@phdthesis{Duenkeloh2011,
  author    = {D{\"u}nkeloh, Armin},
  title     = {Water Balance Dynamics of Cyprus - Actual State and Impacts of Climate Change},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-75165},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {A completely revised and enhanced version of the water balance model MODBIL of the regional water balance dynamics of Cyprus was developed for this study. The model is based on a physical, process-oriented, spatially distributed concept and is applied for the calculation of all important water balance components of the island for the time period of 1961-2004. The calibrated results are statistically analysed and visualised for the whole island area, and evaluated with respect to the renewability of natural water resources. Climate variability and changes of the past decades are analysed with regard to their influence on water balances. A further part of the study focusses on the simulation of impacts of potential climate change. The water balances are simulated under changing climatic conditions on the base of theoretical precipitation, temperature and relative humidity changes and the revealed impacts on the water balances and renewable resources are discussed. Furthermore, a first principal water balance scenario is developed for the assessment of the regional hydrological changes expected for Cyprus by the end of the 21st century. The scenarios are based on recently calculated climate change assessments for this part of the Mediterranean, under an assumed further increase of greenhouse gasses in the atmosphere.},
  subject      = {Wasserhaushalt},
  language  = {en}
}
@phdthesis{Tran2011,
  author    = {Tran, Nam Binh},
  title     = {Climate change assessment in Southeast Asia and implications for agricultural production in Vietnam},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-64570},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {Seit vielen Jahren ist die Erforschung von Klimawandel und -schwankungen das zentrale Thema der Klimatologie. Besonderes deutlich wird dies anhand der IPCC-Berichte, ebenso wie der zahlreichen Einzelstudien zur Entwicklung des Klimas auf unterschiedlichsten raum-zeitlichen Skalen. Insbesondere seit den 1980er Jahren befassen sich zahlreiche Forschungsgruppen weltweit mit der systematischen Sammlung, Aufbereitung und auch Auswertung von Klimadaten. Diese Datengrundlage erlaubt Analysen zur Entwicklung der globalen Lufttemperatur, des Niederschlags und anderer Klimaelemente (Jones et al., 1986; Hansen und Lebedeff, 1987; Vinnikov et al., 1987, 1990). Das wichtigste {\"u}bergreifende Ergebnis dieser Untersuchungen ist die Feststellung einer globalen Erw{\"a}rmung w{\"a}hrend des 20. Jahrhunderts, die sich in den beiden letzten Jahrzehnten besonders intensivierte. Absch{\"a}tzungen {\"u}ber die Art und St{\"a}rke des Klimawandels auf gr{\"o}ßeren, planungsrelevanten Massst{\"a}ben sind jedoch nach wie vor mit großen Unsicherheiten verbunden. F{\"u}r eine detailliertere Erforschung der Auswirkungen der globalen Erw{\"a}rmung auf regionaler oder gar lokaler Ebene besteht daher noch großer Forschungsbedarf. In dieser Dissertation wird zu diesem Zweck ein statistischer Ansatz verfolgt. Dieser erlaubt die Identifikation systematischer Unterschiede zwischen den Auspr{\"a}gungen klimatologischer Feldgr{\"o}ßen (bodennahe Lufttemperatur und Niederschlag) wie sie von sogenannten General Circulation Models (GCMs) simuliert werden im Vergleich zu den betreffenden Parametern aus Beobachtungsdaten. Als Beobachtungsdaten werden die NCEP Reanalysen, die statistisch interpolierten Datens{\"a}tze der CRU sowie Stationsdaten aus Vietnam verwendet. Hierbei zeigt sich, dass die aktuellen Klimamodelle die r{\"a}umlichen Muster der betrachteten Variablen in befriedigender Weise reproduzieren. Die Analyse des regionalen Klimawandels in S{\"u}dost-Asien erfolgt durch die Auswertung von Klimamodellrechnungen. Diese wurden von verschiedenen GCMs durchgef{\"u}hrt, wobei unterschiedliche Annahmen {\"u}ber die zuk{\"u}nftigen Treibhausgasemissionen ber{\"u}cksichtigt wurden. Der Fokus dieser Dissertation ist die Analyse der projizierten zeitlichen Entwicklung von bodennaher Temperatur und Niederschlag im 21. Jahrhundert. Hierbei werden sowohl j{\"a}hrliche als auch saisonale Mittelwerte bzw. Summen ber{\"u}cksichtigt. Neben diesen rein physikalisch-klimatologischen Betrachtungen behandelt diese Dissertation auch einen angewandten Aspekt, n{\"a}mlich den Impakt des Klimawandels auf die Landwirtschaft, exemplarisch untersucht am Beispiel Vietnams. F{\"u}r die Absch{\"a}tzung der Vulnerabilit{\"a}t dieses essentiellen Wirtschaftsbereiches wird ein statistisches Modell entwickelt in das an klimatischen Parametern die bodennahe temperatur sowie der Niederschlag einfliessen. Diese Untersuchung leistet damit einen wichtigen Beitrag zum Wissenstand {\"u}ber die Auswirkungen des Klimawandels in