@phdthesis{Mueller2022, author = {M{\"u}ller, Daniela}, title = {Abrupt climate changes and extreme events in two different varved lake sediment records}, doi = {10.25932/publishup-55833}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-558331}, school = {Universit{\"a}t Potsdam}, pages = {XVIII, 209}, year = {2022}, abstract = {Different lake systems might reflect different climate elements of climate changes, while the responses of lake systems are also divers, and are not completely understood so far. Therefore, a comparison of lakes in different climate zones, during the high-amplitude and abrupt climate fluctuations of the Last Glacial to Holocene transition provides an exceptional opportunity to investigate distinct natural lake system responses to different abrupt climate changes. The aim of this doctoral thesis was to reconstruct climatic and environmental fluctuations down to (sub-) annual resolution from two different lake systems during the Last Glacial-Interglacial transition (~17 and 11 ka). Lake Gościąż, situated in the temperate central Poland, developed in the Aller{\o}d after recession of the Last Glacial ice sheets. The Dead Sea is located in the Levant (eastern Mediterranean) within a steep gradient from sub-humid to hyper-arid climate, and formed in the mid-Miocene. Despite their differences in sedimentation processes, both lakes form annual laminations (varves), which are crucial for studies of abrupt climate fluctuations. This doctoral thesis was carried out within the DFG project PALEX-II (Paleohydrology and Extreme Floods from the Dead Sea ICDP Core) that investigates extreme hydro-meteorological events in the ICDP core in relation to climate changes, and ICLEA (Virtual Institute of Integrated Climate and Landscape Evolution Analyses) that intends to better the understanding of climate dynamics and landscape evolutions in north-central Europe since the Last Glacial. Further, it contributes to the Helmholtz Climate Initiative REKLIM (Regional Climate Change and Humans) Research Theme 3 "Extreme events across temporal and spatial scales" that investigates extreme events using climate data, paleo-records and model-based simulations. The three main aims were to (1) establish robust chronologies of the lakes, (2) investigate how major and abrupt climate changes affect the lake systems, and (3) to compare the responses of the two varved lakes to these hemispheric-scale climate changes. Robust chronologies are a prerequisite for high-resolved climate and environmental reconstructions, as well as for archive comparisons. Thus, addressing the first aim, the novel chronology of Lake Gościąż was established by microscopic varve counting and Bayesian age-depth modelling in Bacon for a non-varved section, and was corroborated by independent age constrains from 137Cs activity concentration measurements, AMS radiocarbon dating and pollen analysis. The varve chronology reaches from the late Aller{\o}d until AD 2015, revealing more Holocene varves than a previous study of Lake Gościąż suggested. Varve formation throughout the complete Younger Dryas (YD) even allowed the identification of annually- to decadal-resolved leads and lags in proxy responses at the YD transitions. The lateglacial chronology of the Dead Sea (DS) was thus far mainly based on radiocarbon and U/Th-dating. In the unique ICDP core from the deep lake centre, continuous search for cryptotephra has been carried out in lateglacial sediments between two prominent gypsum deposits - the Upper and Additional Gypsum Units (UGU and AGU, respectively). Two cryptotephras were identified with glass analyses that correlate with tephra deposits from the S{\"u}phan and Nemrut volcanoes indicating that the AGU is ~1000 years younger than previously assumed, shifting it into the YD, and the underlying varved interval into the B{\o}lling/Aller{\o}d, contradicting previous assumptions. Using microfacies analyses, stable isotopes and temperature reconstructions, the second aim was achieved at Lake Gościąż. The YD lake system was dynamic, characterized by higher aquatic bioproductivity, more re-suspended material and less anoxia than during the Aller{\o}d and Early Holocene, mainly influenced by stronger water circulation and catchment erosion due to stronger westerly winds and less lake sheltering. Cooling at the YD onset was ~100 years longer than the final warming, while environmental proxies lagged the onset of cooling by ~90 years, but occurred contemporaneously during the termination of the YD. Chironomid-based temperature reconstructions support recent studies indicating mild YD summer temperatures. Such a comparison of annually-resolved proxy responses to both abrupt YD transitions is rare, because most European lake archives do not preserve varves during the YD. To accomplish the second aim at the DS, microfacies analyses were performed between the UGU (~17 ka) and