Prof. Dr. Jens Schröter
Profil
Forschungsthemen10
CL Topoi II / Ü: Ancient Judaism
Quelle ↗Förderer: DFG Exzellenzinitiative Cluster Zeitraum: 11/2017 - 12/2018 Projektleitung: Prof. Dr. Gerd Graßhoff, Prof. Dr. Jens Schröter
Die Nag-Hammadi-Schriften in der Literaturgeschichte des frühen Christentums
Quelle ↗Förderer: Fritz Thyssen Stiftung Zeitraum: 02/2015 - 05/2016 Projektleitung: Prof. Dr. Jens Schröter
Durchsicht der Lutherbibel
Quelle ↗Zeitraum: 11/2010 - 12/2011 Projektleitung: Prof. Dr. Jens Schröter
Endkorrektur eines Manuskripts "Texte und Materialien des Neuen Testaments"
Quelle ↗Zeitraum: 08/2011 - 09/2011 Projektleitung: Prof. Dr. Jens Schröter
Fellowship im Rahmen der DFG-Kolleg-Forschungsgruppe FOR 2770/1
Quelle ↗Förderer: DFG Kolleg-Forschungsgruppe Zeitraum: 09/2020 - 08/2021 Projektleitung: Prof. Dr. Jens Schröter
Gleichnisse und Parabeln in der frühchristlichen Literatur
Quelle ↗Zeitraum: 03/2018 - 07/2019 Projektleitung: Prof. Dr. Jens Schröter
Paulusrezeptionen im frühen Christentum: Von den Anfängen bis zu Irenäus
Quelle ↗Förderer: Fritz Thyssen Stiftung Zeitraum: 02/2017 - 03/2018 Projektleitung: Prof. Dr. Jens Schröter
"The Eucharist in Early Christianity within the Context of Ancient Cultic Meals" (Veranstaltung: 19. - 21. April, Barcelona)
Quelle ↗Förderer: Fritz Thyssen Stiftung Zeitraum: 04/2013 - 05/2013 Projektleitung: Prof. Dr. Jens Schröter
The Rise and Expansion of Christianity in the First Three Centuries C.E." (Veranstaltung: 26.-27.07.2010, Berlin)
Quelle ↗Zeitraum: 07/2010 - 12/2010 Projektleitung: Prof. Dr. Jens Schröter
The Rise and Expansion of Early Christianity - Tagungsbanderstellung
Quelle ↗Zeitraum: 11/2011 - 04/2012 Projektleitung: Prof. Dr. Jens Schröter
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Publikationen25
Top 25 nach Zitationen — Quelle: OpenAlex (BAAI/bge-m3 embedded für Matching).
Geoscientific model development · 301 Zitationen · DOI
Abstract. The Finite Element Sea Ice-Ocean Model (FESOM) is the first global ocean general circulation model based on unstructured-mesh methods that has been developed for the purpose of climate research. The advantage of unstructured-mesh models is their flexible multi-resolution modelling functionality. In this study, an overview of the main features of FESOM will be given; based on sensitivity experiments a number of specific parameter choices will be explained; and directions of future developments will be outlined. It is argued that FESOM is sufficiently mature to explore the benefits of multi-resolution climate modelling and that its applications will provide information useful for the advancement of climate modelling on unstructured meshes.