den niederen Breiten. Die sozio-{\"o}konomische Entwicklung jedes Staates der Erde wird von den Folgen des Klimawandels beeinflusst, allerdings variiert der Grad der Beeintr{\"a}chtigung erheblich. Vermutlich werden Entwicklungsl{\"a}nder wie Vietnam die Auswirkungen des Klimawandels besonders stark zu sp{\"u}ren bekommen. Die Ursachen f{\"u}r diese hohe Vulnerabilit{\"a}t liegen unter anderem in der Wirtschaftsstruktur: der allgemein hohe Stellenwert nat{\"u}rlicher Ressourcen und eine geringe Diversit{\"a}t verringern hier die M{\"o}glichkeiten zur Adaption an die beobachteten und projizierten Ver{\"a}nderungen. Die vorliegende Dissertation gliedert sich wie folgt: In Kapitel 1 stellt eine allgemeine Einf{\"u}hrung zur Thematik dar. Die Begriffe Klima und Klimawandel sowie einige {\"u}bliche Modelle zum Klimawandel, verbunden mit einer Abw{\"a}gung der spezifischen Vor- und Nachteile, werden erl{\"a}utert. Kapitel 2 besch{\"a}ftigt sich mit der Methodik. Hier werden die r{\"a}umliche Interpolation sowie die angewendeten explorativen und inferentiellen statistischen Verfahren diskutiert. Die Kapitel 3 und 4 beschreiben die Datengrundlage und die betrachtete Region. Im Kapitel 5 werden die Untersuchungsergebnisse dargelegt. In Kapitel 6 erfolgt die Abschlussbetrachtung und ein Ausblick auf die Zukunft. Am Ende der Dissertation finden sich die verwendeten Quellen sowie ein Appendix mit landwirtschaftlichen Daten.},
  subject      = {Klima{\"a}nderung},
  language  = {en}
}
@phdthesis{Machwitz2010,
  author    = {Machwitz, Miriam},
  title     = {Eine raum-zeitliche Modellierung der Kohlenstoffbilanz mit Fernerkundungsdaten auf regionaler Ebene in Westafrika},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-55136},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2010},
  abstract  = {Der Klimawandel und insbesondere die globale Erw{\"a}rmung geh{\"o}ren aktuell zu den gr{\"o}ßten Herausforderungen an Politik und Wissenschaft. Steigende CO2-Emissionen sind hierbei maßgeblich f{\"u}r die Klimaerw{\"a}rmung verantwortlich. Ein regulierender Faktor beim CO2-Austausch mit der Atmosph{\"a}re ist die Vegetation, welche als CO2-Senke aber auch als CO2-Quelle fungieren kann. Diese Funktionen k{\"o}nnen durch Analysen der Landbedeckungs{\"a}nderung in Kombination mit Modellierungen der Kohlenstoffbilanz quantifiziert werden, was insbesondere von aktuellen und zuk{\"u}nftigen politischen Instrumenten wie CDM (Clean Development Mechanism) oder REDD (Reducing Emissions from Deforestation and Degradation) gefordert wird. Vor allem in Regionen mit starker Landbedeckungs{\"a}nderung und hoher Bev{\"o}lkerungsdichte sowie bei geringem Wissen {\"u}ber die Produktivit{\"a}t und CO2-Speicherpotentiale der Vegetation, bedarf es einer Erforschung und Quantifizierung der terrestrischen Kohlenstoffspeicher. Eine Region, f{\"u}r die dies in besonderem Maße zutrifft, ist Westafrika. J{\"u}ngste Studien haben gezeigt, dass sich einerseits die Folgen des Klimawandels und Umweltver{\"a}nderungen sehr stark in Westafrika auswirken werden und andererseits Bev{\"o}lkerungswachstum eine starke {\"A}nderung der Landbedeckung f{\"u}r die Nutzung als agrarische Fl{\"a}che bewirkt hat. Folglich sind in dieser Region die terrestrischen Kohlenstoffspeicher durch Ausdehnung der Landwirtschaft und Waldrodung besonders gef{\"a}hrdet. Große Fl{\"a}chen agieren anstelle ihrer urspr{\"u}nglichen Funktion als CO2-Senke bereits als CO2-Quelle. [...]},
  subject      = {Carbon dioxide capture and storage},
  language  = {de}
}
@phdthesis{Awoye2015,
  author    = {Awoye, Oy{\´e}monbad{\´e} Herv{\´e} Rodrigue},
  title     = {Implications of future climate change on agricultural production in tropical West Africa: evidence from the Republic of Benin},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-122887},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2015},
  abstract  = {Environmental interlinked problems such as human-induced land cover change, water scarcity, loss in soil fertility, and anthropogenic climate change are expected to affect the viability of agriculture and increase food insecurity in many developing countries. Climate change is certainly the most serious of these challenges for the twenty-first century. The poorest regions of the world - tropical West Africa included - are the most vulnerable due to their high dependence on climate and weather sensitive activities such as agriculture, and the widespread poverty that limits the institutional and economic capacities to adapt to the new stresses brought about by climate change. Climate change is already acting negatively on the poor smallholders of tropical West Africa whose livelihoods dependent mainly on rain-fed agriculture that remains the cornerstone of the economy in the region. Adaptation of the agricultural systems to climate change effects is, therefore, crucial to secure the livelihoods of these rural communities. Since