Inter- and Transdisciplinary Sessions
Disciplinary sessions AS–GM
Disciplinary sessions GMPV–TS

Session programme


ESSI – Earth & Space Science Informatics

Programme group chairs: Jane Hart, Jens Klump, Helen Glaves


Global plastic production has increased exponentially since the fifties, with 359 million metric tons manufactured in 2018 alone. Nearly 20% of this production took place within Europe, where at least half of discarded plastics collected for ‘recycling’ were instead exported to China and SE Asia. Every year, an increasing proportion of these plastics (in the order of millions of tons) enter and accumulate in our waterways and oceans. In riverine and marine systems, the presence of micro to macroplastic debris has generated a growing and persistent threat to the environment and ecosystems, as well as an urgent and multi-dimensional challenge for our society.

Methods for resource-efficient and large-scale detection and monitoring of plastic litter are still relatively new. However, in the last few years, they have blossomed across technologies and environments - from mounted cameras to drones to satellites, and from lakes and rivers to coastal waters and open oceans. These new technologies can be crucial to fill in the gaps between limited in situ observations and global models, allowing coverage across fine as well as large spatial scales, and over long time periods. We invite abstracts describing the use of cameras, drones, satellites and other remote sensing techniques to observe and monitor riverine and marine plastics. We also welcome work describing or demonstrating new approaches, methods and algorithms to improve the use of cameras and sensors for plastic detection on (and in) water.

Co-organized by EOS7/GI4/HS12/OS4
Convener: Lauren BiermannECSECS | Co-conveners: Katerina KikakiECSECS, Cecilia MartinECSECS, Irene RuizECSECS, Tim van Emmerik
vPICO presentations
| Thu, 29 Apr, 13:30–14:15 (CEST)

This session is organised by the EGU Earth and Space Sciences Division to honour the recipients of the Ian McHarg Medal and the Early Career Scientist Award.

The Ian McHarg Medal is awarded for distinguished research in information technology applied to Earth and space sciences. It is named after Ian McHarg (1920-2001), a pioneer of the concept of ecological planning, who set forth the basic concepts of what was to become Geographic Information Systems (GIS).

The Earth and Space Science Informatics Division’s Outstanding Early Career Scientists is awarded for outstanding contributions to the field by researchers early in their career.

Convener: Jens Klump | Co-convener: Jane Hart
| Tue, 20 Apr, 10:30–12:15 (CEST)
Division meeting for Earth & Space Science Informatics (ESSI)
Convener: Jens Klump
Tue, 20 Apr, 13:30–14:30 (CEST)

Public information:
This networking events gives you the opportunity to get to know your peers belonging to the ESSI community. We will be discussing two topics proposed by the ESSI ECS community over the weeks before the General Assembly: the challenge and opportunities raising from attending (virtual) conferences in geosciences, and the importance of scientific error reporting culture.
This meeting is also the perfect moment to ask your peers careers advice, start new research collaboration, or having a low-key chat.
Convener: Federico AmatoECSECS
Tue, 27 Apr, 12:00–13:00 (CEST)

Public information:
This networking event gives you the opportunity to get to know your peers belonging to the ESSI community. We want to hear about your experiences at #vEGU21 and look ahead towards EGU 2022.
Conveners: Federico AmatoECSECS, Jens Klump, Jane Hart
Thu, 29 Apr, 12:30–13:30 (CEST)

ESSI1 – Community-driven challenges and solutions dealing with Informatics

Programme group scientific officer: Kerstin Lehnert

ITS4.4/AS4.1 EDI

There are many ways in which machine learning promises to provide insight into the Earth System, and this area of research is developing at a breathtaking pace.
Unsupervised, supervised as well as reinforcement learning are now increasingly used to address Earth system related challenges.
Machine learning could help extract information from numerous Earth System data, such as satellite observations, as well as improve model fidelity through novel parameterisations or speed-ups. This session invites submissions spanning modelling and observational approaches towards providing an overview of the state-of-the-art of the application of these novel methods

Co-organized by CL5.2/ESSI1/NP4
Convener: Julien Brajard | Co-conveners: Peter Düben, Redouane Lguensat, Francine Schevenhoven, Maike SonnewaldECSECS
vPICO presentations
| Fri, 30 Apr, 11:00–17:00 (CEST)

Source of most progress in artificial intelligence (AI) and machine learning (ML) can be traced back to data. Data, specifically, large-scale and openly-accessible training data are critical in adoption and acceleration of ML. While there are successful applications of ML in Earth science, the wider adoption of ML has been limited. Access to high-quality labeled training data is required to entice ML practitioners to tackle supervised learning problems in Earth science. However, creating labeled data that scales to support ML models is still a bottleneck and new strategies to increase the size and diversity of training datasets need to be explored. Additionally, enabling discovery and open sharing of existing training data and corresponding models to enable reproducibility of research and minimize duplication is a challenge.

This session seeks submissions from ML practitioners and data curators using different approaches to create labeled training data, catalog training data and models, and provide search, discovery and distribution of training data and models.

Co-organized by GI2
Convener: Manil MaskeyECSECS | Co-conveners: Hamed AlemohammadECSECS, Anirudh KoulECSECS, Rahul Ramachandran, Nicolas Longépé
vPICO presentations
| Wed, 28 Apr, 15:30–16:15 (CEST)

Geostatistical methods are commonly applied in the Water, Earth and Environmental sciences to quantify spatial variation, produce interpolated maps with quantified uncertainty and optimize spatial sampling designs. Space-time geostatistics explores the dynamic aspects of environmental processes and characterise the dynamic variation in terms of correlations. Geostatistics can also be combined with machine learning and mechanistic models to improve the modelling of real-world processes and patterns. Such methods are used to model soil properties, produce climate model outputs, simulate hydrological processes, and to better understand and predict uncertainties overall. Big data analysis and data fusion have become major topics of research due to technological advances and the abundance of new data sources from remote and proximal sensing as well as a multitude of environmental sensor networks. Methodological advances, such as hierarchical Bayesian modeling, machine learning, sparse Gaussian processes, local interaction models, as well as advances in geostatistical software modules in R and Python have enhanced the geostatistical toolbox.

This session aims to provide a forum where scientists from different disciplines can present and discuss innovative geostatistical methods targeting important problems in the Water, Earth and Environmental sciences. We also encourage contributions focusing on real-world applications of state-of-the-art geostatistical methods.

