@phdthesis{Dahlke2020,
  author    = {Dahlke, Sandro},
  title     = {Rapid climate changes in the arctic region of Svalbard},
  doi       = {10.25932/publishup-44554},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-445542},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xv, 123},
  year      = {2020},
  abstract  = {Over the last decades, the Arctic regions of the earth have warmed at a rate 2-3 times faster than the global average- a phenomenon called Arctic Amplification. A complex, non-linear interplay of physical processes and unique pecularities in the Arctic climate system is responsible for this, but the relative role of individual processes remains to be debated. This thesis focuses on the climate change and related processes on Svalbard, an archipelago in the North Atlantic sector of the Arctic, which is shown to be a "hotspot" for the amplified recent warming during winter. In this highly dynamical region, both oceanic and atmospheric large-scale transports of heat and moisture interfere with spatially inhomogenous surface conditions, and the corresponding energy exchange strongly shapes the atmospheric boundary layer. In the first part, Pan-Svalbard gradients in the surface air temperature (SAT) and sea ice extent (SIE) in the fjords are quantified and characterized. This analysis is based on observational data from meteorological stations, operational sea ice charts, and hydrographic observations from the adjacent ocean, which cover the 1980-2016 period. It is revealed that typical estimates of SIE during late winter range from 40-50\% (80-90\%) in the western (eastern) parts of Svalbard. However, strong SAT warming during winter of the order of 2-3K per decade dictates excessive ice loss, leaving fjords in the western parts essentially ice-free in recent winters. It is further demostrated that warm water currents on the west coast of Svalbard, as well as meridional winds contribute to regional differences in the SIE evolution. In particular, the proximity to warm water masses of the West Spitsbergen Current can explain 20-37\% of SIE variability in fjords on west Svalbard, while meridional winds and associated ice drift may regionally explain 20-50\% of SIE variability in the north and northeast. Strong SAT warming has overruled these impacts in recent years, though. In the next part of the analysis, the contribution of large-scale atmospheric circulation changes to the Svalbard temperature development over the last 20 years is investigated. A study employing kinematic air-back trajectories for Ny-{\AA}lesund reveals a shift in the source regions of lower-troposheric air over time for both the winter and the summer season. In winter, air in the recent decade is more often of lower-latitude Atlantic origin, and less frequent of Arctic origin. This affects heat- and moisture advection towards Svalbard, potentially manipulating clouds and longwave downward radiation in that region. A closer investigation indicates that this shift during winter is associated with a strengthened Ural blocking high and Icelandic low, and contributes about 25\% to the observed winter warming on Svalbard over the last 20 years. Conversely, circulation changes during summer include a strengthened Greenland blocking high which leads to more frequent cold air advection from the central Arctic towards Svalbard, and less frequent air mass origins in the lower latitudes of the North Atlantic. Hence, circulation changes during winter are shown to have an amplifying effect on the recent warming on Svalbard, while summer circulation changes tend to mask warming. An observational case study using upper air soundings from the AWIPEV research station in Ny-{\AA}lesund during May-June 2017 underlines that such circulation changes during summer are associated with tropospheric anomalies in temperature, humidity and boundary layer height. In the last part of the analysis, the regional representativeness of the above described changes around Svalbard for the broader Arctic is investigated. Therefore, the terms in the diagnostic temperature equation in the Arctic-wide lower troposphere are examined for the Era-Interim atmospheric reanalysis product. Significant positive trends in diabatic heating rates, consistent with latent heat transfer to the atmosphere over regions of increasing ice melt, are found for all seasons over the Barents/Kara Seas, and in individual months in the vicinity of Svalbard. The above introduced warm (cold) advection trends during winter (summer) on Svalbard are successfully reproduced. Regarding winter, they are regionally confined to the Barents Sea and Fram Strait, between 70°-80°N, resembling a unique feature in the whole Arctic. Summer cold advection trends are confined to the area between eastern Greenland and Franz Josef Land, enclosing Svalbard.},
  language  = {en}
}
@phdthesis{Knopf2006,
  author    = {Knopf, Brigitte},
  title     = {On intrinsic uncertainties in earth system modelling},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-10949},
  school      = {Universit{\"a}t Potsdam},
  year      = {2006},
  abstract  = {Uncertainties are pervasive in the Earth System modelling. This is not just due to a lack of knowledge about physical processes but has its seeds in intrinsic, i.e. inevitable and irreducible, uncertainties concerning the process of modelling as well. Therefore, it is indispensable to quantify uncertainty in order to determine, which are robust results under this inherent uncertainty. The central goal of this thesis is to explore how uncertainties map on the properties of interest such as phase space topology and qualitative dynamics of the system. We will address several types of uncertainty and apply methods of dynamical systems theory on a trendsetting field of climate research, i.e. the Indian monsoon. For the systematic analysis concerning the different facets of uncertainty, a box model of the Indian monsoon is investigated, which shows a saddle node bifurcation against those parameters that influence the heat budget of the system and that goes along with a regime shift from a wet to a dry summer monsoon. As some of these parameters are crucially influenced by anthropogenic perturbations, the question is whether the occurrence of this bifurcation is robust against uncertainties in parameters and in the number of considered processes and secondly, whether the bifurcation can be reached under climate change. Results indicate, for example, the robustness of the bifurcation point against all considered parameter uncertainties. The possibility of reaching the critical point under climate change seems rather improbable. A novel method is applied for the analysis of the occurrence and the position of the