This paper introduces the Graphics Processing Unit (GPU)-based tool Geo-Temporal eXplorer (GTX), integrating a set of highly interactive techniques for visual analytics of large geo-referenced complex networks from the climate research domain. The visual exploration of these networks faces a multitude of challenges related to the geo-reference and the size of these networks with up to several million edges and the manifold types of such networks. In this paper, solutions for the interactive visual analysis for several distinct types of large complex networks will be discussed, in particular, time-dependent, multi-scale, and multi-layered ensemble networks. Custom-tailored for climate researchers, the GTX tool supports heterogeneous tasks based on interactive, GPU-based solutions for on-the-fly large network data processing, analysis, and visualization. These solutions are illustrated for two use cases: multi-scale climatic process and climate infection risk networks. This tool helps one to reduce the complexity of the highly interrelated climate information and unveils hidden and temporal links in the climate system, not available using standard and linear tools (such as empirical orthogonal function analysis).

Countless climate images are in circulation on the internet, such as burning globes, polar bears and photos of global climate impacts.These images are networked and generate a specific view of climate change.Our case study engages in an intercultural image comparison based on Google Image queries.As an interdisciplinary team of experts drawn from art history, media studies, interface design and computer graphics, our goal was to use a combination of qualitative and quantitative image analyses to explore the predominant discourses of digitised visual climate communication on the web.To this end, we automated the analysis of different formal features of climate images (such as colour values, density and composition) with the aid of computer-driven methods (such as computer vision and machine learning) to build a corpus of thousands of images.Our focus was on image similarities, a concept shared by both image theory and computer analysis.In this chapter, we elucidate the outcome of our research on a conceptual and technical basis.The core issue addressed here is the manner in which arthistorical methods (such as iconography and the concept of visual framing) are transformed when using computer-generated methods of computer vision and machine learning to analyse image similarities.This chapter focuses on our various insights while also reflecting on the general question of networked images on a methodological level.Ultimately, we were able to identify the promising potential but also the key limits of algorithmic image recognition and sorting when using machine learning to study images on the internet.

The digital transformation is accompanied by two simultaneous processes: digital humanities challenging the humanities, their theories, methodologies and disciplinary identities, and pushing computer science to get involved in new fields. But how can qualitative and quantitative methods be usefully combined in one research project? What are the theoretical and methodological principles across all disciplinary digital approaches? This volume focusses on driving innovation and conceptualising the humanities in the 21st century. Building on the results of 10 research projects, it serves as a useful tool for designing cutting-edge research that goes beyond conventional strategies.

Himalayan region is a critical part of the globe. In recent years, vegetation cover in this region is undergoing considerable changes attributed ongoing to climatic and anthropogenic factors. The present study aims to capture the interannual vegetation changes over 19 years and explore how topographic and climatic variables contribute to the observed changes. Satellite-derived Normalized Difference Vegetation Index (NDVI) dataset (2001–2019) was used to examine the spatio-temporal patterns of vegetation in Uttarakhand state in the Indian western Himalayas. Further analysis explored variation across elevation, temperature, precipitation, and vegetation types. Most parts of the Uttarakhand region experienced increasing NDVI trends, particularly in the Needleleaved Evergreen and Broadleaved Deciduous forest types; however, negative trends were observed in shrublands.