The topics of interest include:
1) Space-time geostatistics for hydrology, soil, climate system observations and modelling
2) Hybrid methods: Integration of geostatistics with optimization and machine learning approaches
3) Advanced parametric and non-parametric spatial estimation and prediction techniques
4) Big spatial data: analysis and visualization
5) Optimisation of spatial sampling frameworks and space-time monitoring designs
6) Algorithms and applications on Earth Observation Systems
7) Data Fusion, mining and information analysis
8) Geostatistical characterization of uncertainties and error propagation
9) Bayesian geostatistical analysis and hierarchical modelling
10) Functional data analysis approaches to geostatistics
11) Multiple point geostatistics

This session is co-sponsored by the International Association for Mathematical Geosciences (IAMG), https://www.iamg.org/

Co-organized by ESSI1/GI2/SSS10
Convener: Emmanouil VarouchakisECSECS | Co-conveners: Gerard Heuvelink, Dionissios Hristopulos, R. Murray Lark, Alessandra MenafoglioECSECS, Gerald A Corzo P, András Bárdossy, Panayiotis DimitriadisECSECS
vPICO presentations
| Mon, 26 Apr, 13:30–17:00 (CEST)

Detailed maps of the seabed, portraying the spatial distribution of geomorphic features, substrates, and habitats, are used for a wide range of environmental, scientific, and economic maritime applications. These maps are the scientific basis for informed ocean and coastal management at local to regional scales, and thereby provide cornerstones to national and international nature-conservation policies. Fundamental to seabed mapping are acoustic remote-sensing technologies, which include singlebeam and multibeam echosounders, along with sidescan, interferometric, and synthetic-aperture sonars. These are deployed on various platforms including crewed and uncrewed surface and underwater vessels. In relatively shallow and transparent waters, optical methods such as aircraft and satellite-based remote sensing and LiDAR are employed with increasing success. Innovative processing and classification software, image analysis, machine and deep-learning applications are advancing developments in seabed-recognition techniques, the application of which is increasing the resolution and confidence in the maps produced. We welcome submissions that provide insights into new developments, methods, and results in the field of seabed mapping and classification. This session also aims to showcase a range of applications for these datasets.

Co-organized by ESSI1/OS4
Convener: Markus Diesing | Co-conveners: Maria Judge, Benjamin MisiukECSECS, Rachel Nanson
vPICO presentations
| Thu, 29 Apr, 09:00–10:30 (CEST)

Most of the processes studied by geoscientists are characterized by variations in both space and time. These spatio-temporal phenomena have been traditionally investigated using linear statistical approaches, as in the case of physically-based models and geostatistical models. Additionally, the rising attention toward machine learning, as well as the rapid growth of computational resources, opens new horizons in understanding, modeling, and forecasting complex spatio-temporal systems through the use of stochastics non-linear models.

These issues are particularly relevant in the field of performance evaluations of Earth Systems Science Prediction (ESSP) systems. A central issue in this domain deals with the representativeness of observational data used for evaluation, which are often not representative of the physical structures that are being predicted. While many large spatial and temporal observations datasets can help provide this information, adequate tools to integrate these large datasets to provide meaningful physical insights on the strengths and weaknesses of predicted fields are required. Other challenges deal with the large storage volumes to handle model simulations, large spatio-temporal datasets, and verification statistics which are difficult to maintain.

This session aims at exploring the new challenges and opportunities opened by the spread of data-driven statistical learning approaches in Earth and Soil Sciences. We invite cutting-edge contributions related to methods of spatio-temporal geostatistics or data mining on topics that include, but are not limited to:
- meaningful and informative model evaluation frameworks and platforms for ESSP;
- advances in spatio-temporal modeling using geostatistics and machine learning;
- uncertainty quantification and representation;
- innovative techniques of knowledge extraction based on clustering, pattern recognition and, more generally, data mining.

The main applications will be closely related to the research in Earth system science and quantitative geography. A non-complete list of possible applications includes:
- weather and climate (e.g. numerical weather prediction, hydrologic prediction, climate prediction and projection);
- natural and anthropogenic hazards (e.g. floods; landslides; earthquakes; wildfires; air pollution);
- interaction between geosphere and anthroposphere (e.g. land degradation; urban sprawl);
- socio-economic sciences (e.g. census data; transport; commuter traffic).

This is a merged session of “Spatio-temporal data science: theoretical advances and applications in computational geosciences” and “Innovative Evaluation Frameworks and Platforms for Weather and Climate Research”.

Co-organized by GI2/NP4
Convener: Federico AmatoECSECS | Co-conveners: Jerome Servonnat, Daniela Castro-CamiloECSECS, Fabian GuignardECSECS, Christopher KadowECSECS, Paul Kucera, Luigi Lombardo, Marj ToniniECSECS
vPICO presentations
| Mon, 26 Apr, 09:00–10:30 (CEST)

This interdisciplinary session welcomes contributions on novel conceptual and/or methodological approaches and methods for the analysis and statistical-dynamical modeling of observational as well as model time series from all geoscientific disciplines.
Methods to be discussed include, but are not limited to linear and nonlinear methods of time series analysis. time-frequency methods, statistical inference for nonlinear time series, including empirical inference of causal linkages from multivariate data, nonlinear statistical decomposition and related techniques for multivariate and spatio-temporal data, nonlinear correlation analysis and synchronisation, surrogate data techniques, filtering approaches and nonlinear methods of noise reduction, artificial intelligence and machine learning based analysis and prediction for univariate and multivariate time series.
Contributions on methodological developments and applications to problems across all geoscientific disciplines are equally encouraged. We particularly aim at fostering a transfer of new methodological data analysis and modeling concepts among different fields of the geosciences.


Sub-Session "Mathematical Climatology and Space-time Data Analysis" (Abdel Hannachi, Amro Elfeki, Christian Franzke, Muhammad Latif, Carlos Pires)

The recent progress in mathematical methods to solve various problems in weather & climate nonlinear dynamics and data analysis calls for the need to develop a new session that focus on those methods. Novel and powerful mathematical methods have been developed and used in different subjects of climate. Because those methods are used within specific contexts they go unnoticed most of the time by climate researchers. The proposed new session will provide the opportunity to climate scientists and researchers working on developing mathematical methods for climate to come together and present their findings in a transparent way. This will also be easily accessible to other climate scientists who look for, and are interested in specific methods to solve their problems.
Contributions are encouraged from researchers working on mathematical methods and their application to weather and climate. We particularly welcome contributions on optimization, dimension reduction and data mining, space-time patterns identification, machine learning, statistical prediction modelling, nonlinear methods , Bayesian statistics, and Monte-Carlo Markov Chain (MCMC) methods in stochastic modelling.