Holocene onset (~11 ka) in shallow- (Masada) and deep-water (ICDP core) environments. This time interval is marked by a huge but fluctuating lake level drop and therefore the complete transition into the Holocene is only recorded in the deep-basin ICDP core. In this thesis, this transition was investigated for the first time continuously and in detail. The final two pronounced lake level drops recorded by deposition of the UGU and AGU, were interrupted by one millennium of relative depositional stability and a positive water budget as recorded by aragonite varve deposition interrupted by only a few event layers. Further, intercalation of aragonite varves between the gypsum beds of the UGU and AGU shows that these generally dry intervals were also marked by decadal- to centennial-long rises in lake level. While continuous aragonite varves indicate decadal-long stable phases, the occurrence of thicker and more frequent event layers suggests general more instability during the gypsum units. These results suggest a pattern of complex and variable hydroclimate at different time scales during the Lateglacial at the DS. The third aim was accomplished based on the individual studies above that jointly provide an integrated picture of different lake responses to different climate elements of hemispheric-scale abrupt climate changes during the Last Glacial-Interglacial transition. In general, climatically-driven facies changes are more dramatic in the DS than at Lake Gościąż. Further, Lake Gościąż is characterized by continuous varve formation nearly throughout the complete profile, whereas the DS record is widely characterized by extreme event layers, hampering the establishment of a continuous varve chronology. The lateglacial sedimentation in Lake Gościąż is mainly influenced by westerly winds and minor by changes in catchment vegetation, whereas the DS is primarily influenced by changes in winter precipitation, which are caused by temperature variations in the Mediterranean. Interestingly, sedimentation in both archives is more stable during the B{\o}lling/Aller{\o}d and more dynamic during the YD, even when sedimentation processes are different. In summary, this doctoral thesis presents seasonally-resolved records from two lake archives during the Lateglacial (ca 17-11 ka) to investigate the impact of abrupt climate changes in different lake systems. New age constrains from the identification of volcanic glass shards in the lateglacial sediments of the DS allowed the first lithology-based interpretation of the YD in the DS record and its comparison to Lake Gościąż. This highlights the importance of the construction of a robust chronology, and provides a first step for synchronization of the DS with other eastern Mediterranean archives. Further, climate reconstructions from the lake sediments showed variability on different time scales in the different archives, i.e. decadal- to millennial fluctuations in the lateglacial DS, and even annual variations and sub-decadal leads and lags in proxy responses during the rapid YD transitions in Lake Gościąż. This showed the importance of a comparison of different lake archives to better understand the regional and local impacts of hemispheric-scale climate variability. An unprecedented example is demonstrated here of how different lake systems show different lake responses and also react to different climate elements of abrupt climate changes. This further highlights the importance of the understanding of the respective lake system for climate reconstructions.}, language = {en} } @article{DiCapuaCoumou2016, author = {Di Capua, Giorgia and Coumou, Dim}, title = {Changes in meandering of the Northern Hemisphere circulation}, series = {Environmental research letters}, volume = {11}, journal = {Environmental research letters}, publisher = {IOP Publ. Ltd.}, address = {Bristol}, issn = {1748-9326}, doi = {10.1088/1748-9326/11/9/094028}, pages = {9}, year = {2016}, abstract = {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.}, language = {en} } @phdthesis{Banerjee2022, author = {Banerjee, Abhirup}, title = {Characterizing the spatio-temporal patterns of extreme events}, doi = {10.25932/publishup-55983}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-559839}, school = {Universit{\"a}t Potsdam}, pages = {xiv, 91}, year = {2022}, abstract = {Over the past decades, there has been a growing interest in 'extreme events' owing to the increasing threats that climate-related extremes such as floods, heatwaves, droughts, etc., pose to society. While extreme events have diverse definitions across various disciplines, ranging from earth science to neuroscience, they are characterized mainly as dynamic occurrences within a limited time frame that impedes the normal functioning of a system. Although extreme events are rare in occurrence, it has been found in various hydro-meteorological and physiological time series (e.g., river flows, temperatures, heartbeat intervals) that they may exhibit recurrent behavior, i.e., do not end the lifetime of the system. The aim of this thesis to develop some sophisticated methods to study various properties of extreme events. One of the main challenges in analyzing such extreme event-like time series is that they have large temporal gaps due to the paucity of the number of observations of extreme events. As a result, existing time series analysis tools are usually not helpful to decode the underlying information. I use the edit distance (ED) method to analyze extreme event-like time series in their unaltered form. ED is a specific distance metric, mainly designed to measure the similarity/dissimilarity between point process-like data. I combine ED with recurrence plot techniques to identify the recurrence property of flood events in the Mississippi River in the United States. I also use recurrence quantification analysis to show the deterministic properties and serial dependency in flood events. After that, I use this non-linear similarity measure (ED) to compute the pairwise dependency in extreme precipitation event series. I incorporate the similarity measure within the framework of complex network theory to study the collective behavior of climate extremes. Under this architecture, the nodes are defined by the spatial grid points of the given spatio-temporal climate dataset. Each node is associated with a time series corresponding to the temporal evolution of the climate observation at that grid point. Finally, the network links are functions of the pairwise statistical interdependence between the nodes. Various network measures, such as degree, betweenness centrality, clustering coefficient, etc., can be used to quantify the network's topology. We apply the methodology mentioned above to study the spatio-temporal coherence pattern of extreme rainfall events in the United States and the Ganga River basin, which reveals its relation to various climate processes and the orography of the region. The identification of precursors associated with the occurrence of extreme events in the near future is extremely important to prepare the masses for an upcoming disaster and mitigate the potential risks associated with such events. Under this motivation, I propose an in-data prediction recipe for predicting the data structures that typically occur prior to extreme events using the Echo state network, a type of Recurrent Neural Network which is a part of the reservoir computing framework. However, unlike previous works that identify precursory structures in the same variable in which extreme events are manifested (active variable), I try to predict these structures by using data from another dynamic variable (passive variable) which does not show large excursions from the nominal condition but carries imprints of these extreme events. Furthermore, my results demonstrate that the quality of prediction depends on the magnitude of events, i.e., the higher the magnitude of the extreme, the better is its predictability skill. I show quantitatively that this is because the input signals collectively form a more coherent pattern for an extreme event of higher magnitude, which enhances the efficiency of the machine to predict the forthcoming extreme events.}, language = {en} } @phdthesis{Malik2011, author = {Malik, Nishant}, title = {Extremes in events and dynamics : a nonlinear data analysis perspective on the past and present dynamics of the Indian summer monsoon}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-58016}, school = {Universit{\"a}t Potsdam}, year = {2011}, abstract = {To identify extreme changes in the dynamics of the Indian Summer Monsoon (ISM) in the past, I propose a new approach based on the quantification of fluctuations of a nonlinear similarity measure, to identify regimes of distinct dynamical complexity in short time series. I provide an analytical derivation for the relationship of the new measure with the dynamical invariants such as dimension and Lyapunov exponents of the underlying system. A statistical test is also developed to estimate the significance of the identified transitions. Our method is justified by uncovering bifurcation structures in several paradigmatic models, providing more complex transitions compared with traditional Lyapunov exponents. In a real world situation, we apply the method to identify millennial-scale dynamical transitions in Pleistocene proxy records of the south Asian summer monsoon system. We infer that many of these transitions are induced by the external forcing of solar insolation and are also affected by internal forcing on Monsoonal dynamics, i.e., the glaciation cycles of the Northern Hemisphere and the onset of the tropical Walker circulation. Although this new method has general applicability, it is particularly useful in analysing short palaeo-climate