information is a key for decision-making, it is important to provide well-founded information on the magnitude of the impacts in order to design appropriate and sustainable adaptation strategies. Considering the case of agricultural production in the Republic of Benin, this study aims at using large-scale climatic predictors to assess the potential impacts of past and future climate change on agricultural productivity at a country scale in West Africa. Climate signals from large-scale circulation were used because state-of-the art regional climate models (RCM) still do not perfectly resolve synoptic and mesoscale convective processes. It was hypothesised that in rain-fed systems with low investments in agricultural inputs, yield variations are widely governed by climatic factors. Starting with pineapple, a perennial fruit crops, the study further considered some annual crops such as cotton in the group of fibre crops, maize, sorghum and rice in the group of cereals, cowpeas and groundnuts belonging to the legume crops, and cassava and yams which are root and tuber crops. Thus the selected crops represented the three known groups of photosynthetic pathways (i.e. CAM, C3, and C4 plants). In the study, use was made of the historical agricultural yield statistics for the Republic of Benin, observed precipitation and mean near-surface air temperature data from the Climatic Research Unit (CRU TS 3.1) and the corresponding variables simulated by the regional climate model (RCM) REMO. REMO RCM was driven at its boundaries by the global climate model ECHAM 5. Simulations with different greenhouse gas concentrations (SRES-A1B and B1 emission scenarios) and transient land cover change scenarios for present-day and future conditions were considered. The CRU data were submitted to empirical orthogonal functions analysis over the north hemispheric part of Africa to obtain large-scale observed climate predictors and associated consistent variability modes. REMO RCM data for the same region were projected on the derived climate patterns to get simulated climate predictors. By means of cross-validated Model Output Statistics (MOS) approach combined with Bayesian model averaging (BMA) techniques, the observed climate predictors and the crop predictand were further on used to derive robust statistical relationships. The robust statistical crop models perform well with high goodness-of-fit coefficients (e.g. for all combined crop models: 0.49 ≤ R2 ≤ 0.99; 0.28 ≤ Brier-Skill-Score ≤ 0.90). Provided that REMO RCM captures the main features of the real African climate system and thus is able to reproduce its inter-annual variability, the time-independent statistical transfer functions were then used to translate future climate change signal from the simulated climate predictors into attainable crop yields/crop yield changes. The results confirm that precipitation and air temperature governed agricultural production in Benin in general, and particularly, pineapple yield variations are mainly influenced by temperature. Furthermore, the projected yield changes under future anthropogenic climate change during the first-half of the 21st century amount up to -12.5\% for both maize and groundnuts, and -11\%, -29\%, -33\% for pineapple, cassava, and cowpeas respectively. Meanwhile yield gain of up to +10\% for sorghum and yams, +24\% for cotton, and +39\% for rice are expected. Over the time period 2001 - 2050, on average the future yield changes range between -3\% and -13\% under REMO SRES-B1 (GHG)+LCC, -2\% and -11\% under REMO SRES-A1B (GHG only),and -3\% and -14\% under REMO SRES-A1B (GHG)+LCC for pineapple, maize, sorghum, groundnuts, cowpeas and cassava. In the meantime for yams, cotton and rice, the average yield gains lie in interval of about +2\% to +7\% under REMO SRES-B1 (GHG)+LCC, +0.1\% and +12\% under REMO SRES-A1B (GHG only), and +3\% and +10\% under REMO SRES-A1B (GHG)+LCC. For sorghum, although the long-term average future yield depicts a reduction there are tendencies towards increasing yields in the future. The results also reveal that the increases in mean air temperature more than the changes in precipitation patterns are responsible for the projected yield changes. As well the results suggest that the reductions in pineapple yields cannot be attributed to the land cover/land use changes across sub-Saharan Africa. The production of groundnuts and in particular yams and cotton will profit from the on-going land use/land cover changes while the other crops will face detrimental effects. Henceforth, policymakers should take effective measures to limit the on-going land degradation processes and all other anthropogenic actions responsible for temperature increase. Biotechnological improvement of the cultivated crop varieties towards development of set of seed varieties adapted to hotter and dry conditions should be included in the breeding pipeline programs. Amongst other solutions, application of appropriate climate-smart agricultural practices and conservation agriculture are also required to offset the negative impacts of climate change in agriculture.},