Co-organized by BG2/CL5.2/ESSI1/GI2/HS3/SM3/ST2
Convener: Reik Donner | Co-conveners: Tommaso Alberti, Giorgia Di CapuaECSECS, Federica GugoleECSECS, Andrea Toreti
vPICO presentations
| Thu, 29 Apr, 09:00–10:30 (CEST)

Machine learning (ML) is now widely used across Hydrology and the broader Earth Sciences and especially its subfield deep learning (DL) has recently enjoyed increased attention.. This session highlights the continued integration of ML, and its many variants, including deep learning (DL), into traditional and emerging Hydrology-related workflows. Abstracts are solicited related to novel theory development, novel methodology, or practical applications of ML and DL in hydrological modeling. This might include, but is not limited to, the following:

(1) Development of novel DL models or modeling workflows.
(2) Integrating DL with process-based models and/or physical understanding.
(3) Improving understanding of the (internal) states/representations of ML/DL models.
(4) Understanding the reliability of ML/DL, including under nonstationarity.
(5) Deriving scaling relationships or process-related insights with ML/DL.
(6) Modeling human behavior and impacts on the hydrological cycle.
(7) Hazard analysis, detection, and mitigation.
(8) Natural Language Processing in support of models and/or modeling workflows

Co-organized by ESSI1/NP4
Convener: Frederik KratzertECSECS | Co-conveners: Claire BrennerECSECS, Pierre Gentine, Daniel KlotzECSECS, Grey Nearing
vPICO presentations
| Thu, 29 Apr, 15:30–17:00 (CEST)

Hydroinformatics has emerged over the last decades to become a recognised and established field of independent research within the hydrological sciences. Hydroinformatics is concerned with data acquisition, development and hydrological application of mathematical modelling, information technology, systems science and computational intelligence tools. We also have to face the challenges of the so-called Big Data: large data sets, both in size and complexity. Methods and technologies for data handling, visualization and knowledge acquisition are often referred to as Data Science.

The aim of this session is to provide an active forum in which to demonstrate and discuss the integration and appropriate application of emergent computational technologies in a hydrological modelling context. Topics of interest are expected to cover a broad spectrum of theoretical and practical activities that would be of interest to hydro-scientists and water-engineers. We aim to address the following classes of methods and technologies:

* Predictive and analytical models based on the methods of statistics, computational intelligence, machine learning : neural networks (including deep learning), fuzzy systems, genetic programming, cellular automata, chaos theory, etc.
* Innovative sensing techniques: satellites, gauges and citizens (crowdsourcing)
* Methods for the analysis of complex data sets, including remote sensing data: principal and independent component analysis, time series analysis, information theory, etc.
* Specific concepts and methods of Big Data and Data Science
* Optimisation methods associated with heuristic search procedures: various types of evolutionary algorithms, randomised and adaptive search, etc.
* Applications of systems analysis and optimisation in water resources
* Hybrid modelling involving different types of models both process-based and data-driven, combination of models (multi-models), etc.
* Data assimilation and model reduction in integrated modelling
* Novel methods of analysing model uncertainty and sensitivity
* Software architectures for linking different types of models and data sources

Applications could belong to any area of hydrology or water resources: rainfall-runoff modelling, flow forecasting, sedimentation modelling, analysis of meteorological and hydrologic data sets, linkages between numerical weather prediction and hydrologic models, model calibration, model uncertainty, optimisation of water resources, etc.

Co-organized by ESSI1/NH1
Convener: Dimitri Solomatine | Co-conveners: Ghada El Serafy, Amin Elshorbagy, Dawei Han, Thaine H. Assumpção, Fernando Nardi, Serena CeolaECSECS, Maurizio Mazzoleni
vPICO presentations
| Fri, 30 Apr, 09:00–12:30 (CEST)

Clustering analysis is a well-known exploratory task for partitioning databases into smaller groups based on patterns or inherent similarity in data. Clustering methods have found many applications in many disciplines due to growing interest in unravelling the hidden and meaningful patterns that exist in large amounts of available data. Due to its unsupervised nature, clustering data is a complex task that requires attention to optimal choice alternatives regarding methods, model parameters and performance metrics. However, the suitability of clustering algorithms depends on their application. Different methods and approaches co-exist in a large pool. The challenge is to obtain application-specific insights while enabling a practical knowledge perspective for benchmarking. There are still research gaps in the wider clustering literature, and hydrology-specific knowledge is fragmented and difficult to find.

In hydrology, unsupervised classification of multivariate data is often used but typically in rather basic forms and as an intermediate step. Recently, the number of studies using clustering methods has rapidly increased. However, a clear and integrative vision on clustering algorithms is currently missing. Despite advances in other fields, the scope of hydrological studies is limited. Knowledge exchange on hydrology-specific ways of dealing with the issues related to clustering is needed.

The aim of this session is to explore theoretical and conceptual underpinnings of well-known clustering methods, offer fresh insights into applications of new clustering methods, gain thorough understanding of pearls and pitfalls in clustering algorithms, provide a critical overview of the main challenges associated with data clustering process, discuss major research trends and highlight open research issues. It is expected to improve scientific practice within the hydrology domain, and foster scientific debate on benchmarking in cluster analysis.

We invite contributions (case studies, comparative analyses, theoretical experiments) on a wide range of topics including (but not limited to): hard vs fuzzy clustering; comparison of clustering algorithms; benchmarking in cluster analysis; clustering as an exploratory tool vs clustering as a hypothesis testing tool; determination of number of clusters; selecting variables to cluster upon; evaluation of clustering performance; alternative clustering methods (sequential, evolutionary, deep, ensemble, etc.)

Public information:
Please join us in the first year of this new Hydroinformatics session at #vEGU21! We are looking forward to your participation!:)
Co-organized by ESSI1/NP4
Convener: Nilay Dogulu | Co-conveners: Svenja FischerECSECS, Wouter KnobenECSECS
vPICO presentations
| Thu, 29 Apr, 13:30–14:15 (CEST)

Understanding Earth’s system natural processes, especially in the context of global climate change, has been recognised globally as a very urgent and central research direction which need further exploration. With the launch of new satellite platforms with a high revisit time, combined with the increasing capability for collecting repetitive ultra-high aerial images, through unmade aerial vehicles, the scientific community have new opportunities for developing and applying new image processing algorithms to solve old and new environmental issues.

