TY - CHAP A1 - Kuhn, Alexander A1 - Lindow, Norbert A1 - Günther, Tobias A1 - Wiebel, Alexander A1 - Theisel, Holger A1 - Hege, Hans-Christian T1 - Trajectory Density Projection for Vector Field Visualization T2 - EuroVis 2013, short papers. M. Hlawitschka, Tino Weinkauf (eds.) Y1 - 2013 UR - http://vc.cs.ovgu.de/files/publications/2013/Kuhn_2013_EUROVIS.pdf U6 - https://doi.org/10.2312/PE.EuroVisShort.EuroVisShort2013.031-035 SP - 31 EP - 35 ER - TY - JOUR A1 - Günther, Tobias A1 - Kuhn, Alexander A1 - Kutz, Benjamin A1 - Theisel, Holger T1 - Mass-Dependent Integral Curves in Unsteady Vector Fields JF - Computer Graphics Forum Y1 - 2013 U6 - https://doi.org/10.1111/cgf.12108 VL - 32 SP - 211 EP - 220 ER - TY - CHAP A1 - Engelke, Wito A1 - Kuhn, Alexander A1 - Flatken, Markus A1 - Chen, Fang A1 - Hege, Hans-Christian A1 - Gerndt, Andreas A1 - Hotz, Ingrid T1 - Atmospheric Impact of Volcano Eruptions T2 - Proceedings IEEE SciVis 2014 N2 - The analysis of data that captures volcanic eruptions and their atmospheric aftermath plays an important role for domain experts to gain a deeper understanding of the volcanic eruption and their consequences for atmosphere, climate and air traffic. Thereby, one major challenge is to extract and combine the essential information, which is spread over various, mostly sparse data sources. This requires a careful integration of each data set with its strength and limitations. The sparse, but more reliable measurement data is mainly used to calibrate the more dense simulation data. This work combines a collection of visualization approaches into an exploitative framework. The goal is to support the domain experts to build a complete picture of the situation. But it is also important to understand the individual data sources, the wealth of their information and the quality of the simulation results. All presented methods are designed for direct interaction with the data from different perspectives rather than the sole generation of some final images. Y1 - 2014 ER - TY - CHAP A1 - Kuhn, Alexander A1 - Engelke, Wito A1 - Flatken, Markus A1 - Hege, Hans-Christian A1 - Hotz, Ingrid T1 - Topology-based Analysis for Multimodal Atmospheric Data of Volcano Eruptions T2 - Topological Methods in Data Analysis and Visualization IV Y1 - 2017 U6 - https://doi.org/10.1007/978-3-319-44684-4_2 SP - 35 EP - 50 PB - Springer CY - Cham, Schweiz ER - TY - JOUR A1 - Günther, Tobias A1 - Kuhn, Alexander A1 - Hege, Hans-Christian A1 - Theisel, Holger T1 - MCFTLE: Monte Carlo Rendering of Finite-Time Lyapunov Exponent Fields JF - Computer Graphics Forum Y1 - 2016 U6 - https://doi.org/10.1111/cgf.12914 N1 - By mistake the fourth author Hans-Christian Hege has been ommitted in the journal publication VL - 35 IS - 3 SP - 381 EP - 390 ER - TY - GEN A1 - Günther, Tobias A1 - Kuhn, Alexander A1 - Hege, Hans-Christian A1 - Gross, Markus A1 - Theisel, Holger T1 - Progressive Monte-Carlo Rendering of Atmospheric Flow Features Across Scales T2 - 69th Annual Meeting of the APS Division of Fluid Dynamics, Gallery of Fluid Motion, Nov 20-22, 2016, Portland, OR, USA. N2 - To improve existing weather prediction and reanalysis capabilities, high-resolution and multi-modal climate data becomes an increasingly important topic. The advent of increasingly dense numerical simulation of atmospheric phenomena, provides new means to better understand dynamic processes and to visualize structural flow patterns that remain hidden otherwise. In the presented illustrations we demonstrate an advanced technique to visualize multiple scales of dense flow fields and Lagrangian patterns therein, simulated by state-of-the-art simulation models for each scale. They provide a deeper insight into the structural differences and patterns that occur on each scale and highlight the complexity of flow phenomena in our atmosphere. Y1 - 2016 U6 - https://doi.org/10.1103/APS.DFD.2016.GFM.P0030 ER - TY - CHAP A1 - Kuhn, Alexander A1 - Hege, Hans-Christian T1 - Object-based visualization and evaluation of cloud-resolving simulations T2 - Book of Abstracts, SCCS 2017 – Scaling Cascades in Complex Systems, Mar 27-29, 2017, Berlin, Germany N2 - Recent advances in high-resolution, cloud resolving simulation models pose several challenges towards respective analysis methodologies. To enable efficient comparison and validation of such models efficient, scalable, and informative diagnostic procedures are mandatory. In this talk, an object-based evaluation scheme based on the notion of scalar field topology will