records. Rainfall during the ISM over the Indian subcontinent occurs in form of enormously complex spatiotemporal patterns due to the underlying dynamics of atmospheric circulation and varying topography. I present a detailed analysis of summer monsoon rainfall over the Indian peninsular using Event Synchronization (ES), a measure of nonlinear correlation for point processes such as rainfall. First, using hierarchical clustering I identify principle regions where the dynamics of monsoonal rainfall is more coherent or homogenous. I also provide a method to reconstruct the time delay patterns of rain events. Moreover, further analysis is carried out employing the tools of complex network theory. This study provides valuable insights into the spatial organization, scales, and structure of the 90th and 94th percentile rainfall events during the ISM (June to September). I furthermore analyse the influence of different critical synoptic atmospheric systems and the impact of the steep Himalayan topography on rainfall patterns. The presented method not only helps in visualising the structure of the extremeevent rainfall fields, but also identifies the water vapor pathways and decadal-scale moisture sinks over the region. Furthermore a simple scheme based on complex networks is presented to decipher the spatial intricacies and temporal evolution of monsoonal rainfall patterns over the last six decades. Some supplementary results on the evolution of monsoonal rainfall extremes over the last sixty years are also presented.}, language = {de} } @article{WebberLischeidSommeretal.2020, author = {Webber, Heidi and Lischeid, Gunnar and Sommer, Michael and Finger, Robert and Nendel, Claas and Gaiser, Thomas and Ewert, Frank}, title = {No perfect storm for crop yield failure in Germany}, series = {Environmental research letters}, volume = {15}, journal = {Environmental research letters}, number = {10}, publisher = {IOP Publ. Ltd.}, address = {Bristol}, issn = {1748-9326}, doi = {10.1088/1748-9326/aba2a4}, pages = {14}, year = {2020}, abstract = {Large-scale crop yield failures are increasingly associated with food price spikes and food insecurity and are a large source of income risk for farmers. While the evidence linking extreme weather to yield failures is clear, consensus on the broader set of weather drivers and conditions responsible for recent yield failures is lacking. We investigate this for the case of four major crops in Germany over the past 20 years using a combination of machine learning and process-based modelling. Our results confirm that years associated with widespread yield failures across crops were generally associated with severe drought, such as in 2018 and to a lesser extent 2003. However, for years with more localized yield failures and large differences in spatial patterns of yield failures between crops, no single driver or combination of drivers was identified. Relatively large residuals of unexplained variation likely indicate the importance of non-weather related factors, such as management (pest, weed and nutrient management and possible interactions with weather) explaining yield failures. Models to inform adaptation planning at farm, market or policy levels are here suggested to require consideration of cumulative resource capture and use, as well as effects of extreme events, the latter largely missing in process-based models. However, increasingly novel combinations of weather events under climate change may limit the extent to which data driven methods can replace process-based models in risk assessments.}, language = {en} } @phdthesis{Riebold2023, author = {Riebold, Johannes}, title = {On the linkage between future Arctic sea ice retreat, the large-scale atmospheric circulation and temperature extremes over Europe}, doi = {10.25932/publishup-60488}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-604883}, school = {Universit{\"a}t Potsdam}, pages = {xi, 126}, year = {2023}, abstract = {Extreme weather and climate events are one of the greatest dangers for present-day society. Therefore, it is important to provide reliable statements on what changes in extreme events can be expected along with future global climate change. However, the projected overall response to future climate change is generally a result of a complex interplay between individual physical mechanisms originated within the different climate subsystems. Hence, a profound understanding of these individual contributions is required in order to provide meaningful assessments of future changes in extreme events. One aspect of climate change is the recently observed phenomenon of Arctic Amplification and the related dramatic Arctic sea ice decline, which is expected to continue over the next decades. The question to what extent Arctic sea ice loss is able to affect atmospheric dynamics and extreme events over mid-latitudes has received a lot of attention over recent years and still remains a highly debated topic. In this respect, the objective of this thesis is to contribute to a better understanding on the impact of future Arctic sea ice retreat on European temperature extremes and large-scale atmospheric dynamics. The outcomes are based on model data from the atmospheric general circulation model ECHAM6. Two different sea ice sensitivity simulations from the Polar Amplification Intercomparison Project are employed and contrasted to a present day reference experiment: one experiment with prescribed future sea ice loss over the entire Arctic, as well as another one with sea ice reductions only locally prescribed over the Barents-Kara Sea.