Anyone entering the job market or looking for a new job after academia will confront the phrase ‘transferable skills’. PhD candidates and scientists are advised to highlight their transferable skills when applying for non-academic jobs, but it can be hard to know what these skills are. Similarly, for those looking to change scientific research areas or take a leap into a new field for their PhD, it is important to highlight your transferable skills. Big data analysis, communicating your findings, supervising, teaching, project management and budgeting are skills you might have from your research/science career. But there are many more. In this interactive workshop, we will start your journey of identifying your transferable skills and highlighting careers where these will be necessary!

Effective risk communication is crucial for enhancing public understanding and response to disaster risks. This short course is designed to equip students, early-career scientists, experienced researchers, and science communicators with advanced tools and strategies for effective risk communication. Participants will learn about fundamental principles of risk communication, cognitive biases, risk perception, and the use of media and social media in conveying risk information. The course will also address how to adapt communication strategies to different environments and audiences, beyond the traditional sharing of scientific data. Contributing to the European Commission’s disaster resilience goal no. 2 on ‘Prepare - Increasing risk awareness and preparedness of the population’ and the preparEU programme, the course will provide practical skills to improve risk communication efforts and foster more resilient communities. Attendees are welcome to join the scientific session and splinter meetings, creating a unified path for those interested in a comprehensive exploration of risk communication

The concepts and tools of algebraic topology can be applied to the evolution of systems in both phase space and physical space, as well as to the interesting back-and-forth excursions between these two spaces. The way that dynamics and topology interact is at the core of the present course.

Starting with the early contributions of knot theory to nonlinear dynamics, we introduce the templex, a novel concept in algebraic topology that considers a flow in physical or phase space with no restrictions to its dimensions, drawing on both homology groups and graph theory. The templex approach is illustrated through its application to paradigmatic chaotic attractors – like the Lorenz or Rössler attractors – as well as to non-chaotic flows. Applications to kinematic and dynamic models of the ocean gyres and to idealized models of the Atlantic Meridional Overturning Circulation (AMOC) are presented, along with the topological analysis of oceanographic time series derived from altimetric velocity fields. Lagrangian ocean analysis is a key element of the course.

The extension of the templex concept to the noise-perturbed chaotic attractors of random dynamical systems theory is presented, leading to the definition of topological tipping points (TTPs). TTPs enable the study of successive bifurcations of climate models beyond those known from the classical theory of autonomous dynamical systems, as well as of those more recently added by consideration of tipping points in nonautonomous systems.

We thus propose to start a journey through the mathematical concepts and tools that characterize the topological approach to nonlinear dynamics. This approach goes beyond purely metric, i.e., non-topological, descriptions of the mechanisms that are responsible for higher and higher versions of irregular behavior, from deterministic chaos to various forms of turbulence. These novel tools provide challenging and promising inroads for understanding the effects of anthropogenic forcing on the climate system’s intrinsic variability.

Transdisciplinary research offers a powerful approach to tackling complex challenges in natural hazards and risk management, but it also presents unique challenges, particularly for early career scientists and practitioners. This short course is specifically designed to equip early career participants with practical tools and strategies for effectively engaging in and contributing to transdisciplinary projects. By focusing on the cross-fertilisation of hard and social sciences, the course will provide actionable insights into how to communicate across disciplines, deliver impactful research, and find common ground for collaboration. Participants will engage in hands-on activities and discussions, drawing from the experiences of leading projects such as The HuT (https://thehut-nexus.eu), PARATUS (https://www.paratus-project.eu), MYRIAD (https://www.myriadproject.eu), and DIRECTED (https://directedproject.eu). Attendees are also welcome to join the scientific session and splinter meeting that are part of this unified path, allowing them to choose between engaging in the entire programme or specific parts according to their interests.

Data assimilation (DA) is widely used in the study of the atmosphere, the ocean, the land surface, hydrological processes, etc. The powerful technique combines prior information from numerical model simulations with observations to provide a better estimate of the state of the system than either the data or the model alone. This short course will introduce participants to the basics of data assimilation, including the theory and its applications to various disciplines of geoscience. An interactive hands-on example of building a data assimilation system based on a simple numerical model will be given. This will prepare participants to build a data assimilation system for their own numerical models at a later stage after the course.
In summary, the short course introduces the following topics:

(1) DA theory, including basic concepts and selected methodologies.
(2) Examples of DA applications in various geoscience fields.
(3) Hands-on exercise in applying data assimilation to an example numerical model using open-source software.