be presented. The presentation will cover the application of topological clustering procedures for object identification, tracking, and the retrieval of object-based statistics. The pro-posed methodology is shown to enable an advanced in-depth evaluation and visualization of high cloud-resolving models. Using a newly developed large-scale high-resolution model (i.e., HD(CP)2 ICON), it will be demonstrated that the presented procedures are applicable to assess the model performance compared to measurements (e.g., radar, satellite) and standard operational models (COSMO) at different domains and spatial scales. Y1 - 2017 ER - TY - CHAP A1 - Sakurai, Daisuke A1 - Hege, Hans-Christian A1 - Kuhn, Alexander A1 - Rust, Henning A1 - Kern, Bastian A1 - Breitkopf, Tom-Lukas T1 - An Application-Oriented Framework for Feature Tracking in Atmospheric Sciences T2 - Proceedings of 2017 IEEE 7th Symposium on Large Data Analysis and Visualization (LDAV) N2 - In atmospheric sciences, sizes of data sets grow continuously due to increasing resolutions. A central task is the comparison of spatiotemporal fields, to assess different simulations and to compare simulations with observations. A significant information reduction is possible by focusing on geometric-topological features of the fields or on derived meteorological objects. Due to the huge size of the data sets, spatial features have to be extracted in time slices and traced over time. Fields with chaotic component, i.e. without 1:1 spatiotemporal correspondences, can be compared by looking upon statistics of feature properties. Feature extraction, however, requires a clear mathematical definition of the features - which many meteorological objects still lack. Traditionally, object extractions are often heuristic, defined only by implemented algorithms, and thus are not comparable. This work surveys our framework designed for efficient development of feature tracking methods and for testing new feature definitions. The framework supports well-established visualization practices and is being used by atmospheric researchers to diagnose and compare data. Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-66685 SP - 96 EP - 97 ER - TY - JOUR A1 - Günther, Tobias A1 - Kuhn, Alexander A1 - Hege, Hans-Christian A1 - Gross, Markus A1 - Theisel, Holger T1 - Progressive Monte Carlo rendering of atmospheric flow features across scales JF - Physical Review Fluids N2 - To improve existing weather prediction and reanalysis capabilities, high-resolution and multi-modal climate data becomes an increasingly important topic. The advent of increasingly dense numerical simulation of atmospheric phenomena, provides new means to better understand dynamic processes and to visualize structural flow patterns that remain hidden otherwise. In the presented illustrations we demonstrate an advanced technique to visualize multiple scales of dense flow fields and Lagrangian patterns therein, simulated by state-of-the-art simulation models for each scale. They provide a deeper insight into the structural differences and patterns that occur on each scale and highlight the complexity of flow phenomena in our atmosphere. This paper is associated with a poster winner of a 2016 APS/DFD Milton van Dyke Award for work presented at the DFD Gallery of Fluid Motion. The original poster is available from the Gallery of Fluid Motion, https://doi.org/10.1103/APS.DFD.2016.GFM.P0030 Y1 - 2017 U6 - https://doi.org/10.1103/PhysRevFluids.2.090502 VL - 2 SP - 09050-1 EP - 09050-3 ER - TY - JOUR A1 - Heinze, Rieke A1 - Dipankar, Anurag A1 - Henken, Cintia Carbajal A1 - Moseley, Christopher A1 - Sourdeval, Odran A1 - Trömel, Silke A1 - Xie, Xinxin A1 - Adamidis, Panos A1 - Ament, Felix A1 - Baars, Holger A1 - Barthlott, Christian A1 - Behrendt, Andreas A1 - Blahak, Ulrich A1 - Bley, Sebastian A1 - Brdar, Slavko A1 - Brueck, Matthias A1 - Crewell, Susanne A1 - Deneke, Hartwig A1 - Di Girolamo, Paolo A1 - Evaristo, Raquel A1 - Fischer, Jürgen A1 - Frank, Christopher A1 - Friederichs, Petra A1 - Göcke, Tobias A1 - Gorges, Ksenia A1 - Hande, Luke A1 - Hanke, Moritz A1 - Hansen, Akio A1 - Hege, Hans-Christian A1 - Hose, Corinna A1 - Jahns, Thomas A1 - Kalthoff, Norbert A1 - Klocke, Daniel A1 - Kneifel, Stefan A1 - Knippertz, Peter A1 - Kuhn, Alexander A1 - van Laar, Thriza A1 - Macke, Andreas A1 - Maurer, Vera A1 - Mayer, Bernhard A1 - Meyer, Catrin I. A1 - Muppa, Shravan K. A1 - Neggers, Roeland A. J. A1 - Orlandi, Emiliano A1 - Pantillon, Florian A1 - Pospichal, Bernhard A1 - Röber, Niklas A1 - Scheck, Leonhard A1 - Seifert, Axel A1 - Seifert, Patric A1 - Senf, Fabian A1 - Siligam, Pavan A1 - Simmer, Clemens A1 - Steinke, Sandra A1 - Stevens, Bjorn A1 - Wapler, Kathrin A1 - Weniger, Michael A1 - Wulfmeyer, Volker A1 - Zängl, Günther A1 - Zhang, Dan A1 - Quaas, Johannes T1 - Large-eddy simulations over Germany using ICON: a comprehensive evaluation JF - Quarterly Journal of the Royal Meteorological Society N2 - Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales, focusing on boundary-layer variables, clouds and precipitation. The evaluation points to the need to work on parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small- to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model. Y1 - 2017 U6 - https://doi.org/10.1002/qj.2947 VL - 143 IS - 702 SP - 69 EP - 100 ER - TY - GEN A1 - Sieber, Moritz A1 - Kuhn, Alexander A1 - Hege, Hans-Christian A1 - Paschereit, C. Oliver A1 - Oberleithner, Kilian T1 - A Graphical Representation of the Spectral Proper Orthogonal Decomposition T2 - 68th Annual Meeting of the APS Division of Fluid Dynamics, Gallery of Fluid Motion, Nov 22-24, 2015, Boston, MA, USA. N2 - We consider the spectral proper orthogonal decomposition (SPOD) for experimental data of a turbulent swirling jet. This newly introduced method combines the advantages of spectral methods, such as Fourier decomposition or dynamic mode decomposition, with the energy-ranked proper orthogonal decomposition (POD). This poster visualizes how the modal energy spectrum transitions from the spectral purity of Fourier space to the sparsity of POD space. The transition is achieved by changing a single parameter – the width of the SPOD filter. Each dot in the 3D space corresponds to an SPOD mode pair, where the size and color indicates its spectral coherence. What we notice is that neither the Fourier nor the POD spectrum achieves a clear separation of the dynamic phenomena. Scanning through the graph from the front plane (Fourier) to the back plane (POD), we observe how three highly coherent SPOD modes emerge from the dispersed Fourier spectrum and later branch out into numerous POD modes. The spatial properties of these three individual SPOD modes are displayed in the back of the graph using line integral convolution colored by vorticity. The first two modes correspond to single-helical global instabilities that are well known for these flows. Their coexistence, however, has not been observed until now. The third mode is of double- helical shape and has not been observed so far. For this considered data set and many others, the SPOD is superior in identification of coherent structures in turbulent flows. Hopefully, it gives access to new fluid dynamic phenomena and enriches the available methods. Y1 - 2015 ER - TY - GEN A1 - Kuhn, Alexander A1 - Trömel, Silke T1 - Intercomparison Study of Cloud Feature Extraction and Tracking Algorithms BT - EGU General Assembly 2015, held 12-17 April, 2015 in Vienna, Austria T2 - Geophysical Research Abstracts, Vol 17 N2 - Clouds and precipitation systems are fundamental features in the global climate cycle and are one focus aspect of recent high resolution, cloud resolving simulations and measurement modalities. Highly resolved data sources allow for more precise methodologies to extract and track cloud features on different scales and enable novel evaluation tasks such as life-cycle tracking, feature-based statistics, and feature-based comparison of simulation and measurements. However, their complex dynamics and highly variable shape morphology makes extraction and tracking of clouds a challenging task with respect to stable and reliable algorithms. In this work we will present our efforts on establishing an community-wide inter-comparison study to provide an overview of state-of-the-art algorithms for cloud extraction and tracking. We propose a set of 2D and 3D benchmark data sets (from simulations and measurements) that are used as a common basis for comparison. In addition we describe a joint feature-based evaluation framework and provide an in depth analysis and comparison of those algorithms. The goal is to systematically compare and assess numerical extraction and tracking techniques for cloud features in meteorological data and provide a comprehensive overview of suitable application scenarios, describe current strengths and limitations, and derive statements about their variability for feature-based analysis tasks. Y1 - 2015 N1 - Oral presentation at EGU 2015 VL - 17 SP - ID 14128 ER - TY - JOUR A1 - Oeltze, Steffen A1 - Lehmann, Dirk J. A1 - Kuhn, Alexander A1 - Janiga, Gábor A1 - Theisel, Holger A1 - Preim, Bernhard T1 - Blood Flow Clustering and Applications in Virtual Stenting of Intracranial Aneurysms JF - IEEE Transactions on Visualization and Computer Graphics, 2014 Y1 - 2013 U6 - https://doi.org/10.1109/TVCG.2013.2297914 SN - 0934-5892 VL - 20 IS - 5 SP - 686 EP - 701 ER - TY - THES A1 - Kuhn, Alexander T1 - Lagrangian Methods for Visualization and Analysis of Time-dependent Vector Fields N2 - Time-dependent vector fields are of high relevance to describe a wide range of physical phenomena based on particle motion, including stall effects in technical engineering, blood flow anomalies, and atmospheric mass trans- port. The efficient analysis and fundamental understanding of intrinsic field properties can lead to significant improvements when interacting with such phenomena based on the available field data. So called Lagrangian methods are a particularly established technique for this purpose. They are based on the evaluation of time-dependent particle trajectories. This work will present an overview of the state of the art in time-dependent vector field analysis and visualization, with special focus on topology-oriented and Lagrangian methods. The first core aspect of this work is the introduction of a novel concept for a more objective and qualitative benchmark of existing Lagrangian approaches. Based on this benchmark, this work contributes and evaluates a set of novel concepts, that offer new perspectives towards established approaches with respect to computational handling, quality and efficiency. The second core aspect is the empirical application and validation of Lagrangian methods with respect to practically relevant analysis scenarios. Each application case includes an introduction into the underlying problem statement and an efficient solution using Lagrangian methods. The validation focuses on the comparison with existing flow analysis concepts and aspects of the quantitative evaluation in each case. Together, both topics of this work contribute towards a more consistent formalization, but also to the improved applicability of Lagrangian methods. KW - Flow Visualization, Time-dependent Vector Fields Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:ma9:1-4177 UR - http://edoc2.bibliothek.uni-halle.de/hs/id/31067 ER - TY - GEN A1 - Sakurai, Daisuke A1 - Hege, Hans-Christian A1 - Kuhn, Alexander A1 - Rust, Henning A1 - Kern, Bastian A1 - Breitkopf, Tom-Lukas T1 - An Application-Oriented Framework for Feature Tracking in Atmospheric Sciences N2 - In atmospheric sciences, sizes of data sets grow continuously due to increasing resolutions. A central task is the comparison of spatiotemporal fields, to assess different simulations and to compare simulations with observations. A significant information reduction is possible by focusing on geometric-topological features of the fields or on derived meteorological objects. Due to the huge size of the data sets, spatial features have to be extracted in time slices and traced over time. Fields with chaotic component, i.e. without 1:1 spatiotemporal correspondences, can be compared by looking upon statistics of feature properties. Feature extraction, however, requires a clear mathematical definition of the features – which many meteorological objects still lack. Traditionally, object extractions are often heuristic, defined only by implemented algorithms, and thus are not comparable. This work surveys our framework designed for efficient development of feature tracking methods and for testing new feature definitions. The framework supports well-established visualization practices and is being used by atmospheric researchers to diagnose and compare data. T3 - ZIB-Report - 17-50 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-72617 SN - 1438-0064 ER - TY - GEN A1 - Günther, Tobias A1 - Kuhn, Alexander A1 - Hege, Hans-Christian A1 - Theisel, Holger T1 - MCFTLE: Monte Carlo Rendering of Finite-Time Lyapunov Exponent Fields N2 - Traditionally, Lagrangian fields such as finite-time Lyapunov exponents (FTLE) are precomputed on a discrete grid and are ray casted afterwards. This, however, introduces both grid discretization errors and sampling errors during ray marching. In this work, we apply a progressive, view-dependent Monte Carlo-based approach for the visualization of such Lagrangian fields in time-dependent flows. Our ap- proach avoids grid discretization and ray marching errors