The purpose of the proposed session is to gather scientific researchers related to this topic aiming to highlight ongoing researches and new applications in the field of satellite and aerial time-series imagery. The session focus is on presenting studies aimed at the development or exploitation of novel satellite times series processing algorithms, and applications to different types of remote sensing data for investigating longtime processes in all branches of Earth (sea, ice, land, atmosphere).

The conveners encourage both applied and theoretical research contributions focusing in novel methods and applications of satellite and aerial time-series imagery all disciplines of geosciences, including both aerial and satellite platforms and data acquired in all regions of the electromagnetic spectrum.

Co-organized by GI3
Convener: Ionut Cosmin Sandric | Co-conveners: Dionissios Hristopulos, George P. Petropoulos, Marina VîrghileanuECSECS, Milan Žukovič
vPICO presentations
| Mon, 26 Apr, 11:00–12:30 (CEST)
ITS4.2/PS4.4 EDI

The increasing amount of data from an increasing number of spacecraft in our solar system shouts out for new data analysis strategies. There is a need for frameworks that can rapidly and intelligently extract information from these data sets in a manner useful for scientific analysis. The community is starting to respond to this need. Machine learning, with all of its different facets, provides a viable playground for tackling a wide range of research questions. Algorithms to automatically detect and classify special features in time series data of the solar wind or in 2D images of planetary surfaces are examples of where machine learning approaches can support and improve existing models. Further, modern learning methods can encode properties of interest in lower dimensional space, and thus making them more searchable.

We encourage submissions dealing with machine learning approaches of all levels in planetary sciences and heliophysics. The aim of this session is to provide an overview of the current efforts to integrate machine learning technologies into data driven space research, to highlight state-of-the art developments and to generate a wider discussion on further possible applications of machine learning.

Co-organized by ESSI1/ST1
Convener: Mario D'Amore | Co-conveners: Ute Amerstorfer, Sahib JulkaECSECS, Angelo Pio Rossi
vPICO presentations
| Fri, 30 Apr, 09:00–10:30 (CEST)

Cartography and mapping are at this time the only means to conduct basic geoscientific studies (on planetary surfaces). The field of Planetary Cartography and Mapping has been stepping out of its niche existence in the last 15 years due to the availability of an unprecedented amount of new data from various planetary exploration missions from different countries and the advent of internet technology that allows to manage, process, distribute, analyze, and collaborate efficiently. Geospatial information system technology plays a pivotal role in this process and essentially all planetary surface science research in this field benefits from this technology and frequent new developments.
With the availability of data and connection, however, comes the challenge of organizing and structuring available data and research, such as maps and newly derived and refined (base) data that is about to enter its new research life cycle.
This session welcomes presentations covering planetary data and its development into cartographic products and maps. This covers aspects of data archival, dissemination, structuring, analyzing, filtering, visualizing, collaboration, and map compilation but is not limited to these topics.
It should also be emphasized that the exchange of knowledge and experiences from the Earth Sciences would be highly beneficial for the Planetary Data Sciences.

Co-organized by ESSI1/GI3
Convener: Andrea Nass | Co-conveners: Alessandro Frigeri, Angelo Pio Rossi, Stephan van Gasselt, Valentina GalluzziECSECS
vPICO presentations
| Mon, 26 Apr, 09:00–10:30 (CEST)

Homo sapiens as product of the natural evolution of the biosphere , was created as a species in the geochemical conditions of the virgin biosphere. After successful colonization of the adverse environmental conditions around the whole world, he started its transformation first by land cultivation, urbanization and now by creation a new habitat exclusively for man. All these have led to a significant geochemical transformation of the virgin biosphere. Nowadays, a growing variety of anthropogenic sources of pollution requires, not only a constant monitoring of the chemical state of soil, water, air and food products, but also the development of spatially differentiated approaches to assessing the health risk by evaluation of diseases’ provocation. To solve this problem, it is necessary to develop effective approaches towards interpretation of spatially related geochemical and medical information. In this way we propose to discuss: 1) the global trends of health transformation in geochemical environment of actual noosphere; 2) different approaches to assess the risk of diseases of geochemical nature in different countries; 3) criteria for determining pollution level depending on geochemical constrains and health effects; 4) the problem of mapping of risk zones, related to negative medical effects due to both excess and deficiency of certain chemical elements or compounds.

Co-organized by BG2/ESSI1
Convener: Elena Korobova | Co-conveners: Jaume Bech, Liudmila KolmykovaECSECS
vPICO presentations
| Fri, 30 Apr, 09:00–10:30 (CEST)

This session invites presentations on simulations of weather and climate models running at high resolution. This includes state-of-the-art storm-resolving simulations (e.g. from the DYAMAND project), high-resolution climate models (e.g. from the PRIMAVERA project) but also large-eddy simulations and high-resolution ocean modelling. Presentations can cover developments to improve model fidelity (e.g. via improved parametrisations), detailed studies of modelled phenomena (e.g. tropical cyclones) but also computational and model development challenges (e.g. the use of GPUs, domain-specific languages or the development of new dynamical cores).

Co-organized by CL5.2/ESSI1/OS4
Convener: Peter Düben | Co-conveners: Daniel Klocke, Florian Ziemen
vPICO presentations
| Thu, 29 Apr, 09:00–11:45 (CEST)

Remote sensing measurements, acquired using different platforms - ground, UAV, aircraft and satellite - have increasingly become rapidly developing technologies to study and monitor Earth surface, to perform comprehensive analysis and modeling, with the final goal of supporting decision systems for ecosystem management. The spectral, spatial and temporal resolutions of remote sensors have been continuously improving, making environmental remote sensing more accurate and comprehensive than ever before. Such progress enables understanding multiscale aspects of high-risk natural phenomena and development of multi-platform and inter-disciplinary surveillance monitoring tools. The session welcomes contributions focusing on present and future perspectives in environmental remote sensing, from multispectral/hyperspectral optical and thermal sensors. Applications are encouraged to cover, but not limited to, the monitoring and characterization of environmental changes and natural hazards from volcanic and seismic processes, landslides, and soil science. Specifically, we are looking for novel solutions and approaches including the topics as follows: (i) state-of-the-art techniques focusing on novel quantitative methods; (ii) new applications for state-of-the-art sensors, including UAVs and other close-range systems; (iii) techniques for multiplatform data fusion.