This short course is aimed at people who are interested in data assimilation but do not necessarily have experience in data assimilation, in particular early career scientists (BSc, MSc, PhD students and postdocs) and people who are new to data assimilation.

Structural geologic modeling is a crucial part of many geoscientific workflows. There is a wide variety of applications, from geological research to applied fields such as geothermics, geotechnical engineering, and natural resource exploration. This short course introduces participants to GemPy, a powerful and successful open-source Python library for 3D geological modeling. GemPy allows users to generate geological models efficiently and integrates well with the Python ecosystem, making it a valuable resource for both researchers and industry professionals.
The course will cover the following topics:
(1) Modeling approach and theoretical background: An introduction to the principles behind implicit structural geological modeling.
(2) Creating a GemPy model: A step-by-step guide to building a basic geological model using GemPy.
(3) Open Source Project: An overview of GemPy's development, community, and opportunities for contribution.
(4) Outlook and applications: Exploration of the wide-ranging applications of GemPy in various geoscientific fields, including the link to geophysical inversion. Coding examples for advanced functionalities and examples from publications.
This interactive course is designed for both beginners and those with some experience in geological modeling. Participants are encouraged to bring a laptop to actively engage in the tutorials and apply their newly acquired skills by writing their own code. While basic Python knowledge and a pre-installed Python environment are beneficial, they are not mandatory for participation.

Discover the basics of Geodesy and geodetic data! Geodetic data, from GNSS to gravity measurements, play a crucial role in various Earth sciences, including hydrology, glaciology, geodynamics, oceanography, and seismology. Curious about what these data can (and cannot) tell us? This short course offers a crash course in core geodetic concepts, giving you the insights you need to better understand the advantages and limitations of geodetic data. While you won’t become a full-fledged geodesist by the end, you’ll walk away with a clearer picture of how to use these datasets across various fields. Led by scientists from the Geodesy division, this course is open to all, whether you frequently work with geodetic data or are simply curious about what geodesists do. Expect lively discussions and practical insights. For all geodesists, get the chance to learn what non-geodesists need when working with geodetic data!

This 60-minute short course is part of a quintet of introductory 101 courses on Geodesy, Geodynamics, Geology, Seismology, and Tectonic Modelling. All courses are led by experts who aim to make complex Earth science concepts accessible to non-experts.

Model Land is a conceptual place within the boundaries of a model. When we confuse a Model Land for the real world, we can be ignorant to the assumptions, limitations, uncertainties, and biases inherent in our models. These things need to be carefully understood and considered before we use models to inform decisions about the real world and by doing so we can escape from our Model Lands (Thompson, 2019).
However, in order to escape, we need to explore our Model Lands, mapping them and developing a deeper understanding of their rules and boundaries. In this short course we will present a framework inspired by tabletop roleplay games (TTRPGs) that will bring Model Lands to life. Either using your own model or one of our examples you will learn how to build a world that follows its rules, how to investigate what it would be like to exist within that world, and how to share with others what you have learnt.
Please bring along a pen and paper and be prepared to share your Model Lands. We want to encourage creative expression, so if you have a flair for drawing, poetry, games design, or interpretive dance, feel free to bring along the means to share your creations through whatever medium you prefer.

In April 2023, EPOS, the European Plate Observing System launched the EPOS Data Portal (https://www.ics-c.epos-eu.org/), which provides access to multidisciplinary data, data products, services and software from solid Earth science domain. Currently, ten thematic communities provide input to the EPOS Data Portal through services (APIs): Anthropogenic Hazards, Geological Information and Modelling, Geomagnetic Observations, GNSS Data and Products, Multi-Scale Laboratories, Near Fault Observatories, Satellite Data, Seismology, Tsunami and Volcano Observations.
The EPOS Data Portal enables search and discovery of assets thanks to metadata and visualisation in map, table or graph views, including download of the assets, with the objective to enable multi-, inter- transdisciplinary research by following FAIR principles.
This short course will provide an introduction to the EPOS ecosystem, demonstration of the EPOS Data Portal and hands-on training by following a scientific use case using the online portal. It is expected that participants have scientific background in one or more scientific domains listed above.
The training especially targets young researchers and all those who need to combine multi-, inter- and transdisciplinary data in their research. The use of the EPOS data Portal will simplify data search for Early Career Scientists and potentially help them in accelerating their career development.
Feedback from participants will be collected and used for further improvements of the Data Portal.