completely, is consistent, and has a low memory consumption. The system provides noisy previews that con- verge over time to an accurate high-quality visualization. Compared to traditional approaches, the proposed system avoids explicitly predefined fieldline seeding structures, and uses a Monte Carlo sampling strategy named Woodcock tracking to distribute samples along the view ray. An acceleration of this sampling strategy requires local upper bounds for the FTLE values, which we progressively acquire during the rendering. Our approach is tailored for high-quality visualizations of complex FTLE fields and is guaranteed to faithfully represent detailed ridge surface structures as indicators for Lagrangian coherent structures (LCS). We demonstrate the effectiveness of our approach by using a set of analytic test cases and real-world numerical simulations. T3 - ZIB-Report - 16-21 KW - Picture/Image Generation, Display algorithms, Three-Dimensional Graphics and Realism, Raytracing Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-59054 SN - 1438-0064 N1 - By mistake the fourth author Hans-Christian Hege has been ommitted in the journal publication ER - TY - GEN A1 - Kuhn, Alexander A1 - Engelke, Wito A1 - Flatken, Markus A1 - Hege, Hans-Christian A1 - Hotz, Ingrid T1 - Topology-based Analysis for Multimodal Atmospheric Data of Volcano Eruptions N2 - Many scientific applications deal with data from a multitude of different sources, e.g., measurements, imaging and simulations. Each source provides an additional perspective on the phenomenon of interest, but also comes with specific limitations, e.g. regarding accuracy, spatial and temporal availability. Effectively combining and analyzing such multimodal and partially incomplete data of limited accuracy in an integrated way is challenging. In this work, we outline an approach for an integrated analysis and visualization of the atmospheric impact of volcano eruptions. The data sets comprise observation and imaging data from satellites as well as results from numerical particle simulations. To analyze the clouds from the volcano eruption in the spatiotemporal domain we apply topological methods. Extremal structures reveal structures in the data that support clustering and comparison. We further discuss the robustness of those methods with respect to different properties of the data and different parameter setups. Finally we outline open challenges for the effective integrated visualization using topological methods. T3 - ZIB-Report - 16-03 KW - multi-modal, intergrated data analysis, topology Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-57043 SN - 1438-0064 ER - TY - GEN A1 - Kuhn, Alexander A1 - Engelke, Wito A1 - Rössl, Christian A1 - Hadwiger, Markus A1 - Theisel, Holger T1 - Time Line Cell Tracking for the Approximation of Lagrangian Coherent Structures with Subgrid Accuracy N2 - Lagrangian Coherent Structures (LCS) have become a widespread and powerful method to describe dynamic motion patterns in time-dependent flow fields. The standard way to extract LCS is to compute height ridges in the Finite Time Lyapunov Exponent (FTLE) field. In this work, we present an alternative method to approximate Lagrangian features for 2D unsteady flow fields that achieves subgrid accuracy without additional particle sampling. We obtain this by a geometric reconstruction of the flow map using additional material constraints for the available samples. In comparison to the standard method, this allows for a more accurate global approximation of LCS on sparse grids and for long integration intervals. The proposed algorithm works directly on a set of given particle trajectories and without additional flow map derivatives. We demonstrate its application for a set of computational fluid dynamic examples, as well as trajectories acquired by Lagrangian methods, and discuss its benefits and limitations. T3 - ZIB-Report - 13-71 KW - time-dependent vector fields KW - flow field visualization KW - Lagrangian Coherent Structures (LCS) KW - finite-time Lyapunov exponents (FTLE) KW - time lines Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-43050 SN - 1438-0064 ER - TY - JOUR A1 - Kuhn, Alexander A1 - Engelke, Wito A1 - Rössl, Christian A1 - Hadwiger, Markus A1 - Theisel, Holger T1 - Time Line Cell Tracking for the Approximation of Lagrangian Coherent Structures with Subgrid Accuracy JF - Computer Graphics Forum Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-43990 SN - 0934-5892 VL - 33 SP - 222 EP - 234 PB - Wiley Blackwell ER -