decreases from closed forest to single-tree tundra. Age-structure analyses indicate that the trees in the closed forest and forest-tundra have been present for at least similar to 240 yr. At all sites except the most southerly ones, past establishment is positively correlated with regional temperature increase. In the single-tree tundra, however, a change in growth form from krummholz to erect trees, beginning similar to 130 yr ago, rather than establishment date has been recorded. Seed mass decreases from south to north, while seed quantity increases. Simulations with LAVESI (Larix Vegetation Simulator) further suggest that relative density changes strongly in response to a warming signal in the forest-tundra while intra-specific competition limits densification in the closed forest and seed limitation hinders densification in the single-tree tundra. We find striking differences in strength and timing of responses to recent climate warming. While forest-tundra stands recently densified, recruitment is almost non-existent at the southern and northern end of the ecotone due to autecological processes. Palaeo-treelines may therefore be inappropriate to infer past temperature changes at a fine scale. Moreover, a lagged treeline response to past warming will, via feedback mechanisms, influence climate change in the future.
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon-climate feedbacks.
We present a new set of global and local sea‐level projections at example tide gauge locations under the RCP2.6, RCP4.5, and RCP8.5 emissions scenarios. Compared to the CMIP5‐based sea‐level projections presented in IPCC AR5, we introduce a number of methodological innovations, including (i) more comprehensive treatment of uncertainties, (ii) direct traceability between global and local projections, and (iii) exploratory extended projections to 2300 based on emulation of individual CMIP5 models. Combining the projections with observed tide gauge records, we explore the contribution to total variance that arises from sea‐level variability, different emissions scenarios, and model uncertainty. For the period out to 2300 we further breakdown the model uncertainty by sea‐level component and consider the dependence on geographic location, time horizon, and emissions scenario. Our analysis highlights the importance of local variability for sea‐level change in the coming decades and the potential value of annual‐to‐decadal predictions of local sea‐level change. Projections to 2300 show a substantial degree of committed sea‐level rise under all emissions scenarios considered and highlight the reduced future risk associated with RCP2.6 and RCP4.5 compared to RCP8.5. Tide gauge locations can show large ( > 50%) departures from the global average, in some cases even reversing the sign of the change. While uncertainty in projections of the future Antarctic ice dynamic response tends to dominate post‐2100, we see substantial differences in the breakdown of model variance as a function of location, time scale, and emissions scenario.
We present a new set of global and local sea‐level projections at example tide gauge locations under the RCP2.6, RCP4.5, and RCP8.5 emissions scenarios. Compared to the CMIP5‐based sea‐level projections presented in IPCC AR5, we introduce a number of methodological innovations, including (i) more comprehensive treatment of uncertainties, (ii) direct traceability between global and local projections, and (iii) exploratory extended projections to 2300 based on emulation of individual CMIP5 models. Combining the projections with observed tide gauge records, we explore the contribution to total variance that arises from sea‐level variability, different emissions scenarios, and model uncertainty. For the period out to 2300 we further breakdown the model uncertainty by sea‐level component and consider the dependence on geographic location, time horizon, and emissions scenario. Our analysis highlights the importance of local variability for sea‐level change in the coming decades and the potential value of annual‐to‐decadal predictions of local sea‐level change. Projections to 2300 show a substantial degree of committed sea‐level rise under all emissions scenarios considered and highlight the reduced future risk associated with RCP2.6 and RCP4.5 compared to RCP8.5. Tide gauge locations can show large ( > 50%) departures from the global average, in some cases even reversing the sign of the change. While uncertainty in projections of the future Antarctic ice dynamic response tends to dominate post‐2100, we see substantial differences in the breakdown of model variance as a function of location, time scale, and emissions scenario.
In the last decade, the number and dimensions of catastrophic flooding events in the Niger River Basin (NRB) have markedly increased. Despite the devastating impact of the floods on the population and the mainly agriculturally based economy of the riverine nations, awareness of the hazards in policy and science is still low. The urgency of this topic and the existing research deficits are the motivation for the present dissertation.
The thesis is an initial detailed assessment of the increasing flood risk in the NRB. The research strategy is based on four questions regarding (1) features of the change in flood risk, (2) reasons for the change in the flood regime, (3) expected changes of the flood regime given climate and land use changes, and (4) recommendations from previous analysis for reducing the flood risk in the NRB.
The question examining the features of change in the flood regime is answered by means of statistical analysis. Trend, correlation, changepoint, and variance analyses show that, in addition to the factors exposure and vulnerability, the hazard itself has also increased significantly in the NRB, in accordance with the decadal climate pattern of West Africa. The northern arid and semi-arid parts of the NRB are those most affected by the changes.
As potential reasons for the increase in flood magnitudes, climate and land use changes are attributed by means of a hypothesis-testing framework. Two different approaches, based on either data analysis or simulation, lead to similar results, showing that the influence of climatic changes is generally larger compared to that of land use changes. Only in the dry areas of the NRB is the influence of land use changes comparable to that of climatic alterations.
Future changes of the flood regime are evaluated using modelling results. First ensembles of statistically and dynamically downscaled climate models based on different emission scenarios are analyzed. The models agree with a distinct increase in temperature. The precipitation signal, however, is not coherent. The climate scenarios are used to drive an eco-hydrological model. The influence of climatic changes on the flood regime is uncertain due to the unclear precipitation signal. Still, in general, higher flood peaks are expected. In a next step, effects of land use changes are integrated into the model. Different scenarios show that regreening might help to reduce flood peaks. In contrast, an expansion of agriculture might enhance the flood peaks in the NRB. Similarly to the analysis of observed changes in the flood regime, the impacts of climate- and land use changes for the future scenarios are also most severe in the dry areas of the NRB.
In order to answer the final research question, the results of the above analysis are integrated into a range of recommendations for science and policy on how to reduce flood risk in the NRB. The main recommendations include a stronger consideration of the enormous natural climate variability in the NRB and a focus on so called “no-regret” adaptation strategies which account for high uncertainty, as well as a stronger consideration of regional differences. Regarding the prevention and mitigation of catastrophic flooding, the most vulnerable and sensitive areas in the basin, the arid and semi-arid Sahelian and Sudano-Sahelian regions, should be prioritized. Eventually, an active, science-based and science-guided flood policy is recommended. The enormous population growth in the NRB in connection with the expected deterioration of environmental and climatic conditions is likely to enhance the region´s vulnerability to flooding. A smart and sustainable flood policy can help mitigate these negative impacts of flooding on the development of riverine societies in West Africa.
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.