Eddy covariance measurements are instrumental for our understanding of carbon and water cycles. It allows us to examine local conditions at the given site or provide a global picture of the interaction of the terrestrial ecosystems with the overlaying atmosphere through data integration in modeling frameworks. The application of the method is multifaceted, and the data processing consists of multiple steps (i.e. raw data processing, quality control, gap-filling, flux partitioning, aggregation) that are dependent and result in a processing chain. Setting up this processing chain can be daunting, especially for new teams not connected to station networks.
In this workshop, we will provide a brief introductory presentation concerning the eddy covariance post-processing chain (30 mins), show useful resources and software (15 mins), and mainly focus on the independent hands-on training using available commented tutorials or complete processing workflow. The attendees will have a chance to learn how to use openeddy to 1) read and write data with units; 2) remap variable names; 3) merge data and fill gaps in timestamp; 4) plot eddy covariance data; 5) flag and remove spurious measurements and 6) aggregate gap-filled data and evaluate uncertainty. They will also have a chance to learn how to use REddyProc standard post-processing routines for 1) the estimation of the u*-threshold; 2) gap-filling, 3) flux-partitioning, and 4) the derivation of ecosystem properties using the bigleaf R package. The workshop could also be a good opportunity to meet the software developers, ask questions and interact with other colleagues.
Participants should come with a laptop with installed recent versions of R, RStudio, and the openeddy, REddyProc and bigleaf R packages. To work with openeddy tutorials and workflow files, you will also need to download additional data sets (see below).
openeddy package installation: https://github.com/lsigut/openeddy#installation
openeddy tutorials installation: https://github.com/lsigut/openeddy_tutorials#installation
eddy covariance workflow instructions: https://github.com/lsigut/EC_workflow#usage
REddyProc vignettes: https://github.com/bgctw/REddyProc/tree/master/vignettes
bigleaf vignette: https://github.com/cran/bigleaf/blob/master/vignettes/

Early Career Researchers (ECRs) often play a crucial part in Research Projects. They are at the forefront of developing new methods, finding new insights, creating new solutions, and often are essential contributors in projects achieving their promised scientific output and deliverables. At the same time, research projects serve as an environment where ECRs can observe how projects are run, which might influence how these ECRs will then act as project leaders in the future. Yet, too few projects seem to address the fundamental importance of ECRs within a project and do not explicitly account for their needs or systematically offer opportunities that help them grow professionally.

This short course aims to provide an interactive platform for ECRs and project leaders to share, learn, and discuss best practices in engagement and empowerment within Research Projects. The course will offer a space for ECRs to reflect on their experiences, both positive or negative and to discuss means of structuring research projects that explicitly account for the needs and opportunities of ECRs, such as networking, discussion and dissemination of results, leadership, collaboration, scientific communication, creation of a community (especially in large and spread out consortiums).

The co-conveners of the session will first share some best practice examples of ECR empowerment in terms of 1) systematic involvement in project management, 2) organizing a peer-to-peer inter- and transdisciplinary academy program, and 3) facilitating an active ECR network at and across events. Afterwards there will be space for break-out discussions with the audience to reflect on the added value of such examples and allow participants to discuss and explore new ideas and approaches to improve ECR engagement and empowerment in future research projects.
The course invites ECRs, project leaders, and anyone involved in the management or participation of Research Projects, particularly those interested in improving ECR engagement and empowerment.