Co-organized by ESSI1/GMPV9/NH6
Convener: Annalisa CappelloECSECS | Co-conveners: Sabine Chabrillat, Gaetana Ganci, Gabor KereszturiECSECS, Veronika Kopackova
vPICO presentations
| Thu, 29 Apr, 11:00–12:30 (CEST), 13:30–14:15 (CEST)

Space-based measurements of the Earth System, including its atmosphere, oceans, land surface, cryosphere, biosphere, and interior, require extensive prelaunch and post launch calibration and validation activities to ensure scientific accuracy and fitness for purpose throughout the 
lifetime of satellite missions. This requirement stems from the need to demonstrate unambiguously that the space-based measurements, typically based on engineering measurements by the detectors (e.g. photons), are sensitive to and can be used to retrieve reliably the geophysical and/or biogeochemical parameters of interest at locations across the Earth.
Most geophysical parameters vary in time and space, and the retrieval algorithms used must be accurate under the full range of conditions. Calibration and validation over the lifetime of missions assure that any long-term variation in observation can be unambiguously tied to the evolution of the Earth system. Such activities are also critical in ensuring that measurements from different satellites can be inter-compared and used seamlessly to create long-term multi-instrument/multi-platform data sets, which serve as the basis for large-scale international science investigations into topics with high societal or environmental importance. Examples of such investigations include the ice mass balance of Greenland, monitoring the evolution of sea ice and snow cover in the Arctic, assessing sinks and sources of methane in the Arctic and improving our knowledge of the terrestrial carbon cycle through multi-sensor forest biomass mapping. This session seeks presentations on the use of surface-based, airborne, and/or space-based observations to prepare and calibrate/validate space-based satellite missions measuring our Earth system. A particular but not exclusive focus will be on activities carried out jointly by NASA and ESA as part of their Joint Program Planning Group Subgroup on calibration and validation and field activities.

Co-organized by GI3
Convener: Malcolm W. J. Davidson | Co-conveners: Maurice Borgeaud, Jack Kaye
vPICO presentations
| Thu, 29 Apr, 15:30–17:00 (CEST)

Geomorphometry and geomorphological mapping are important tools used for understanding landscape processes and dynamics on Earth and other planetary bodies. The recent rapid advances in technology and data collection methods has made available vast quantities of geospatial data for such morphometric analysis and mapping, with the geospatial data offering unprecedented spatio-temporal range, density, and resolution, but it also created new challenges in terms of data processing and analysis.

This inter-disciplinary session on geomorphometry and landform mapping aims to bridge the gap between process-focused research fields and the technical domain where geospatial products and analytical methods are developed. The increasing availability of a wide range of geospatial datasets requires the continued development of new tools and analytical approaches as well as landform/landscape classifications. However, a potential lack of communication across disciplines results in efforts to be mainly focused on problems within individual fields. We aim to foster collaboration and the sharing of ideas across subject-boundaries, between technique developers and users, enabling us as a community to fully exploit the wealth of geospatial data that is now available.

We welcome perspectives on geomorphometry and landform mapping from ANY discipline (e.g. geomorphology, planetary science, natural hazard assessment, computer science, remote sensing). This session aims to showcase both technical and applied studies, and we welcome contributions that present (a) new techniques for collecting or deriving geospatial data products, (b) novel tools for analysing geospatial data and extracting innovative geomorphometric variables, (c) mapping and/or morphometric analysis of specific landforms as well as whole landscapes, and (d) mapping and/or morphometric analysis of newly available geospatial datasets. Contributions that demonstrate multi-method or inter-disciplinary approaches are particularly encouraged. We also actively encourage contributors to present tools/methods that are “in development”.

Co-organized by ESSI1/GI6/NH6/PS7
Convener: Giulia Sofia | Co-conveners: Benjamin ChandlerECSECS, Susan Conway, Stuart GrieveECSECS, John K. Hillier
vPICO presentations
| Mon, 26 Apr, 09:00–12:30 (CEST)

Vetted probabilistic earthquake forecasts can contribute to more earthquake-resilient societies. Forecasts underpin seismic hazard assessments and thus determine building and life safety. They also provide scientifically sound information about the time-dependence of earthquake potential before, during and after earthquake sequences. To ensure forecasts are trustworthy and to assess the scientific hypotheses underlying the forecasts, models should be tested both retrospectively and prospectively (i.e., against yet-to-be-collected data). For this purpose, the Collaboratory for the Study of Earthquake Predictability (CSEP) provides tools and methods for testing the consistency and precision of earthquake forecasts. This session welcomes contributions that showcase advances in the science of earthquake forecasting and model testing. These can include: new approaches for identifying precursory activity (e.g. b-value variations, aseismic slip transients); forecasts based on empirical machine-learning or physical stress-transfer algorithms; applications of models to earthquake sequences around the globe; advances in model evaluation techniques; or contributions to software tools for model developers. Presentations may also highlight progress of community efforts, such as the EU H2020 project RISE (Real-time earthquake rIsk reduction for a reSilient Europe, www.rise-eu.org) and other initiatives.

Co-organized by ESSI1/NH4
Convener: Maximilian Werner | Co-conveners: Warner Marzocchi, Danijel Schorlemmer
vPICO presentations
| Thu, 29 Apr, 13:30–14:15 (CEST)

Innovative forward and inverse modeling techniques, advances in numerical solvers and the ever-increasing power of high-performance compute clusters have driven recent developments in inverting seismic and other geophysical data to reveal properties of the Earth at all scales.

This session provides a forum to present, discuss and learn the state-of-the-art as well as future directions in seismic tomography, computational inverse problems, and uncertainty quantification.

We welcome contributions focusing on, but not limited to:

- innovative modeling techniques and advancements in numerical solvers,
- seismic tomography and full-waveform inversion from local to global scales,
- multi-scale, multi-parameter and joint inversions of Earth structure and sources,
- statistical inverse problems and uncertainty quantification,
- homogenization and effective medium theory,
- machine learning algorithms for seismic problems,
- big data (seismic & computational) problems on emerging HPC architectures.

Co-organized by ESSI1/PS7
Convener: Christian BoehmECSECS | Co-convener: Ebru Bozdag
vPICO presentations
| Mon, 26 Apr, 13:30–15:00 (CEST)

ESSI2 –  Infrastructures across the Earth and Space Sciences

Programme group scientific officer: Horst Schwichtenberg


The preconditions for interdisciplinary research are set by building bridges between silos of deep, disciplinary-specific knowledge. One way of building these bridges is via collaboration around shared technologies, as scientists need sophisticated infrastructure, tools, services, and data.