  subject      = {Benin},
  language  = {en}
}
@phdthesis{Vogt2014,
  author    = {Vogt, Gernot},
  title     = {Future changes and signal analyses of climate means and extremes in the Mediterranean Area deduced from a CMIP3 multi-model ensemble},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-117369},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {Considering its social, economic and natural conditions the Mediterranean Area is a highly vulnerable region by designated affections of climate change. Furthermore, its climatic characteristics are subordinated to high natural variability and are steered by various elements, leading to strong seasonal alterations. Additionally, General Circulation Models project compelling trends in specific climate variables within this region. These circumstances recommend this region for the scientific analyses conducted within this study. Based on the data of the CMIP3 database, the fundamental aim of this study is a detailed investigation of the total variability and the accompanied uncertainty, which superpose these trends, in the projections of temperature, precipitation and sea-level pressure by GCMs and their specific realizations. Special focus in the whole study is dedicated to the German model ECHAM5/MPI-OM. Following this ambition detailed trends and mean values are calculated and displayed for meaningful time periods and compared to reanalysis data of ERA40 and NCEP. To provide quantitative comparison the mentioned data are interpolated to a common 3x3° grid. The total amount of variability is separated in its contributors by the application of an Analysis of Variance (ANOVA). For individual GCMs and their ensemble-members this is done with the application of a 1-way ANOVA, separating a treatment common to all ensemble-members and variability perturbating the signal given by different initial conditions. With the 2-way ANOVA the projections of numerous models and their realizations are analysed and the total amount of variability is separated into a common treatment effect, a linear bias between the models, an interaction coefficient and the residuals. By doing this, the study is fulfilled in a very detailed approach, by considering yearly and seasonal variations in various reasonable time periods of 1961-2000 to match up with the reanalysis data, from 1961-2050 to provide a transient time period, 2001-2098 with exclusive regard on future simulations and 1901-2098 to comprise a time period of maximum length. The statistical analyses are conducted for regional-averages on the one hand and with respect to individual grid-cells on the other hand. For each of these applications the SRES scenarios of A1B, A2 and B1 are utilized. Furthermore, the spatial approach of the ANOVA is substituted by a temporal approach detecting the temporal development of individual variables. Additionally, an attempt is made to enlarge the signal by applying selected statistical methods. In the detailed investigation it becomes evident, that the different parameters (i.e. length of temporal period, geographic location, climate variable, season, scenarios, models, etc…) have compelling impact on the results, either in enforcing or weakening them by different combinations. This holds on the one hand for the means and trends but also on the other hand for the contributions of the variabilities affecting the uncertainty and the signal. While temperature is a climate variable showing strong signals across these parameters, for precipitation mainly the noise comes to the fore, while for sea-level pressure a more differentiated result manifests. In turn, this recommends the distinguished consideration of the individual parameters in climate impact studies and processes in model generation, as the affecting parameters also provide information about the linkage within the system. Finally, an investigation of extreme precipitation is conducted, implementing the variables of the total amount of heavy precipitation, the frequency of heavy-precipitation events, the percentage of this heavy precipitation to overall precipitation and the mean daily intensity from events of heavy precipitation. Each time heavy precipitation is defined to exceed the 95th percentile of overall precipitation. Consecutively mean values of these variables are displayed for ECHAM5/MPI-OM and the multi-model mean and climate sensitivities, by means of their difference between their average of the past period of 1981-2000 and the average of one of the future periods of 2046-2065 or 2081-2100. Following this investigation again an ANOVA is conducted providing a quantitative measurement of the severity of change of trends in heavy precipitation across several GCMs. Besides it is a difficult task to account for extreme precipitation by GCMs, it is noteworthy that the investigated models differ highly in their projections, resulting partially in a more smoothed and meaningful multi-model mean. Seasonal alterations of the strength of this behaviour are quantitatively supported by the ANOVA.},