Building on our previous successful "Breaking Boundaries" short course from EGU24, which aimed at advancing science communication in the Global South, we are excited to propose a new session focused on writing compelling research proposals for funding. During our last EGU short course, we briefly highlighted the significant funding challenges faced by researchers from the Global South compared to their counterparts in the Global North. Thankfully, with the growing influence of Global South leaders, there has been an increase in collaborative opportunities, national/international and cross-border funding. However, securing this funding or position still hinges on the strength of a research proposal.
To address this need, we have designed a short interactive course dedicated to the art of writing strong research proposals for securing either research position or proposal fundings. This session will offer practical techniques and tips for creating compelling proposals and will include an open discussion. Additionally, we will provide insights from funding agencies based in Global South countries, highlighting the key elements they look for in proposals. This course is valuable for researchers at all career stages, with a particular emphasis on Early Career Scientists (ECS) looking to enhance their proposal-writing skills. Participants will benefit from:
1. Researchers' Perspective: Learn from successful grant recipients about the crucial points to consider when writing a research proposal.
2. Funding Agency Perspective: Gain insights from representatives of funding agencies in the Global South on their requirements and expectations.
3. ECS Perspective: Hear from fellow participants about their experiences and challenges in research proposal writing.
This short course is open to everyone with an interest in improving their proposal writing skills. ECS from the Global South are especially encouraged to participate as they will be provided with an opportunity to interact with researchers and funding agency representatives, gaining valuable insights into their expectations and experiences. For more information or inquiries, please feel free to contact the course convener.

3D data are more and more available and used in earth sciences for a large variety of purposes (glacial changes, forestry, erosion in rivers, changes of land use, sediment transport, landslides, etc). A large variety of methods are now available to acquire such data on the field (terrestrial or airborne LiDAR, photogrammetry from drones or cameras). Our team has developed two plugins freely available in CloudCompare to process point clouds: 3DMASC (Letard et al, 2023) for general purpose classification, and G3Point (Steer et al, 2023) for grain segmentation and features extraction. In this short course, participants will learn how to efficiently use 3DMASC to classify fluvial environments (typically vegetation, rock and sediments) and then apply G3Point on sediments to segment grains and extract their geometries (size, orientation). Workshop material: TLS data set acquired along a fluvial reach (small bedrock gorges and an alluvial bar) provided to the participants.

During this short course, which is open to anyone with a general interest in plate tectonic processes, we will introduce the participants to the principles and application of analogue models in interpreting tectonic systems.

Tectonic processes act at different spatial and temporal scales. What we observe today in the field or via direct and indirect measurement is often just a snapshot of processes that stretch over hundreds or thousands of km, and take millions of years to unfold. Thus, it is challenging for researchers to interpret and recontrust the dynamic evolution of tectonic systems. Analogue modeling provides a tool to overcome this limitation, allowing for the physical reproduction of tectonic processes on practical temporal and spatial scales (Myr → hrs, km → cm/m). Of course, the reliability of analogue models is a function of the assumptions and simplifications involved, but still their usefulness in interpreting data is outstanding.

In this course we will go through the following outline:
- Aims and history of analogue modelling
- Model setups and materials
- Model scaling
- Monitoring techniques
- Interpreting model results
- Interactive demonstration: Running a live model :)
- Q&A

The final aim of this short course will be to present analogue modeling as a valid technique to be applied side by side with observations and data from the real world to improve our interpretation of the evolution of natural tectonic systems. We also intend to inspire the course participants to develop and run their own analogue tectonic modeling projects, and to provide them with the basic skills, as well as directions to find the additional resources and knowledge required to do so.

This short course is part of a quintet of introductory 101 courses on Geodesy, Geodynamics, Geology, Seismology, and Tectonic Modelling. All courses are led by experts who aim to make complex Earth science concepts accessible to non-experts.

In a changing climate world, extreme weather and climate events have become more frequent and severe, and are expected to continue increasing in this century and beyond. Unprecedented extremes in temperature, heavy precipitation, droughts, storms, river floodings and related hot and dry compound events have increased over the last decades, impacting negatively broad socio-economic spheres (such as agriculture), producing several damages to infrastructure, but also putting in risk human well-being, to name but a few. The above have raised many concerns in our society and within the scientific community about our current climate but our projected future. Thus, a better understanding of the climate and the possible changes we will face, is strongly needed. . In order to give answers to those questions, and address a wide range of uncertainties, very large data volumes are needed across different spatial (from local-regional to global) and temporal scales (past, current, future), but sources are multiple (observations, satellite, models, reanalysis, etc), and their resolution may vary each other. To deal with huge amounts of information, and take advantage of their different resolution and properties, high-computational techniques within Artificial Intelligence models are explored in climate and weather research. In this short-course, a novel method using Deep Learning models to detect and characterize extreme weather and climate events will be presented. This method can be applied to several types of extreme events, but a first implementation on which we will focus in the short-course, is its ability to detect past heatwaves. Discussions will take place on the method, and also its applicability to different types of extreme events. The course will be developed in python, but we encourage the climate and weather community to join the short-course and the discussion!