Proceedings of the National Academy of Sciences · 296 Zitationen · DOI
Dividing the sea-level budget into contributions from ice sheets and glaciers, the water cycle, steric expansion, and crustal movement is challenging, especially on regional scales. Here, Gravity Recovery And Climate Experiment (GRACE) gravity observations and sea-level anomalies from altimetry are used in a joint inversion, ensuring a consistent decomposition of the global and regional sea-level rise budget. Over the years 2002-2014, we find a global mean steric trend of 1.38 ± 0.16 mm/y, compared with a total trend of 2.74 ± 0.58 mm/y. This is significantly larger than steric trends derived from in situ temperature/salinity profiles and models which range from 0.66 ± 0.2 to 0.94 ± 0.1 mm/y. Mass contributions from ice sheets and glaciers (1.37 ± 0.09 mm/y, accelerating with 0.03 ± 0.02 mm/y(2)) are offset by a negative hydrological component (-0.29 ± 0.26 mm/y). The combined mass rate (1.08 ± 0.3 mm/y) is smaller than previous GRACE estimates (up to 2 mm/y), but it is consistent with the sum of individual contributions (ice sheets, glaciers, and hydrology) found in literature. The altimetric sea-level budget is closed by coestimating a remaining component of 0.22 ± 0.26 mm/y. Well above average sea-level rise is found regionally near the Philippines (14.7 ± 4.39 mm/y) and Indonesia (8.3 ± 4.7 mm/y) which is dominated by steric components (11.2 ± 3.58 mm/y and 6.4 ± 3.18 mm/y, respectively). In contrast, in the central and Eastern part of the Pacific, negative steric trends (down to -2.8 ± 1.53 mm/y) are detected. Significant regional components are found, up to 5.3 ± 2.6 mm/y in the northwest Atlantic, which are likely due to ocean bottom pressure variations.
Climate Dynamics · 248 Zitationen · DOI
A new climate model has been developed that employs a multi-resolution dynamical core for the sea ice-ocean component. In principle, the multi-resolution approach allows one to use enhanced horizontal resolution in dynamically active regions while keeping a coarse-resolution setup otherwise. The coupled model consists of the atmospheric model ECHAM6 and the finite element sea ice-ocean model (FESOM). In this study only moderate refinement of the unstructured ocean grid is applied and the resolution varies from about 25 km in the northern North Atlantic and in the tropics to about 150 km in parts of the open ocean; the results serve as a benchmark upon which future versions that exploit the potential of variable resolution can be built. Details of the formulation of the model are given and its performance in simulating observed aspects of the mean climate is described. Overall, it is found that ECHAM6–FESOM realistically simulates many aspects of the observed climate. More specifically it is found that ECHAM6–FESOM performs at least as well as some of the most sophisticated climate models participating in the fifth phase of the Coupled Model Intercomparison Project. ECHAM6–FESOM shares substantial shortcomings with other climate models when it comes to simulating the North Atlantic circulation.
Ocean Modelling · 200 Zitationen · DOI
Journal of Marine Systems · 194 Zitationen · DOI
Ocean Modelling · 172 Zitationen · DOI
Geoscientific model development · 170 Zitationen · DOI
Abstract. The Finite-Element Sea Ice Model (FESIM), used as a component of the Finite-Element Sea ice Ocean Model, is presented. Version 2 includes the elastic-viscous-plastic (EVP) and viscous-plastic (VP) solvers and employs a flux corrected transport algorithm to advect the ice and snow mean thicknesses and concentration. The EVP part also includes a modified approach proposed recently by Bouillon et al. (2013), which is characterized by an improved stability compared to the standard EVP approach. The model is formulated on unstructured triangular meshes. It assumes a collocated placement of ice velocities, mean thicknesses and concentration at mesh vertices, and relies on piecewise-linear (P1) continuous elements. Simple tests for the modified EVP and VP solvers are presented to show that they may produce very close results provided the number of iterations is sufficiently high.
Helmholtz-Zentrum für Polar-und Meeresforschung (Alfred-Wegener-Institut) · 166 Zitationen
Monthly Weather Review · 152 Zitationen · DOI
Abstract In recent years, several ensemble-based Kalman filter algorithms have been developed that have been classified as ensemble square root Kalman filters. Parallel to this development, the singular “evolutive” interpolated Kalman (SEIK) filter has been introduced and applied in several studies. Some publications note that the SEIK filter is an ensemble Kalman filter or even an ensemble square root Kalman filter. This study examines the relation of the SEIK filter to ensemble square root filters in detail. It shows that the SEIK filter is indeed an ensemble square root Kalman filter. Furthermore, a variant of the SEIK filter, the error subspace transform Kalman filter (ESTKF), is presented that results in identical ensemble transformations to those of the ensemble transform Kalman filter (ETKF), while having a slightly lower computational cost. Numerical experiments are conducted to compare the performance of three filters (SEIK, ETKF, and ESTKF) using deterministic and random ensemble transformations. The results show better performance for the ETKF and ESTKF methods over the SEIK filter as long as this filter is not applied with a symmetric square root. The findings unify the separate developments that have been performed for the SEIK filter and the other ensemble square root Kalman filters.
