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The Greenland Ice Sheet is the second-largest mass of ice on Earth. Being almost 2000 km long, more than 700 km wide, and more than 3 km thick at the summit, it holds enough ice to raise global sea levels by 7m if melted completely. Despite its massive size, it is particularly vulnerable to anthropogenic climate change: temperatures over the Greenland Ice Sheet have increased by more than 2.7◦C in the past 30 years, twice as much as the global mean temperature. Consequently, the ice sheet has been significantly losing mass since the 1980s and the rate of loss has increased sixfold since then. Moreover, it is one of the potential tipping elements of the Earth System, which might undergo irreversible change once a warming threshold is exceeded. This thesis aims at extending the understanding of the resilience of the Greenland Ice Sheet against global warming by analyzing processes and feedbacks relevant to its centennial to multi-millennial stability using ice sheet modeling.
One of these feedbacks, the melt-elevation-feedback is driven by the temperature rise with decreasing altitudes: As the ice sheet melts, its thickness and surface elevation decrease, exposing the ice surface to warmer air and thus increasing the melt rates even further. The glacial isostatic adjustment (GIA) can partly mitigate this melt-elevation feedback as the bedrock lifts in response to an ice load decrease, forming the negative GIA feedback. In my thesis, I show that the interaction between these two competing feedbacks can lead to qualitatively different dynamical responses of the Greenland Ice Sheet to warming – from permanent loss to incomplete recovery, depending on the feedback parameters. My research shows that the interaction of those feedbacks can initiate self-sustained oscillations of the ice volume while the climate forcing remains constant.
Furthermore, the increased surface melt changes the optical properties of the snow or ice surface, e.g. by lowering their albedo, which in turn enhances melt rates – a process known as the melt-albedo feedback. Process-based ice sheet models often neglect this melt-albedo feedback. To close this gap, I implemented a simplified version of the diurnal Energy Balance Model, a computationally efficient approach that can capture the first-order effects of the melt-albedo feedback, into the Parallel Ice Sheet Model (PISM). Using the coupled model, I show in warming experiments that the melt-albedo feedback almost doubles the ice loss until the year 2300 under the low greenhouse gas emission scenario RCP2.6, compared to simulations where the melt-albedo feedback is neglected,
and adds up to 58% additional ice loss under the high emission scenario RCP8.5. Moreover, I find that the melt-albedo feedback dominates the ice loss until 2300, compared to the melt-elevation feedback.
Another process that could influence the resilience of the Greenland Ice Sheet is the warming induced softening of the ice and the resulting increase in flow. In my thesis, I show with PISM how the uncertainty in Glen’s flow law impacts the simulated response to warming. In a flow line setup at fixed climatic mass balance, the uncertainty in flow parameters leads to a range of ice loss comparable to the range caused by different warming levels.
While I focus on fundamental processes, feedbacks, and their interactions in the first three projects of my thesis, I also explore the impact of specific climate scenarios on the sea level rise contribution of the Greenland Ice Sheet. To increase the carbon budget flexibility, some warming scenarios – while still staying within the limits of the Paris Agreement – include a temporal overshoot of global warming. I show that an overshoot by 0.4◦C increases the short-term and long-term ice loss from Greenland by several centimeters. The long-term increase is driven by the warming at high latitudes, which persists even when global warming is reversed. This leads to a substantial long-term commitment of the sea level rise contribution from the Greenland Ice Sheet.
Overall, in my thesis I show that the melt-albedo feedback is most relevant for the ice loss of the Greenland Ice Sheet on centennial timescales. In contrast, the melt-elevation feedback and its interplay with the GIA feedback become increasingly relevant on millennial timescales. All of these influence the resilience of the Greenland Ice Sheet against global warming, in the near future and on the long term.