\% prescribed over the entire Arctic, as well as only locally over the Barent/Karasea with a present day reference experiment. The first part of the thesis focuses on how future Arctic sea ice reductions affect large-scale atmospheric dynamics over the Northern Hemisphere in terms of occurrence frequency changes of five preferred Euro-Atlantic circulation regimes. When compared to circulation regimes computed from ERA5 it shows that ECHAM6 is able to realistically simulate the regime structures. Both ECHAM6 sea ice sensitivity experiments exhibit similar regime frequency changes. Consistent with tendencies found in ERA5, a more frequent occurrence of a Scandinavian blocking pattern in midwinter is for instance detected under future sea ice conditions in the sensitivity experiments. Changes in occurrence frequencies of circulation regimes in summer season are however barely detected. After identifying suitable regime storylines for the occurrence of European temperature extremes in winter, the previously detected regime frequency changes are used to quantify dynamically and thermodynamically driven contributions to sea ice-induced changes in European winter temperature extremes. It is for instance shown how the preferred occurrence of a Scandinavian blocking regime under low sea ice conditions dynamically contributes to more frequent midwinter cold extreme occurrences over Central Europe. In addition, a reduced occurrence frequency of a Atlantic trough regime is linked to reduced winter warm extremes over Mid-Europe. Furthermore, it is demonstrated how the overall thermodynamical warming effect due to sea ice loss can result in less (more) frequent winter cold (warm) extremes, and consequently counteracts the dynamically induced changes. Compared to winter season, circulation regimes in summer are less suitable as storylines for the occurrence of summer heat extremes. Therefore, an approach based on circulation analogues is employed in order to quantify thermodyamically and dynamically driven contributions to sea ice-induced changes of summer heat extremes over three different European sectors. Reduced occurrences of blockings over Western Russia are detected in the ECHAM6 sea ice sensitivity experiments; however, arguing for dynamically and thermodynamically induced contributions to changes in summer heat extremes remains rather challenging.}, language = {en} } @article{GilingNejstgaardBergeretal.2017, author = {Giling, Darren P. and Nejstgaard, Jens C. and Berger, Stella A. and Grossart, Hans-Peter and Kirillin, Georgiy and Penske, Armin and Lentz, Maren and Casper, Peter and Sareyka, Joerg and Gessner, Mark O.}, title = {Thermocline deepening boosts ecosystem metabolism: evidence from a large-scale lake enclosure experiment simulating a summer storm}, series = {Global change biology}, volume = {23}, journal = {Global change biology}, publisher = {Wiley}, address = {Hoboken}, issn = {1354-1013}, doi = {10.1111/gcb.13512}, pages = {1448 -- 1462}, year = {2017}, abstract = {Extreme weather events can pervasively influence ecosystems. Observations in lakes indicate that severe storms in particular can have pronounced ecosystem-scale consequences, but the underlying mechanisms have not been rigorously assessed in experiments. One major effect of storms on lakes is the redistribution of mineral resources and plankton communities as a result of abrupt thermocline deepening. We aimed at elucidating the importance of this effect by mimicking in replicated large enclosures (each 9 m in diameter, ca. 20 m deep, ca. 1300 m 3 in volume) a mixing event caused by a severe natural storm that was previously observed in a deep clear-water lake. Metabolic rates were derived from diel changes in vertical profiles of dissolved oxygen concentrations using a Bayesian modelling approach, based on high-frequency measurements. Experimental thermocline deepening stimulated daily gross primary production (GPP) in surface waters by an average of 63\% for > 4 weeks even though thermal stratification re-established within 5 days. Ecosystem respiration (ER) was tightly coupled to GPP, exceeding that in control enclosures by 53\% over the same period. As GPP responded more strongly than