  subject      = {Klimaschwankung},
  language  = {en}
}
@phdthesis{Mutz2013,
  author    = {Mutz, Sebastian},
  title     = {Dynamic Statistical Modelling of Climate-Related Mass Balance Changes in Norway},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-114799},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {The glaciers in Norway exert a strong influence on Norwegian economy and society. Unlike many glaciers elsewhere and despite ongoing climate change and warming, many of them showed renewed advances and positive net mass changes in the 1980's and 1990's, followed by rapid retreats and mass losses since 2000. This difference in behaviour may be attributed to differences and shifts in the glaciological regime - the differences in the magnitude of impacts of climatic and non-climatic geographical factors on the glacier mass. This study investigates the influence of various atmospheric variables on mass balance changes of a selection of glaciers in Norway by means of Pearson correlation analyses and cross-validated stepwise multiple regression analyses. The analyses are carried out for three time periods (1949-2008, 1949-1988, 1989-2008) separately in order to take into consideration the possible shift in the glaciological regime in the 1980's. The atmospheric variables are constructed from ERA40 and NCEP/NCAR re-analysis datasets and include regional means of seasonal air temperature and precipitation rates and atmospheric circulation indices. The multiple regression models trained in these time periods are then applied to predictors reconstructed from the CMIP3 climate model dataset to generate an estimate for mass changes from the year 1950 to 2100. The temporal overlap of estimates and observations is used for calibration. Finally, observed atmospheric states in seasons that are characterised by a particularly positive or negative mass balance are categorised into time periods of modelled climate by the application of a Bayesian classification procedure. The strongest influence on winter mass balance is exerted by different indices of the North Atlantic Oscillation (NAO), Northern Annular Mode (NAM) and precipitation. The correlation coefficients and explained variances determined from the multiple regression analyses reveal an East-West gradient, suggesting a weaker influence of the NAO and NAM on glaciers underlying a more continental regime. The highest correlation coefficients and explained variances were obtained for the 1989-2008 time period, which might be due to a strong and predominantly positive phase of the NAO. Multi-model ensemble means of the estimates show a mass loss for all three eastern glaciers, while the estimates for the more maritime glaciers are ambivalent. In general, the estimates show a greater sensitivity to the training time period than to the greenhouse gas emission scenarios according to which the climates were simulated. The average net mass change by the end of 2100 is negative for all glaciers except for the northern Engabreen. For many glaciers, the Bayesian classification of observed atmospheric states into time periods of modelled climate reveals a decrease in probability of atmospheric states favouring extremes in winter, and an increase in probability of atmospheric states favouring extreme mass loss in summer for the distant future (2071-2100). This pattern of probabilities for the ablation season is most pronounced for glaciers underlying a continental and intermediate regime.},
  subject      = {Norwegen},
  language  = {en}
}
@phdthesis{Sieber2012,
  author    = {Sieber, Jeannette},
  title     = {Impacts of Extreme Hydro-Meteorological Events on Electricity Generation and Possible Adaptation Measures - A GIS-based Approach for Corporate Risk Management and Enhanced Climate Mitigation Concepts in Germany},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-79000},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {This thesis on the "Impacts of extreme hydro-meteorological events on electricity generation and possible adaptation measures - a GIS-based approach for corporate risk management and enhanced climate mitigation concepts in Germany" presents an identification of hydro-meteorological extreme events in Germany and their effects on electricity generating units, i.e. on conventional thermal and nuclear power plants as well as on installations of the renewable energies of hydropower, wind energy and photovoltaic installations. In addition, adaptation measures and strategies are named that help power plant operators to prepare for a changing climate. Due to the different requirements of large facility operators and