Digitale Forschungsdaten gewinnen zunehmend an Bedeutung und stellen neue Herausforderungen an wissenschaftliche Einrichtungen und ihre Forschenden. Der Begriff Forschungsdatenmanagement umfasst alle Aktivitäten, die mit der Aufbereitung, Speicherung, Archivierung und Veröffentlichung von Forschungsdaten verbunden sind. Da der Umgang mit Forschungsdaten generische, fachliche, rechtliche und technische Aspekte betrifft, erfordert es eine Begleitung der Forschenden durch ein umfangreiches Spektrum an Services, von Information und Beratung bis hin zu fachspezifischen Standards und IT-Infrastrukturen.
Im vorliegenden Bericht werden zunächst die Ausgangslage und die Begrifflichkeiten rund um Forschungsdatenmanagement geklärt und anschließend die wichtigsten nationalen und internationalen Strategien und Entwicklungen vorgestellt. Dabei bilden Richtlinien und Empfehlungen für Forschungsdaten(management) den Handlungsrahmen für alle Beteiligte hin zu einem nachhaltigen Forschungsdatenmanagement. Bundeslandinitiativen schaffen die Grundlage und unterstützen den Kulturwandel zu offenen Daten.
Eine Forschungsdaten-Strategie für Brandenburg muss die Bedeutung von digitalen Forschungsdaten als wissenschaftliches Gut in den Vordergrund stellen, indem dafür das Bewusstsein geschaffen wird und konkrete Vorgaben und Leitlinien auf Landes- und Einrichtungsebene vereinbart werden. Gute wissenschaftliche Praxis wird durch eine geeignete Infrastruktur unterstützt, welche die heterogenen Bedarfe und Voraussetzungen aller Beteiligten berücksichtigt. Ziele sollten die Institutionalisierung von Forschungsdatenmanagement an den Hochschulen und Kooperationen zwischen den Einrichtungen Brandenburgs sein.
This paper introduces a novel measure to assess similarity between event hydrographs. It is based on Cross Recurrence Plots and Recurrence Quantification Analysis which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multi-dimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to Cross Recurrence Plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.
The NAC transcription factor (TF) JUNGBRUNNEN1 (JUB1) is an important negative regulator of plant senescence, as well as of gibberellic acid (GA) and brassinosteroid (BR) biosynthesis in Arabidopsis thaliana. Overexpression of JUB1 promotes longevity and enhances tolerance to drought and other abiotic stresses. A similar role of JUB1 has been observed in other plant species, including tomato and banana. Our data show that JUB1 overexpressors (JUB1-OXs) accumulate higher levels of proline than WT plants under control conditions, during the onset of drought stress, and thereafter. We identified that overexpression of JUB1 induces key proline biosynthesis and suppresses key proline degradation genes. Furthermore, bZIP63, the transcription factor involved in proline metabolism, was identified as a novel downstream target of JUB1 by Yeast One-Hybrid (Y1H) analysis and Chromatin immunoprecipitation (ChIP). However, based on Electrophoretic Mobility Shift Assay (EMSA), direct binding of JUB1 to bZIP63 could not be confirmed. Our data indicate that JUB1-OX plants exhibit reduced stomatal conductance under control conditions. However, selective overexpression of JUB1 in guard cells did not improve drought stress tolerance in Arabidopsis. Moreover, the drought-tolerant phenotype of JUB1 overexpressors does not solely depend on the transcriptional control of the DREB2A gene. Thus, our data suggest that JUB1 confers tolerance to drought stress by regulating multiple components. Until today, none of the previous studies on JUB1´s regulatory network focused on identifying protein-protein interactions. We, therefore, performed a yeast two-hybrid screen (Y2H) which identified several protein interactors of JUB1, two of which are the calcium-binding proteins CaM1 and CaM4. Both proteins interact with JUB1 in the nucleus of Arabidopsis protoplasts. Moreover, JUB1 is expressed with CaM1 and CaM4 under the same conditions. Since CaM1.1 and CaM4.1 encode proteins with identical amino acid sequences, all further experiments were performed with constructs involving the CaM4 coding sequence. Our data show that JUB1 harbors multiple CaM-binding sites, which are localized in both the N-terminal and C-terminal regions of the protein. One of the CaM-binding sites, localized in the DNA-binding domain of JUB1, was identified as a functional CaM-binding site since its mutation strongly reduced the binding of CaM4 to JUB1. Furthermore, JUB1 transactivates expression of the stress-related gene DREB2A in mesophyll cells; this effect is significantly reduced when the calcium-binding protein CaM4 is expressed as well. Overexpression of both genes in Arabidopsis results in early senescence observed through lower chlorophyll content and an enhanced expression of senescence-associated genes (SAGs) when compared with single JUB1 overexpressors. Our data also show that JUB1 and CaM4 proteins interact in senescent leaves, which have increased Ca2+ levels when compared to young leaves. Collectively, our data indicate that JUB1 activity towards its downstream targets is fine-tuned by calcium-binding proteins during leaf senescence.