An inclusive, integrated approach to Open and FAIR is required, with consistent policies, standards and guidelines covering the whole research data lifecycle, addressing also basic legal frameworks e.g. for intellectual property and licensing. At the same time, the research community needs to further develop a common understanding of best practices and appropriate scientific conduct adequate for this new era, and could still better share tools and techniques.
With the help of newly established cloud-based e-infrastructures like EOSC, AOSP, ARDC, ESIP or similar ones in all parts of the world, scientist, with the help of ICT experts are able to access large scale supporting e-Infrastructure to run workflows, access data services, visualisation and modeling tools to improve scientific results and achieve breakthroughs in understanding the Planet Earth System.

This session will present examples from different fields of expertise in the Environmental and Earth system domain (research and e-infrastructures, repositories and data hubs, software frameworks, interdisciplinary data users, global and domain-specific initiatives, etc.), who are demonstrating the effective use of these infrastructures, their services, quality checks and tools. In that sense, this session also supports tackling the existing and upcoming challenges in the evolution of an integrated, Open and FAIR research ecosystem.

Public information:
The session will present examples from different fields of expertise in the Environmental and Earth system domain (research and e-infrastructures, repositories and data hubs, software frameworks, interdisciplinary data users, global and domain-specific initiatives, etc.), who are demonstrating the effective use of cloud-based e-infrastructures, their services, quality checks and tools. In that sense, this session also supports tackling the existing and upcoming challenges in the evolution of an integrated, Open and FAIR research ecosystem.
Convener: Anca Hienola | Co-conveners: Amber Budden, Jacco Konijn, Susan Shingledecker, Lesley Wyborn
vPICO presentations
| Tue, 27 Apr, 11:00–12:30 (CEST)

The leading-edge computational and data facilities of the forthcoming Exascale era will bring a variety of currently inaccessible Solid Earth computational challenges within reach. Firstly, many Geoscience calculations that are currently unaffordable due to the size of the computational domain, necessary model resolution, or insurmountable data requirements, will become increasingly tractable. Secondly, Exascale supercomputing will facilitate probabilistic framework approaches to ever larger and more complex problems, through larger ensembles of model realizations and incorporating high-end data inversion, model data assimilation, and uncertainty quantification. Finally, Urgent High Performance Computing will become a reality with complex numerical simulations, potentially with large model ensembles, becoming possible in near real-time. Numerous natural hazards which pose a direct threat to human life and critical infrastructure (e.g. earthquakes, volcanic eruptions, wildfire, landslides, and tsunamis) can require rapid and well-informed decision making in the emergency management process. The basis for these decisions is often provided by complex and data-intensive numerical models and we face a challenge of designing and implementing robust and powerful workflows (including computing, data management, sharing and logistics, and post processing) which present stakeholders with relevant and accurate results in a timely manner. This transdisciplinary session seeks contributions related to the preparation of codes for Exascale, geoscience workflows and services, adapting codes for emerging hybrid hardware architectures, e-services demanding Urgent HPC, early warning and forecasts for geohazards, hazard assessment, and high-performance data analytics. Examples include codes and workflows for near real-time seismic simulations, full-waveform seismic inversion, ensemble-based forecasts, faster than real-time tsunami simulation, magneto-hydrodynamics simulations, and physics-based hazard assessment.
This session is organized by the Center of Excellence for Exascale in Solid Earth (ChEESE) with the support of the European Plate Observatory System (EPOS), the EUDAT Collaborative Data Infrastructure (EUDAT CDI) and the Partnership for Advanced Computing in Europe (PRACE). The organisers plan to submit a proposal for an Advances in Geosciences (ADGEO) EGU General Assembly special volume on one or more EGU Divisions.

Public information:
Many problems in modern geosciences require vast and complex numerical models. These may require great volumes of data and complex data logistics to resolve geophysical processes over many scales, vast numbers of simulations to adequately model uncertainty, or urgent computation to forecast impending hazards. Such applications require High Performance Computing (HPC) and/or Data Analysis (HPDA). On the verge of Exascale computing, this transdisciplinary session seeks to close the gap between geoscience needs and the codes, workflows, and data logistics needed to exploit Exascale HPC.
Co-organized by EMRP2/ESSI2/GD8/GMPV1/SM8
Convener: Arnau Folch | Co-conveners: Steven Gibbons, Marisol Monterrubio-Velasco, Jean-Pierre Vilotte, Sara Aniko Wirp
vPICO presentations
| Thu, 29 Apr, 11:00–11:45 (CEST)

Earth Sciences depend on detailed multi-variate measurements and investigations to understand the physical, geological, chemical, biogeochemical and biological processes of the Earth. Making accurate prognoses and providing solutions for current questions related to climate change, water, energy and food security are important requests towards the Earth Science community worldwide. In addition to these society-driven questions, Earth Sciences are still strongly driven by the eagerness of individuals to understand processes, interrelations and tele-connections within and between small sub-systems and the Earth System as a whole. Understand and predict temporal and spatial changes in the above mentioned Micro- to Earth spanning scales is the key to understand Earth ecosystems; we need to utilize high resolution data across all scales in an integrative/holistic approach. Using Big Data, which are often distributed and particularly very in-homogenous, has become standard practice in Earth Sciences and digitalization in conjunction with Data Science promises new discoveries.
The understanding of the Earth System as a whole and its sub-systems depends on our ability to integrate data from different disciplines, between earth compartments, and across interfaces. The need to advance Data Science capabilities and to enable earth scientists to follow best possible workflows, apply methods, and use computerized tools properly and in an accessible way has been identified worldwide as an important next step for advancing scientific understanding. This is particularly necessary to access knowledge contained in already acquired data, but which due to the limitations of data integration and joint exploration possibilities currently remains invisible. This session aims to bring together researchers from Data and Earth Sciences working on, but not limited to,
• SMART monitoring designs by dealing with advancing monitoring strategies to e.g. detect observational gaps and refine sensor layouts to allow better and statistically robust extrapolation
• Data management and stewardship solutions compliant with FAIR principles, including the development and application of real-time capable data management and processing chains
• Data exploration frameworks providing qualified data from different sources and tailoring available computational and visual methods to explore and analyse multi-parameter data generated through monitoring efforts/ model simulations

Co-organized by GI2
Convener: Jens Greinert | Co-conveners: Everardo González ÁvalosECSECS, Daniela Henkel, Patrick MichaelisECSECS
vPICO presentations
| Tue, 27 Apr, 09:00–10:30 (CEST)

Instrumentation and measurement technologies are currently playing a key role in the monitoring, assessment and protection of water resources.
This session focuses on measurement techniques, sensing methods and data science implications for the observation of water systems, given the strong link between measurement aspects and computational aspects, especially in the water sector.
This session aims at providing an updated framework of the observational techniques, data processing approaches and sensing technologies for water management and protection, giving also attention to today’s data science aspects, e.g. data analytics, big data, cloud computing and Artificial Intelligence.
We welcome contributions about field measurement approaches, development of new sensing techniques, low cost sensor systems and measurement methods enabling crowdsourced data collection also through social sensing. Therefore, water quantity and quality measurements as well as water characterization techniques are within the scope of this session.
Remote sensing techniques for the monitoring of water resources and/or the related infrastructures are also welcome.
Contributions dealing with the integration of data from multiple sources are solicited, as well as the design of ICT architectures (including IoT concepts) and of computing systems for the user-friendly monitoring of the water resource and the related networks.
Studies about signal and data processing techniques (including AI approaches) and the integration between sensor networks and large data systems are also very encouraged.