local planners and owners of renewable energies, the work contains the two approaches of corporate risk management and climate mitigation concepts. A changing climate not only consists of a shift in mean values of weather parameters such as global and regional air temperature and precipitation, but may also result in more frequent and more severe single events such as extreme precipitation, tornadoes and thunderstorms. In two case studies, these findings are implemented into an adjusted general risk management structure. This is enhanced by the use of Geographical Information Systems (GIS) to accomplish a localisation of events and infrastructure. The first example gives insight into the consequences of ice throw from wind turbines and how climate mitigation concepts can act as a framework for an adapted, sustainable energy planning. The second example on the other hand highlights a GIS-based flood risk management for thermal power plants and the benefits of an adjusted corporate risk management cycle. The described approach leads to an integrated management of extreme hydro-meteorological events at power plant site respectively district level by combining two cycles of site-related and local planning in addition to GIS-based analyses. This is demonstrated as an example by the comparison of two districts in Germany. The practical outcome is a comprehensive support for decision-making processes.},
  subject      = {Deutschland},
  language  = {en}
}
@phdthesis{Pollinger2013,
  author    = {Pollinger, Felix},
  title     = {Bewertung und Auswirkungen der Simulationsg{\"u}te f{\"u}hrender Klimamoden in einem Multi-Modell Ensemble},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-97982},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Der rezente und zuk{\"u}nftige Anstieg der atmosph{\"a}rischen Treibhausgaskonzentration bedeutet f{\"u}r das terrestrische Klimasystem einen grundlegenden Wandel, der f{\"u}r die globale Gesellschaft schwer zu bew{\"a}ltigende Aufgaben und Herausforderungen bereit h{\"a}lt. Eine effektive, r{\"u}hzeitige Anpassung an diesen Klimawandel profitiert dabei enorm von m{\"o}glichst genauen Absch{\"a}tzungen k{\"u}nftiger Klima{\"a}nderungen. Das geeignete Werkzeug hierf{\"u}r sind Gekoppelte Atmosph{\"a}re Ozean Modelle (AOGCMs). F{\"u}r solche Fragestellungen m{\"u}ssen allerdings weitreichende Annahmen {\"u}ber die zuk{\"u}nftigen klimarelevanten Randbedingungen getroffen werden. Individuelle Fehler dieser Klimamodelle, die aus der nicht perfekten Abbildung der realen Verh{\"a}ltnisse und Prozesse resultieren, erh{\"o}hen die Unsicherheit langfristiger Klimaprojektionen. So unterscheiden sich die Aussagen verschiedener AOGCMs im Hinblick auf den zuk{\"u}nftigen Klimawandel insbesondere bei regionaler Betrachtung, deutlich. Als Absicherung gegen Modellfehler werden {\"u}blicherweise die Ergebnisse mehrerer AOGCMs, eines Ensembles an Modellen, kombiniert. Um die Absch{\"a}tzung des Klimawandels zu pr{\"a}zisieren, wird in der vorliegenden Arbeit der Versuch unternommen, eine Bewertung der Modellperformance der 24 AOGCMs, die an der dritten Phase des Vergleichsprojekts f{\"u}r gekoppelte Modelle (CMIP3) teilgenommen haben, zu erstellen. Auf dieser Basis wird dann eine nummerische Gewichtung f{\"u}r die Kombination des Ensembles erstellt. Zun{\"a}chst werden die von den AOGCMs simulierten Klimatologien f{\"u}r einige grundlegende Klimaelemente mit den betreffenden klimatologien verschiedener Beobachtungsdatens{\"a}tze quantitativ abgeglichen. Ein wichtiger methodischer Aspekt hierbei ist, dass auch die Unsicherheit der Beobachtungen, konkret Unterschiede zwischen verschiedenen Datens{\"a}tzen, ber{\"u}cksichtigt werden. So zeigt sich, dass die Aussagen, die aus solchen Ans{\"a}tzen resultieren, von zu vielen Unsicherheiten in den Referenzdaten beeintr{\"a}chtigt werden, um generelle Aussagen zur Qualit{\"a}t von AOGCMs zu treffen. Die Nutzung der K{\"o}ppen-Geiger Klassifikation offenbart jedoch, dass die prinzipielle Verteilung der bekannten Klimatypen im kompletten CMIP3 in vergleichbar guter Qualit{\"a}t reproduziert wird. Als Bewertungskriterium wird daher hier die F{\"a}higkeit der AOGCMs die großskalige nat{\"u}rliche Klimavariabilit{\"a}t, konkret die hochkomplexe gekoppelte El Ni{\~n}o-Southern Oscillation (ENSO), realistisch abzubilden herangezogen. Es kann anhand verschiedener Aspekte des ENSO-Ph{\"a}nomens gezeigt werden, dass nicht alle AOGCMs hierzu mit gleicher Realit{\"a}tsn{\"a}he in der Lage sind. Dies steht im Gegensatz zu den dominierenden Klimamoden der Außertropen, die modell{\"u}bergreifend {\"u}berzeugend repr{\"a}sentiert werden. Die wichtigsten Moden werden, in globaler Betrachtung, in verschiedenen Beobachtungsdaten {\"u}ber einen neuen Ansatz identifiziert. So k{\"o}nnen f{\"u}r einige bekannte Zirkulationsmuster neue Indexdefinitionen gewonnen werden, die sich sowohl als {\"a}quivalent zu den Standardverfahren