Climate change is one of the greatest challenges to humanity in this century, and most noticeable consequences are expected to be impacts on the water cycle – in particular the distribution and availability of water, which is fundamental for all life on Earth. In this context, it is essential to better understand where and when water is available and what processes influence variations in water storages. While estimates of the overall terrestrial water storage (TWS) variations are available from the GRACE satellites, these represent the vertically integrated signal over all water stored in ice, snow, soil moisture, groundwater and surface water bodies. Therefore, complementary observational data and hydrological models are still required to determine the partitioning of the measured signal among different water storages and to understand the underlying processes. However, the application of large-scale observational data is limited by their specific uncertainties and the incapacity to measure certain water fluxes and storages. Hydrological models, on the other hand, vary widely in their structure and process-representation, and rarely incorporate additional observational data to minimize uncertainties that arise from their simplified representation of the complex hydrologic cycle.
In this context, this thesis aims to contribute to improving the understanding of global water storage variability by combining simple hydrological models with a variety of complementary Earth observation-based data. To this end, a model-data integration approach is developed, in which the parameters of a parsimonious hydrological model are calibrated against several observational constraints, inducing GRACE TWS, simultaneously, while taking into account each data’s specific strengths and uncertainties. This approach is used to investigate 3 specific aspects that are relevant for modelling and understanding the composition of large-scale TWS variations.
The first study focusses on Northern latitudes, where snow and cold-region processes define the hydrological cycle. While the study confirms previous findings that seasonal dynamics of TWS are dominated by the cyclic accumulation and melt of snow, it reveals that inter-annual TWS variations on the contrary, are determined by variations in liquid water storages. Additionally, it is found to be important to consider the impact of compensatory effects of spatially heterogeneous hydrological variables when aggregating the contribution of different storage components over large areas. Hence, the determinants of TWS variations are scale-dependent and underlying driving mechanism cannot be simply transferred between spatial and temporal scales. These findings are supported by the second study for the global land areas beyond the Northern latitudes as well.
This second study further identifies the considerable impact of how vegetation is represented in hydrological models on the partitioning of TWS variations. Using spatio-temporal varying fields of Earth observation-based data to parameterize vegetation activity not only significantly improves model performance, but also reduces parameter equifinality and process uncertainties. Moreover, the representation of vegetation drastically changes the contribution of different water storages to overall TWS variability, emphasizing the key role of vegetation for water allocation, especially between sub-surface and delayed water storages. However, the study also identifies parameter equifinality regarding the decay of sub-surface and delayed water storages by either evapotranspiration or runoff, and thus emphasizes the need for further constraints hereof.
The third study focuses on the role of river water storage, in particular whether it is necessary to include computationally expensive river routing for model calibration and validation against the integrated GRACE TWS. The results suggest that river routing is not required for model calibration in such a global model-data integration approach, due to the larger influence other observational constraints, and the determinability of certain model parameters and associated processes are identified as issues of greater relevance. In contrast to model calibration, considering river water storage derived from routing schemes can already significantly improve modelled TWS compared to GRACE observations, and thus should be considered for model evaluation against GRACE data.
Beyond these specific findings that contribute to improved understanding and modelling of large-scale TWS variations, this thesis demonstrates the potential of combining simple modeling approaches with diverse Earth observational data to improve model simulations, overcome inconsistencies of different observational data sets, and identify areas that require further research. These findings encourage future efforts to take advantage of the increasing number of diverse global observational data.