Ocean Modelling · 140 Zitationen · DOI
Biogeosciences · 128 Zitationen · DOI
Abstract. During phytoplankton growth a fraction of dissolved inorganic carbon (DIC) assimilated by phytoplankton is exuded in the form of dissolved organic carbon (DOC), which can be transformed into extracellular particulate organic carbon (POC). A major fraction of extracellular POC is associated with carbon of transparent exopolymer particles (TEP; carbon content = TEPC) that form from dissolved polysaccharides (PCHO). The exudation of PCHO is linked to an excessive uptake of DIC that is not directly quantifiable from utilisation of dissolved inorganic nitrogen (DIN), called carbon overconsumption. Given these conditions, the concept of assuming a constant stoichiometric carbon-to-nitrogen (C:N) ratio for estimating new production of POC from DIN uptake becomes inappropriate. Here, a model of carbon overconsumption is analysed, combining phytoplankton growth with TEPC formation. The model describes two modes of carbon overconsumption. The first mode is associated with DOC exudation during phytoplankton biomass accumulation. The second mode is decoupled from algal growth, but leads to a continuous rise in POC while particulate organic nitrogen (PON) remains constant. While including PCHO coagulation, the model goes beyond a purely physiological explanation of building up carbon rich particulate organic matter (POM). The model is validated against observations from a mesocosm study. Maximum likelihood estimates of model parameters, such as nitrogen- and carbon loss rates of phytoplankton, are determined. The optimisation yields results with higher rates for carbon exudation than for the loss of organic nitrogen. It also suggests that the PCHO fraction of exuded DOC was 63±20% during the mesocosm experiment. Optimal estimates are obtained for coagulation kernels for PCHO transformation into TEPC. Model state estimates are consistent with observations, where 30% of the POC increase was attributed to TEPC formation. The proposed model is of low complexity and is applicable for large-scale biogeochemical simulations.
J.B. Metzler eBooks · 126 Zitationen · DOI
Von Geld über Brief und Comic bis Radio, Video und mobile Medien welchen Platz nehmen diese Themen in den Medienwissenschaften ein? Das Handbuch stellt Begriffe und Theorien vor, darunter systemtheore
Journal of Geophysical Research Atmospheres · 118 Zitationen · DOI
Topographic steering of waves and currents is one of the most important issues of the general ocean circulation. Its representation in ocean models depends on the spatial discretization, which heavily influences the ocean circulation even on the global scale. Models capable of working on unstructured grids allow to represent topography and coastlines continuously and to refine mesh locally. Finite Element Ocean circulation Model (FEOM) belongs to this class of ocean general circulation models. Its discretization is based on unstructured triangular meshes on the surface and prismatic elements in the volume. The model uses continuous linear representation for the horizontal velocity, surface elevation, temperature and salinity, and solves the standard set of hydrostatic primitive equations. The method to stabilize the numerical pressure modes and the implementation of hybrid vertical grids are discussed. The model supports hybrid vertical grids including z and σ grids and their combination within the same numerical kernel. A method for calculating pressure gradient forces is introduced to reduce pressure gradient errors on inclined computational surfaces. Its performance is assessed via numerical experiments. The influence of different vertical discretization is illustrated using a seamount configuration. The model is MPI parallelized and has the functionality required for ocean general circulation modeling. It can be used as an efficient and versatile numerical tool for regional and global oceanographic applications and climate studies.