The educational web portal www.klimafolgenonline-bildung.de is a tailor-made climate service to make climate and climate impact data and scientific knowledge of climate impacts and adaptation applicable for secondary and vocational schools in Germany. Climate science fundamentals and worksheets combining the interactive experience exploring climate data in the web portal with other sources have been designed for the school context to enable teachers to educate the complex relationships of climate change and its impacts [1]. In addition, as an easy-to-use compendium for the multitude and heterogeneous teaching materials, we have set up the separate web site www.klimabildung-pik.de. This site includes as well handouts, explanations and a tutorial. Here, we follow a competence-oriented approach, directed at everyday experience and the direct regional reference of students, enabling them to come to reasoned decisions. To test and improve the developed learning lessons, to make them more self-explanatory and to tailor them for disciplinary school lessons, we performed more than 40 workshops and surveys with teachers. In secondary schools, nearly for all subjects we found entrance points for climate change learning units. In vocational schools, we developed learning units for economics, social studies, politics, healthcare management and insurance brokerage. During the development process, we identified a number of challenges related to climate education with an interactive web portal approach (see as well [1]): the requirement to break down the scientific information when using a web portal, the usability of scientific visualizations for non-expert users, the communication of uncertainties and the integration of interactive web portals in school lessons in general. A specific observation is that in some cases the gap between the media skills of teachers and students can be a problem while interactively orienting in a complex space of climate scenarios, sectors and parameters. The additional time requirements for teachers integrating new interactive material into a rigid school curriculum and the level of attention span of some students can be further obstacles using the provided teaching material. For vocational schools, we observed much less hurdles and a higher motivation of students even without teacher support. For future work, we plan to integrate the teaching material into our new international portal version (currently available at kfo.pik-potsdam.de), providing teaching material tailored to climate impact information as well outside of Germany and for teachers and students in other world regions. [1] Blumenthal, I., Schlenther, C., Hirsbrunner, S., Stock, M., Nocke, T. (2018): Climate Impacts for German Schools - An Educational Web Portal Solution. - In: Filho, W. L., Manolas, E., Azul, A. M., Azeiteiro, U. M., McGhie, H. (Eds.), Handbook of Climate Change Communication: Vol. 3 - Case Studies in Climate Change Communication, Cham : Springer, 209-223.

Visualization has become an important ingredient of data analysis, supporting users in exploring data and confirming hypotheses. At the beginning of a visual data analysis process, data characteristics are often assessed in an initial data profiling step. These include, for example, statistical properties of the data and information on the data’s well-formedness, which can be used during the subsequent analysis to adequately parametrize views and to highlight or exclude data items. We term this information data descriptors, which can span such diverse aspects as the data’s provenance, its storage schema, or its uncertainties. Gathered descriptors encapsulate basic knowledge about the data and can thus be used as objective starting points for the visual analysis process. In this article, we bring together these different aspects in a systematic form that describes the data itself (e.g. its content and context) and its relation to the larger data gathering and visual analysis process (e.g. its provenance and its utility). Once established in general, we further detail the concept of data descriptors specifically for tabular data as the most common form of structured data today. Finally, we utilize these data descriptors for tabular data to capture domain-specific data characteristics in the field of climate impact research. This procedure from the general concept via the concrete data type to the specific application domain effectively provides a blueprint for instantiating data descriptors for other data types and domains in the future.

The polar and subtropical jet streams are strong upper-level winds with a crucial influence on weather throughout the Northern Hemisphere midlatitudes. In particular, the polar jet is located between cold arctic air to the north and warmer subtropical air to the south. Strongly meandering states therefore often lead to extreme surface weather. Some algorithms exist which can detect the 2-D (latitude and longitude) jets' core around the hemisphere, but all of them use a minimal threshold to determine the subtropical and polar jet stream. This is particularly problematic for the polar jet stream, whose wind velocities can change rapidly from very weak to very high values and vice versa. We develop a network-based scheme using Dijkstra's shortest-path algorithm to detect the polar and subtropical jet stream core. This algorithm not only considers the commonly used wind strength for core detection but also takes wind direction and climatological latitudinal position into account. Furthermore, it distinguishes between polar and subtropical jet, and between separate and merged jet states. The parameter values of the detection scheme are optimized using simulated annealing and a skill function that accounts for the zonal-mean jet stream position (Rikus, 2015). After the successful optimization process, we apply our scheme to reanalysis data covering 1979–2015 and calculate seasonal-mean probabilistic maps and trends in wind strength and position of jet streams. We present longitudinally defined probability distributions of the positions for both jets for all on the Northern Hemisphere seasons. This shows that winter is characterized by two well-separated jets over Europe and Asia (ca. 20° W to 140° E). In contrast, summer normally has a single merged jet over the western hemisphere but can have both merged and separated jet states in the eastern hemisphere. With this algorithm it is possible to investigate the position of the jets' cores around the hemisphere and it is therefore very suitable to analyze jet stream patterns in observations and models, enabling more advanced model-validation.