Co-organized by BG2/ESSI2/HS13
Convener: Andrea Scozzari | Co-conveners: Anna Di MauroECSECS, Francesco Soldovieri
vPICO presentations
| Fri, 30 Apr, 15:30–17:00 (CEST)

NEMO (Nucleus for European Modelling of the Ocean) is a state-of-the-art modelling framework of the ocean that includes components for the ocean dynamics, the sea-ice and the biogeochemistry, so as a nesting package allowing to set up zooms and a versatile data assimilation interface (see https://www.nemo-ocean.eu/).
NEMO is used by a large community in Europe and world-wide (~200 projects, ~100 publications each year) covering a wide range of applications : oceanographic research, operational oceanography, seasonal forecast and climate projections.
NEMO is in particular used in 6 Earth System Models within CMIP6 and in Copernicus Marine Services (CMEMS) model-based products.

This session will provide a forum to properly address the new scientific advances in numerical modelling of the ocean and their implication for NEMO developments associated with:
• Ocean dynamics at large to coastal scales, up to 1km resolution ;
• Ocean biogeochemistry
• Sea-ice
• New numerical schemes associated to energy conservation constraints
• High performance computing challenges and techniques

The session will cover both research and operationnal activities contributing to new analysis, ideas and developments of ocean numerical models.
Presentations of results based on new NEMO functionalities and new NEMO model configurations are welcome.

Co-organized by CL4/ESSI2, co-sponsored by CMEMS
Convener: Claire Levy | Co-conveners: Mike Bell, Jerome Chanut, Julien Le Sommer, Doroteaciro Iovino
vPICO presentations
| Mon, 26 Apr, 15:30–17:00 (CEST)

Global losses due to natural hazards have shown an increasing trend over the last decades, which is expected to continue due to growing exposure in disaster-prone areas and the effects of climate change. In response, recent years have seen greater worldwide commitment to reducing disaster risk. Working towards this end requires the implementation of increasingly effective disaster risk management (DRM) and financing strategies. These must necessarily be supported by reliable estimates of risk and loss before, during, and after a disaster. In this context, innovation plays a key role.
This session aims to provide a forum to the scientific, public and private discourse on the challenges to innovate DRM. We welcome submissions on the development and application of groundbreaking technologies, artificial intelligence and innovative modeling and visualization approaches for disaster risk assessment and DRM decision-making. This includes the quantification and mapping of natural hazard risks and their components (i.e. hazard, exposure, and vulnerability), as well as the forecasting of hazard and impacts prior to a disaster event, or as it is unfolding (in real- or near real-time). We are particularly interested in contributions covering one or more of the following thematic areas in the context of disaster risk assessment and reduction: artificial intelligence and machine learning, big data, remote sensing and earth observation, social media, volunteered geographic information (VGI), mobile applications, crowdsourcing, internet of things (IoT), and blockchain. We also welcome submissions exploring how these or other innovations can support real-world DRM strategies and translate into improved DRM decisions.

Co-organized by ESSI2
Convener: Rui FigueiredoECSECS | Co-conveners: Kai Schröter, Carmine Galasso, Mario Lloyd Virgilio Martina, Xavier Romão, Markus EnenkelECSECS, Clement Atzberger, Rahel Diro
vPICO presentations
| Mon, 26 Apr, 13:30–15:00 (CEST)

In 2020, the Japanese Aerospace Exploration Agency (JAXA) and the European Space Agency (ESA) signed an agreement on the “Cooperation for the Use of Synthetic Aperture Radar Satellites in Earth Science and Applications”. The cooperation focuses on the joint analysis of L-band data acquired by JAXA’s ALOS-2/PALSAR-2 satellite together with ESA’s Sentinel-1 C-band satellite data for various applications. Research areas include polar and ocean monitoring, snow water equivalent retrieval, forest and wetland monitoring, surface soil moisture and agriculture monitoring, as well as the monitoring of geohazards and urban areas.

The key objective of the JAXA-ESA cooperation is to develop a better understanding of the benefits of combining L-band and C-band data over various areas and for the different thematic applications. A comparison with ground-based campaign data is envisaged to validate the results. The research projects will provide important insights for the development of future (L-band) SAR satellite missions, such as JAXA’s ALOS-4 satellite and the High Priority Candidate Mission (HPCM) ROSE-L currently in development at ESA, as well as synergies with existing and future spaceborne C-band SAR missions including Sentinel-1 and Sentinel-1 Next Generation.

This jointly chaired session shall give the involved scientists the opportunity to present ongoing research and results and foster the collaboration and exchange between European, Japanese and international participants.

Organizers: Julia Kubanek (ESA), Shin-ichi Sobue (JAXA), Malcolm Davidson (ESA), Takeo Tadono (JAXA), Maurice Borgeaud (ESA)

Co-organized by GI3
Convener: Julia Kubanek | Co-conveners: Maurice Borgeaud, Shin-ich Sobue, Takeo Tadono
vPICO presentations
| Thu, 29 Apr, 13:30–15:00 (CEST)

ESSI3 – Open Science 2.0 Informatics for Earth and Space Sciences

Programme group scientific officer: Kirsten Elger


Digital data, software and samples are key inputs that underpin research and ultimately scholarly publications, and there are increasing expectations from policy makers and funders that they will be Open and FAIR (Findable, Accessible, Interoperable, Reusable). Open, accessible, high-quality data, software and samples are critical to ensure the integrity of published research and to facilitate reuse of these inputs in future scientific efforts. In Europe, adherence to the INSPIRE directive becomes gradually more enforced by national legislations, affecting also the data lifecycle in Earth and Environmental Sciences.