CLCWeb Comparative Literature and Culture · 107 Zitationen · DOI
In his article "Discourses and Models of Intermediality" Jens Schröter discusses the question as to what relations do different discourses pose between different "media." Schröter identifies four models of discourse: 1) synthetic intermediality: a "fusion" of different media to super-media, a model with roots in the Wagnerian concept of Gesamtkunstwerk with political connotations, 2) formal (or transmedial) intermediality: a concept based on formal structures not "specific" to one medium but found in different media, 3) transformational intermediality: a model centered around the representation of one medium through another medium. Model 3) leads to the postulate that transformational intermediality is not located in intermediality but in processes of representation and thus transformational intermediality is the flip side of model 4) ontological intermediality: a model suggesting that media always already exist in relation to other media. Thus, model 4) suggests that there are no single media but that intermedial relations take place ubiquitously. Schröter comes to the conclusion that one should not start with definitions of media and then discuss intermediality but the opposite: The intermedial field (including the intermedial processes on writing about intermediality) produces definitions of media.
Journal of Geophysical Research Atmospheres · 101 Zitationen · DOI
The 20th century regional and global sea level variations are estimated based on long‐term tide gauge records. For this the neural network technique is utilized that connects the coastal sea level with the regional and global mean via a nonlinear empirical relationship. Two major difficulties are overcome this way: the vertical movement of tide gauges over time and the problem of what weighting function to choose for each individual tide gauge record. Neural networks are also used to fill data gaps in the tide gauge records, which is a prerequisite for our analysis technique. A suite of different gap‐filling strategies is tested which provides information about stability and variance of the results. The global mean sea level for the period January 1900 to December 2006 is estimated to rise at a rate of 1.56 ± 0.25 mm/yr which is reasonably consistent with earlier estimates, but we do not find significant acceleration. The regional mean sea level of the single ocean basins show mixed long‐term behavior. While most of the basins show a sea level rise of varying strength there is an indication for a mean sea level fall in the southern Indian Ocean. Also for the the tropical Indian and the South Atlantic no significant trend can be detected. Nevertheless, the South Atlantic as well as the tropical Atlantic are the only basins that show significant acceleration. On shorter timescales, but longer than the annual cycle, the basins sea level are dominated by oscillations with periods of about 50–75 years and of about 25 years. Consequently, we find high (lagged) correlations between the single basins.
Monthly Weather Review · 100 Zitationen · DOI
Abstract Ensemble Kalman filter methods are typically used in combination with one of two localization techniques. One technique is covariance localization, or direct forecast error localization, in which the ensemble-derived forecast error covariance matrix is Schur multiplied with a chosen correlation matrix. The second way of localization is by domain decomposition. Here, the assimilation is split into local domains in which the assimilation update is performed independently. Domain localization is frequently used in combination with filter algorithms that use the analysis error covariance matrix for the calculation of the gain like the ensemble transform Kalman filter (ETKF) and the singular evolutive interpolated Kalman filter (SEIK). However, since the local assimilations are performed independently, smoothness of the analysis fields across the subdomain boundaries becomes an issue of concern. To address the problem of smoothness, an algorithm is introduced that uses domain localization in combination with a Schur product localization of the forecast error covariance matrix for each local subdomain. On a simple example, using the Lorenz-40 system, it is demonstrated that this modification can produce results comparable to those obtained with direct forecast error localization. In addition, these results are compared to the method that uses domain localization in combination with weighting of observations. In the simple example, the method using weighting of observations is less accurate than the new method, particularly if the observation errors are small. Domain localization with weighting of observations is further examined in the case of assimilation of satellite data into the global finite-element ocean circulation model (FEOM) using the local SEIK filter. In this example, the use of observational weighting improves the accuracy of the analysis. In addition, depending on the correlation function used for weighting, the spectral properties of the solution can be improved.