Visualization has become an accepted tool to support the process of gaining insight into data. Current visualization research mainly focuses on exploratory or confirmatory visualization taking place in classic workplace settings. In this paper, we focus on the presentation and discussion of visualization results among domain experts, rather than on the generation of visual representations by visualization experts. We develop a visualization infrastructure for a novel kind of visualization environment labeled smart meeting room, which provides plenty of display space to present the visual information to be discussed. We describe the mechanisms needed to show multiple visualization views on multiple displays and to interact with the views across device boundaries. Our system includes methods to dynamically generate visualization views, to suggest suitable layouts of the views, and to enable interactive fine-tuning to accommodate the dynamically changing needs of the user (e.g., access to details on demand). The benefits for the users are illustrated by an application in the context of climate impact research.

The visual analysis of complex geo-spatial data is a challenging task. Typically, different views are used to communicate different aspects. With changing topics of interest, however, novel views are required. This leads to dynamically changing presentations of multiple views. This paper introduces a novel approach to support such scenarios. It allows for a spontaneous incorporation of views from different sources and to automatically layout these views in a multi-display environment. Furthermore, we introduce an enhanced undo/redo mechanism for this setting, which records user interactions and, in this way, enables swift reconfigurations of displayed views. Hence, users can fluently switch the focus of visual analysis without extensive manual interactions. We demonstrate our approach by the particular use case of discussing geo-spatial climate data.

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Subnational socio-economic datasets are required if we are to assess the impacts of global environmental changes and to improve adaptation responses. Institutional and community efforts should concentrate on standardization of data collection methodologies, free public access, and geo-referencing.

In this paper, we present an overview of strategies that use graphics and photographs in skeptical climate media. After showing how photographs are used as emotional teaser or as a way of maligning certain scientists, we give examples of the most widespread figures used in a method called "cherry picking'', This describes the strategy of focusing on a small detail among findings while at the same lime blocking out the larger context in order to contradict the consensus that anthropogenic emissions are causing global warming (e.g., "But some glaciers are growing!" instead of "Most glaciers around the world are melting."). The use of such misleading graphs, mainly in the form of time series curves, is more widespread than that of deliberately faked graphs. Given the complex nature of climate science, misleading graphs can easily confuse people not involved in climate research, while the publishing conditions of the web are actually helping the skeptics. Examples for the climate 'skeptical' use of images and,graphs arc discussed in this paper from an interdisciplinary view based on climate science, visual studies and computer graphics. At the same time the example illustrates the precarious distinction of science (epistemology / facts) and politics (values) in modern risk societies, where political decisions arc sought to be legitimated in technical terms only.

Scientific research on climate change has given rise to a variety of images picturing climate change. These range from colorful expert graphics, model visualizations, photographs of extreme weather events like floods, droughts or melting ice, symbols like polar bears, to animated and interactive visualizations. Climate change graphics have not only increased knowledge about the subject, they have begun to influence popular awareness of global weather events. The status of climate pictures today is particularly crucial, as global climate change as a long-term process cannot be seen. When images are widely distributed, they are able to shape how the world is thought about and seen. It is this implicit basic assumption of the power of images to influence reality that this book addresses: today's images might become the blueprint for tomorrow's realities. »Image Politics of Climate Change« combines a wide interdisciplinary range of perspectives and questions, treated here in sixteen interdisciplinary case studies. The author's specializations include both visual practice and theory: in the fields of climate sciences, computer graphics, art, curating, art history and visual studies, communication and cultural science, environmental and science & technology studies. The close interlinking of these viewpoints promotes in-depth insights into issues of production and analysis of climate visualization.