erweisen und im Vergleich zu diesen zudem eine deutliche Reduzierung des Rechenaufwandes bedeuten. Andere bekannte Moden werden dagegen als weniger bedeutsame, regionale Zirkulationsmuster eingestuft. Die hier vorgestellte Methode zur Beurteilung der Simulation von ENSO ist in guter {\"U}bereinstimmung mit anderen Ans{\"a}tzen, ebenso die daraus folgende Bewertung der gesamten Performance der AOGCMs. Das Spektrum des Southern Oscillation-Index (SOI) stellt somit eine aussagekr{\"a}ftige Kenngr{\"o}ße der Modellqualit{\"a}t dar. Die Unterschiede in der F{\"a}higkeit, das ENSO-System abzubilden, erweisen sich als signifikante Unsicherheitsquelle im Hinblick auf die zuk{\"u}nftige Entwicklung einiger fundamentaler und bedeutsamer Klimagr{\"o}ßen, konkret der globalen Mitteltemperatur, des SOIs selbst, sowie des indischen Monsuns. Ebenso zeigen sich signifikante Unterschiede f{\"u}r regionale Klima{\"a}nderungen zwischen zwei Teilensembles des CMIP3, die auf Grundlage der entwickelten Bewertungsfunktion eingeteilt werden. Jedoch sind diese Effekte im Allgemeinen nicht mit den Auswirkungen der anthropogenen Klima{\"a}nderungssignale im Multi-Modell Ensemble vergleichbar, die f{\"u}r die meisten Klimagr{\"o}ßen in einem robusten multivariaten Ansatz detektiert und quantifiziert werden k{\"o}nnen. Entsprechend sind die effektiven Klima{\"a}nderungen, die sich bei der Kombination aller Simulationen als grundlegende Aussage des CMIP3 unter den speziellen Randbedingungen ergeben nahezu unabh{\"a}ngig davon, ob alle L{\"a}ufe mit dem gleichen Einfluss ber{\"u}cksichtigt werden, oder ob die erstellte nummerische Gewichtung verwendet wird. Als eine wesentliche Begr{\"u}ndung hierf{\"u}r kann die Spannbreite der Entwicklung des ENSO-Systems identifiziert werden. Dies bedeutet gr{\"o}ßere Schwankungen in den Ergebnissen der Modelle mit funktionierendem ENSO, was den Stellenwert der nat{\"u}rlichen Variabilit{\"a}t als Unsicherheitsquelle in Fragen des Klimawandels unterstreicht. Sowohl bei Betrachtung der Teilensembles als auch der Gewichtung wirken sich dadurch gegenl{\"a}ufige Trends im SOI ausgleichend auf die Entwicklung anderer Klimagr{\"o}ßen aus, was insbesondere bei letzterem Vorgehen signifikante mittlere Effekte des Ansatzes, verglichen mit der Verwendung des {\"u}blichen arithmetischen Multi-Modell Mittelwert, verhindert.},
  subject      = {Modell},
  language  = {de}
}
@phdthesis{Roedder2014,
  author    = {R{\"o}dder, Tobias},
  title     = {Spatio-temporal assessment of dynamics in discontinuous mountain permafrost - Investigation of small-scale influences on the ground thermal regime and active layer processes during snow melt},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-90629},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {The discontinuous mountain permafrost zone is characterized by its heterogeneous distribution of frozen ground and a small-scale variability of the ground thermal regime. Large parts of these areas are covered by glacial till and sediments that were exposed after the recession of the glaciers since the 19th century. As response to changed climatic conditions permafrost-affected areas will lose their ability as sediment storage and on the contrary, they will act as source areas for unconsolidated debris. Along with modified precipitation patterns the degradation of the discontinuous mountain permafrost zone will (temporarily) increase its predisposition for mass movement processes and thus has to be monitored in a differentiated way. Therefore, the spatio-temporal dynamics of frozen ground are assessed in this study based on results obtained in three glacier forefields in the Engadin (Swiss Alps) and at the Zugspitze (German Alps). Sophisticated techniques are required to uncover structural differences in the subsurface. Thus, the applicability of advanced geophysical methods is tested for alpine environments and proved by the good 3D-delineation of a permafrost body and by the detection of detailed processes in the active layer during snow melt. Electrical resistivity tomography (ERT) approaches (quasi-3D, daily monitoring) reveal their capabilities to detect subsurface resistivity changes both, in space and time. Processes and changes in regard to liquid water content and ice content are observed to exist at short distances even though the active layer is not subject to a considerable thickening over the past 7 years. The stability of the active layer is verified by borehole temperature data. No synchronous trend is recognized in permafrost temperatures and together with multi-annual electrical resistivity data they indicate degradation and aggradation processes to occur at the same time. Different heat transfer mechanisms, especially during winter, are recognized by means of temperature sensors above, at, and beneath the surface. Based on surface and borehole temperature data the snow cover is assessed as the major controlling