Tellus A Dynamic Meteorology and Oceanography · 98 Zitationen · DOI
Three advanced filter algorithms based on the Kalman filter are reviewed and presented in a unified notation. They are the well-known ensemble Kalman filter (EnKF), the singular evolutive extended Kalman (SEEK) filter, and the less common singular evolutive interpolated Kalman (SEIK) filter. For comparison, the mathematical formulations of the filters are reviewed in relation to the extended Kalman filter as error subspace Kalman filters. The algorithms are presented in their original form and possible variations are discussed. A comparison of the algorithms shows their theoretical capabilities for efficient data assimilation with large-scale non-linear systems. In particular, problems of the analysis equations are apparent in the original EnKF algorithm due to the Monte Carlo sampling of ensembles. Theoretically, the SEIK filter appears to be a numerically very efficient algorithm with high potential for use with non-linear models. The superiority of the SEIK filter is demonstrated on the basis of identical twin experiments using a shallow-water model with non-linear evolution. Identical initial conditions for all three filters allow for a consistent comparison of the data assimilation results. These show how choices of particular state ensembles and assimilation schemes lead to significant variations of the filter performance. This is related to different qualities of the predicted error subspaces, as is demonstrated in an examination of the predicted state covariance matrices.
Journal of Climate · 91 Zitationen · DOI
Abstract Empirical orthogonal function (EOF) analysis is commonly used in the climate sciences and elsewhere to describe, reconstruct, and predict highly dimensional data fields. When data contain a high percentage of missing values (i.e., gappy), alternate approaches must be used in order to correctly derive EOFs. The aims of this paper are to assess the accuracy of several EOF approaches in the reconstruction and prediction of gappy data fields, using the Galapagos Archipelago as a case study example. EOF approaches included least squares estimation via a covariance matrix decomposition [least squares EOF (LSEOF)], data interpolating empirical orthogonal functions (DINEOF), and a novel approach called recursively subtracted empirical orthogonal functions (RSEOF). Model-derived data of historical surface chlorophyll- a concentrations and sea surface temperature, combined with a mask of gaps from historical remote sensing estimates, allowed for the creation of true and observed fields by which to gauge the performance of EOF approaches. Only DINEOF and RSEOF were found to be appropriate for gappy data reconstruction and prediction. DINEOF proved to be the superior approach in terms of accuracy, especially for noisy data with a high estimation error, although RSEOF may be preferred for larger data fields because of its relatively faster computation time.
Quarterly Journal of the Royal Meteorological Society · 88 Zitationen · DOI
Abstract Localization is an essential element of ensemble‐based Kalman filters in large‐scale systems. Two localization methods are commonly used: covariance localization and domain localization. The former applies a localizing weight to the forecast covariance matrix, while the latter splits the assimilation into local regions in which independent assimilation updates are performed. The domain localization is usually combined with observation localization, which is a weighting of the observation‐error covariance matrix, resulting in a similar localization effect to that of covariance localized filters. It is shown that the use of the same localization function in covariance localization and observation localization results in distinct effective localization length‐scales in the Kalman gain. In order to improve the performance of observation localization, a regulated localization scheme is introduced. Twin experiments with the Lorenz‐96 model demonstrate that the regulated localization can lead to a significant reduction of estimation errors as well as increased stability of the assimilation process. Copyright © 2011 Royal Meteorological Society
Quarterly Journal of the Royal Meteorological Society · 87 Zitationen · DOI
Abstract During the past 15 years, a number of initiatives have been undertaken at national level to develop ocean forecasting systems operating at regional and/or global scales. The co‐ordination between these efforts has been organized internationally through the Global Ocean Data Assimilation Experiment (GODAE). The French MERCATOR project is one of the leading participants in GODAE. The MERCATOR systems routinely assimilate a variety of observations such as multi‐satellite altimeter data, sea‐surface temperature and in situ temperature and salinity profiles, focusing on high‐resolution scales of the ocean dynamics. The assimilation strategy in MERCATOR is based on a hierarchy of methods of increasing sophistication including optimal interpolation, Kalman filtering and variational methods, which are progressively deployed through the Système d'Assimilation MERCATOR (SAM) series. SAM‐1 