ER, net ecosystem productivity (NEP) of the entire water column was also increased. These protracted increases in ecosystem metabolism and autotrophy were driven by a proliferation of inedible filamentous cyanobacteria released from light and nutrient limitation after they were entrained from below the thermocline into the surface water. Thus, thermocline deepening by a single severe storm can induce prolonged responses of lake ecosystem metabolism independent of other storm-induced effects, such as inputs of terrestrial materials by increased catchment run-off. This highlights that future shifts in frequency, severity or timing of storms are an important component of climate change, whose impacts on lake thermal structure will superimpose upon climate trends to influence algal dynamics and organic matter cycling in clear-water lakes. Keywords: climate variability, ecosystem productivity, extreme events, gross primary production, mesocosm, respiration stratified lakes}, language = {en} } @phdthesis{Agarwal2018, author = {Agarwal, Ankit}, title = {Unraveling spatio-temporal climatic patterns via multi-scale complex networks}, doi = {10.25932/publishup-42395}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423956}, school = {Universit{\"a}t Potsdam}, pages = {xxix, 153}, year = {2018}, abstract = {The climate is a complex dynamical system involving interactions and feedbacks among different processes at multiple temporal and spatial scales. Although numerous studies have attempted to understand the climate system, nonetheless, the studies investigating the multiscale characteristics of the climate are scarce. Further, the present set of techniques are limited in their ability to unravel the multi-scale variability of the climate system. It is completely plausible that extreme events and abrupt transitions, which are of great interest to climate community, are resultant of interactions among processes operating at multi-scale. For instance, storms, weather patterns, seasonal irregularities such as El Ni{\~n}o, floods and droughts, and decades-long climate variations can be better understood and even predicted by quantifying their multi-scale dynamics. This makes a strong argument to unravel the interaction and patterns of climatic processes at different scales. With this background, the thesis aims at developing measures to understand and quantify multi-scale interactions within the climate system. In the first part of the thesis, I proposed two new methods, viz, multi-scale event synchronization (MSES) and wavelet multi-scale correlation (WMC) to capture the scale-specific features present in the climatic processes. The proposed methods were tested on various synthetic and real-world time series in order to check their applicability and replicability. The results indicate that both methods (WMC and MSES) are able to capture scale-specific associations that exist between processes at different time scales in a more detailed manner as compared to the traditional single scale counterparts. In the second part of the thesis, the proposed multi-scale similarity measures were used in constructing climate networks to investigate the evolution of spatial connections within climatic processes at multiple timescales. The proposed methods WMC and MSES, together with complex network were applied to two different datasets. In the first application, climate networks based on WMC were constructed for the univariate global sea surface temperature (SST) data to identify and visualize the SSTs patterns that develop very similarly over time and distinguish them from those that have long-range teleconnections to other ocean regions. Further investigations of climate networks on different timescales revealed (i) various high variability and co-variability regions, and (ii) short and long-range teleconnection regions with varying spatial distance. The outcomes of the study not only re-confirmed the existing knowledge on the link between SST patterns like El Ni{\~n}o Southern Oscillation and the Pacific Decadal Oscillation, but also suggested new insights into the characteristics and origins of long-range teleconnections. In the second application, I used the developed non-linear MSES similarity measure to quantify the multivariate teleconnections between extreme Indian precipitation and climatic patterns with the highest relevance for Indian sub-continent. The results confirmed significant non-linear influences that were not well captured by the traditional methods. Further, there was a substantial variation in the strength and nature of teleconnection across India, and across time scales. Overall, the results from investigations conducted in the thesis strongly highlight the need for considering the multi-scale aspects in climatic processes, and the proposed methods provide robust framework for quantifying the multi-scale characteristics.}, language = {en} }