factor for the thermal regime on a local scale. Beyond that, the debris size of the substrate, which modifies the snow cover and regulates air exchange processes above the ground, plays a crucial role as an additional buffer layer. A fundamental control over the stability of local permafrost patches is attributed to the ice-rich transient layer at the base of the active layer. The refreezing of melt water in spring is illustrated with diurnal ERT monitoring data from glacier forefield Murt{\`e}l. Based on these ERT and borehole temperature data a conceptual model of active layer processes between autumn and spring is developed. The latent heat that is inherent in the transient layer protects the permafrost beneath from additional energy input from the surface as long as the refreezing of melt water in spring prevails and sufficient ice is build up each spring. Permafrost sites without a transient layer show considerably higher temperatures at their table and are more prone to degradation in the years and decades ahead. As main investigation area a glacier forefield beneath the summits of Piz Murt{\`e}l and Piz Corvatsch in the Swiss Engadin was chosen. It is located west of the well-known rock glacier Murt{\`e}l. Here, a permafrost body inside and adjacent to the lateral moraine was investigated and could be delineated very well. In the surrounding glacier forefield no further indications of permafrost occurrence could be made. Geophysical data and temperature values from the surface and from a permafrost borehole were compared with long-term data from proximate glacier forefield Muragl (Engadin). Results from both sites show a considerable stability of the active layer depth in summer while at the same time geophysical data demonstrate annual changes in the amount of liquid water content and ice content in the course of years. A third investigation area is located in the German Alps. The Zugspitzplatt is a high mountain valley with considerably more precipitation and thicker snow cover compared to both Swiss sites. In close proximity to the present glacier and at a large talus slope beneath the summit crest ground ice could be observed. The high subsurface resistivity values and comparable data from existing studies at the Zugspitze may indicate the presence of sedimentary ice in the subsurface of the karstified Zugspitzplatt. Based on these complementary data from geophysical and temperature measurements as well as geomorphological field mapping the development of permafrost in glacier forefields under climate change conditions is analyzed with cooperation partners from the SPCC project. Ground temperature simulations forced with long-term climatological data are modeled to assess future permafrost development in glacier forefield Murt{\`e}l. Results suggest that permafrost is stable as long as the ice-rich layer between the active layer and the permafrost table exists. After a tipping point is reached, the disintegration of frozen ground starts to proceed rapidly from the top.},
  subject      = {Engadin},
  language  = {en}
}
@phdthesis{Baumann2009,
  author    = {Baumann, Sabine Christine},
  title     = {Mapping, analysis, and interpretation of the glacier inventory data from Jotunheimen, South Norway, since the maximum of the 'Little Ice Age'},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-46320},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2009},
  abstract  = {Glacier outlines during the 'Little Ice Age' maximum in Jotunheimen were mapped by using remote sensing techniques (vertical aerial photos and satellite imagery), glacier outlines from the 1980s and 2003, a digital terrain model (DTM), geomorphological maps of individual glaciers, and field-GPS measurements. The related inventory data (surface area, minimum and maximum altitude) and several other variables (e.g. slope, range) were calculated automatically by using a geographical information system. The length of the glacier flowline was mapped manually based on the glacier outlines at the maximum of the 'Little Ice Age' and the DTM. The glacier data during the maximum of the 'Little Ice Age' were compared with the Norwegian glacier inventory of 2003. Based on the glacier inventories during the maximum of the 'Little Ice Age', the 1980s and 2003, a simple parameterization after HAEBERLI \& HOELZLE (1995) was performed to estimate unmeasured glacier variables, as e.g. surface velocity or mean net mass balance. Input data were composed of surface glacier area, minimum and maximum elevation, and glacier length. The results of the parameterization were compared with the results of previous parameterizations in the European Alps and the Southern Alps of New Zealand (HAEBERLI \& HOELZLE 1995; HOELZLE et al. 2007). A relationship between these results of the inventories and of the parameterization and climate and climate changes was made.},
  subject      = {Gletscher},
  language  = {en}
}