These issues and challenges get addressed at an increasing pace today, with journals changing their policies towards openness of data, samples and software connected to publications, and national, European and global initiatives and institutions developing more and more services around Open and FAIR data, covering curation, distribution and processing. Yet, researchers, as producers as well as users of data, products, and software, continue to struggle with the requirements and conditions they encounter in this rapidly evolving environment.

This session will showcase the range of practices with respect to the FAIR and Open paradigms in research infrastructures and research data repositories. It will also look at how research infrastructures and repositories assess FAIRness, the development and role of general standards, and the consequences for data publication and the integration of data, software and samples into the scholarly publication process.

In that sense, this session also supports tackling the existing and upcoming challenges in the evolution of an integrated, Open and FAIR research ecosystem.

Co-sponsored by AGU
Convener: Florian Haslinger | Co-conveners: Kirsten Elger, Shelley Stall, Katrin Seemeyer, Kristin Vanderbilt
vPICO presentations
| Tue, 27 Apr, 13:30–15:00 (CEST)

Earth science research has become increasingly collaborative through shared code and shared platforms. Researchers work together on data, software and algorithms to answer cutting-edge research questions. Teams also share these data and software with other collaborators to refine and improve these products. As data volumes continue to grow, researchers will need new platforms to both enable analysis at scale and to support the sharing of data and software.

Software is critical to the success of science. Creating and using Free and Open Source Software (FOSS) fosters contributions from the scientific community, creates a peer-reviewed and consensus-oriented environment, and promotes the sustainability of science infrastructures.

This session will look at how Free and Open Source Software (FOSS) and cloud-based architecture solutions support information sharing, scientific collaboration, scientific reproducibility and solutions that enable large-scale data analytics.

Co-organized by GI2, co-sponsored by AGU
Convener: Jens Klump | Co-conveners: Kaylin BugbeeECSECS, Horst Schwichtenberg, Anusuriya Devaraju, Wim Som de Cerff
vPICO presentations
| Wed, 28 Apr, 13:30–15:00 (CEST)

Significant investments are made globally in laboratory analytical research in the Earth and space sciences to extract new scientific insights from Earth and planetary materials. Expensive laboratory infrastructure and advanced instrumentation generates data at an ever increasing level of precision, resolution, and volume. Any data generated at any scale needs to be efficiently managed and losslessly transferred from instruments in “Private” domains to a “Collaboration” domains, where researchers can analyze and share these data as well as the analytical tools. Ultimately, the data need to be transferred to the “Public” domain, complete with all relevant information about the analytical process and uncertainty, and cross-references to originating samples and publications. Many solutions today are bespoke and inefficient, lacking, for example, unique identification of samples, instruments, and data sets needed to trace the analytical history of the data.

This session seeks contributions about new developments to achieve FAIR, scalable and sustainable access to analytical data from any laboratory instrument and domain at any scale (from an individual instrument in a geochemical lab to data measured with synchrotrons), and any stage from the initial collection of the sample through to the publication of the final data, including the use of persistent identifiers to uniquely identify samples, instruments, researchers, grants, data, etc. Papers are welcome on systems that transfer data/metadata directly from instruments to “collaborative storage areas” that facilitate sharing and processing of geochemical data, as well as systems that transfer data used in publications to relevant repositories that ensure long term persistence of data and enhanced reproducibility of geochemical research.

Public information:
Significant investments are made globally to study samples from the Earth, the Moon, and other planetary materials in research laboratories to extract new scientific insights about the history and state of our solar system. Expensive laboratory infrastructure and advanced instrumentation generates data at an ever increasing level of precision, resolution, and volume. This data needs to be efficiently managed and losslessly transferred from instruments in the lab, where the data are not accessible to others, to a “Collaboration” domain, where researchers can share and jointly analyze these data, to the “Public” domain, complete with all relevant information about the analytical process and uncertainty, and cross-references to originating samples and publications. Many solutions today are bespoke and inefficient, lacking, for example, unique identification of samples, instruments, and data sets needed to trace the analytical history of the data.

This session provides an overview on all facets of geochemical data management since the first “Editors Roundtable” in 2007, an initial meeting of editors, publishers, and database providers to implement consistent practices for reporting geochemical data in the literature or sharing these data in geochemical databases. What has happened since? Our presentations stretch from initiatives describing the full workflow support, to individual tools for data management in the lab, to specific data collections and data publication initiatives to the overarching aim of linking between systems and the need for standards.
Co-organized by GI2/GMPV1
Convener: Kirsten Elger | Co-conveners: Alexander Prent, Lesley Wyborn
vPICO presentations
| Fri, 30 Apr, 13:30–15:00 (CEST)

ESSI4 – Visualization for scientific discovery and communication

Programme group scientific officer: Jon Blower


Data visualization is fundamental to science: to discovery, to interpretation, and to communication. This is especially true in this era of big and complex datasets, increasing scientific specialization and the need to effectively communicate ideas and results to diverse audiences.

This session will explore innovations in science data visualization that support and advance elements of the scientific process – from exploration and analysis to discovery and communication. We invite a broad spectrum of science visualization breakthroughs that allow researchers and others to broaden their understanding of natural phenomena and communicate that understanding.

Topics to include (but not limited to):

- Visualizing massive datasets
- Combined visualization of multiple datasets
- Extracting new and/or additional meaning through visualization
- Visualization and human perception
- Focused research and development activities regarding visualization elements (e.g., colors, patterns, shading, 3D, etc.)
- New and inventive science visualization tools and applications (e.g., virtual, augmented and mixed reality: VR/AR/MR)

Public information:
Data visualization is fundamental to science: to discovery, to interpretation, and to communication. This is especially true in this era of big and complex datasets, increasing scientific specialization and the need to effectively communicate ideas and results to diverse audiences.

This session will explore innovations in science data visualization that support and advance elements of the scientific process – from exploration and analysis to discovery and communication. We will showcase science visualization breakthroughs that allow researchers and others to broaden their understanding of natural phenomena and communicate that understanding.

Topics include (but not limited to):
- Visualizing massive datasets
- Combined visualization of multiple datasets
- Extracting new and/or additional meaning through visualization
- Visualization and human perception
- Focused research and development activities regarding visualization elements (e.g., colors, patterns, shading, 3D, etc.)
- New and inventive science visualization tools and applications (e.g., virtual, augmented and mixed reality: VR/AR/MR)
Convener: Rick Saltus | Co-convener: Shayna Skolnik
vPICO presentations
| Wed, 28 Apr, 16:15–17:00 (CEST)

ESSI5 – General contributions

Programme group scientific officer: Jens Klump