is based on a reduced‐order optimal interpolation which can be operated using ‘altimetry‐only’ or ‘multi‐data’ set‐ups; it relies on the concept of separability, assuming that the correlations can be separated into a product of horizontal and vertical contributions. The second release, SAM‐2, is being developed to include new features from the singular evolutive extended Kalman (SEEK) filter, such as three‐dimensional, multivariate error modes and adaptivity schemes. The third one, SAM‐3, considers variational methods such as the incremental four‐dimensional variational algorithm. Most operational forecasting systems evaluated during GODAE are based on least‐squares statistical estimation assuming Gaussian errors. In the framework of the EU MERSEA (Marine EnviRonment and Security for the European Area) project, research is being conducted to prepare the next‐generation operational ocean monitoring and forecasting systems. The research effort will explore nonlinear assimilation formulations to overcome limitations of the current systems. This paper provides an overview of the developments conducted in MERSEA with the SEEK filter, the Ensemble Kalman filter and the sequential importance re‐sampling filter. Copyright © 2005 Royal Meteorological Society
Journal of Geophysical Research Atmospheres · 86 Zitationen · DOI
The 2004 catastrophic Indian Ocean tsunami has strongly emphasized the need for reliable tsunami early warning systems. Another giant tsunamigenic earthquake may occur west of Sumatra, close to the large city of Padang. We demonstrate that the presence of islands between the trench and the Sumatran coast makes earthquake‐induced tsunamis especially sensitive to slip distribution on the rupture plane as wave heights at Padang may differ by more than a factor of 5 for earthquakes having the same seismic moment (magnitude) and rupture zone geometry but different slip distribution. Hence reliable prediction of tsunami wave heights for Padang cannot be provided using traditional, earthquake‐magnitude‐based methods. We show, however, that such a prediction can be issued within 10 minutes of an earthquake by incorporating special types of near‐field GPS arrays (“GPS‐Shield”). These arrays measure both vertical and horizontal displacements and can resolve higher order features of the slip distribution on the fault than the seismic moment if placed above the rupture zone or are less than 100 km away of the rupture zone. Stations in the arrays are located as close as possible to the trench and are aligned perpendicular to the trench, i.e., parallel to the expected gradient of surface coseismic displacement. In the case of Sumatra and Java, the GPS‐Shield arrays should be placed at Mentawai Islands, located between the trench and Sumatra and directly at the Sumatra and Java western coasts. We demonstrate that the “GPS‐Shield” can also be applied to northern Chile, where giant earthquakes may also occur in the near future. Moreover, this concept may be applied globally to many other tsunamigenic active margins where the land is located above or close to seismogenic zones.
Harvard University Press eBooks · 74 Zitationen · DOI
Journal of Geophysical Research Oceans · 74 Zitationen · DOI
The volume and freshwater transports through the Canadian Arctic Archipelago (CAA) are assessed using the unstructured‐mesh Finite Element Sea ice‐Ocean Model (FESOM) in a global setup with the CAA resolved at 5 km scale. The hindcast simulation realistically represents fluxes through the main gates of the Arctic Ocean and the Arctic sea ice conditions. During the period 1968–2007, the mean volume transports through Lancaster Sound and Nares Strait amount to 0.86 and 0.91 Sv, respectively. The monthly mean volume transport through western Lancaster Sound is highly correlated with the observational estimate (r = 0.81). The seasonal variability of the Lancaster Sound transport is well represented in the model. The simulated mean CAA freshwater export rate is 123 mSv, slightly higher than the observational estimate. The interannual variability of CAA volume transports is determined by sea surface height (SSH) gradients between the Arctic Ocean and northern Baffin Bay. The sea level upstream of Lancaster Sound is mainly determined by that along the Beaufort Sea coast, which can be explained by changes in the wind regimes (cyclonic versus anticyclonic) associated with release or accumulation of freshwater in the Beaufort Gyre. Sea level variations downstream of Lancaster Sound and Nares Strait are connected to SSH variations in the eastern Baffin Bay and in the Labrador Sea, which can be attributed to the variability of ocean‐atmosphere heat fluxes. Both processes upstream and downstream of the CAA are linked with the North Atlantic Oscillation type of atmospheric variability. The local mesh refinement of ∼5 km allows us to investigate the contribution of individual narrow straits to the Parry Channel volume transport. The volume transports through these straits show a very similar variability.
Ocean Dynamics · 68 Zitationen · DOI
Journal of Geodynamics · 63 Zitationen · DOI
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