bifurcation point in the monsoon model against parameter uncertainties. This method combines two standard approaches: a bifurcation analysis with multi-parameter ensemble simulations. As a model-independent and therefore universal procedure, this method allows investigating the uncertainty referring to a bifurcation in a high dimensional parameter space in many other models. With the monsoon model the uncertainty about the external influence of El Ni{\~n}o / Southern Oscillation (ENSO) is determined. There is evidence that ENSO influences the variability of the Indian monsoon, but the underlying physical mechanism is discussed controversially. As a contribution to the debate three different hypotheses are tested of how ENSO and the Indian summer monsoon are linked. In this thesis the coupling through the trade winds is identified as key in linking these two key climate constituents. On the basis of this physical mechanism the observed monsoon rainfall data can be reproduced to a great extent. Moreover, this mechanism can be identified in two general circulation models (GCMs) for the present day situation and for future projections under climate change. Furthermore, uncertainties in the process of coupling models are investigated, where the focus is on a comparison of forced dynamics as opposed to fully coupled dynamics. The former describes a particular type of coupling, where the dynamics from one sub-module is substituted by data. Intrinsic uncertainties and constraints are identified that prevent the consistency of a forced model with its fully coupled counterpart. Qualitative discrepancies between the two modelling approaches are highlighted, which lead to an overestimation of predictability and produce artificial predictability in the forced system. The results suggest that bistability and intermittent predictability, when found in a forced model set-up, should always be cross-validated with alternative coupling designs before being taken for granted. All in this, this thesis contributes to the fundamental issue of dealing with uncertainties the climate modelling community is confronted with. Although some uncertainties allow for including them in the interpretation of the model results, intrinsic uncertainties could be identified, which are inevitable within a certain modelling paradigm and are provoked by the specific modelling approach.},
  subject      = {Unsicherheit},
  language  = {en}
}
@phdthesis{Maraun2006,
  author    = {Maraun, Douglas},
  title     = {What can we learn from climate data? : Methods for fluctuation, time/scale and phase analysis},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-9047},
  school      = {Universit{\"a}t Potsdam},
  year      = {2006},
  abstract  = {Since Galileo Galilei invented the first thermometer, researchers have tried to understand the complex dynamics of ocean and atmosphere by means of scientific methods. They observe nature and formulate theories about the climate system. Since some decades powerful computers are capable to simulate the past and future evolution of climate. Time series analysis tries to link the observed data to the computer models: Using statistical methods, one estimates characteristic properties of the underlying climatological processes that in turn can enter the models. The quality of an estimation is evaluated by means of error bars and significance testing. On the one hand, such a test should be capable to detect interesting features, i.e. be sensitive. On the other hand, it should be robust and sort out false positive results, i.e. be specific. This thesis mainly aims to contribute to methodological questions of time series analysis with a focus on sensitivity and specificity and to apply the investigated methods to recent climatological problems. First, the inference of long-range correlations by means of Detrended Fluctuation Analysis (DFA) is studied. It is argued that power-law scaling of the fluctuation function and thus long-memory may not be assumed a priori but have to be established. This requires to investigate the local slopes of the fluctuation function. The variability characteristic for stochastic processes is accounted for by calculating empirical confidence regions. The comparison of a long-memory with a short-memory model shows that the inference of long-range correlations from a finite amount of data by means of DFA is not specific. When aiming to infer short memory by means of DFA, a local slope larger than \$\alpha=0.5\$ for large scales does not necessarily imply long-memory. Also, a finite scaling of the autocorrelation function is shifted to larger scales in the fluctuation function. It turns out that long-range correlations cannot be concluded unambiguously from the DFA results for the Prague temperature data set. In the second part of the thesis, an equivalence class of nonstationary Gaussian stochastic processes is defined in the wavelet domain. These processes are characterized by means of wavelet multipliers and exhibit well defined time dependent spectral properties; they allow one to generate realizations of any nonstationary Gaussian process. The dependency of the realizations on the wavelets used for the generation is studied, bias and variance of the wavelet sample spectrum are calculated. To overcome the difficulties of multiple testing, an areawise significance test is developed and compared to the conventional pointwise test in terms of sensitivity and specificity. Applications to Climatological and Hydrological questions are presented. The thesis at hand mainly aims to contribute to methodological questions of time series analysis and to apply the investigated methods to recent climatological problems. In the last part, the coupling between El Nino/Southern Oscillation (ENSO) and the Indian Monsoon on inter-annual time scales is studied by means of Hilbert transformation and a curvature defined phase. This method allows one to investigate the relation of two oscillating systems with respect to their phases, independently of their amplitudes. The performance of the technique is evaluated using a toy model. From the data, distinct epochs are identified, especially two intervals of phase coherence, 1886-1908 and 1964-1980, confirming earlier findings from a new point of view. A significance test of high specificity corroborates these results. Also so far unknown periods of coupling invisible to linear methods are detected. These findings suggest that the decreasing correlation during the last decades might be partly inherent to the ENSO/Monsoon system. Finally, a possible interpretation of how volcanic radiative forcing could cause the coupling is outlined.},
  subject      = {Spektralanalyse <Stochastik>},
  language  = {en}
}