Session programme

Are you unsure about how to bring order in the extensive program of the General Assembly? Are you wondering how to tackle this week of science? Are you curious about what EGU and the General Assembly have to offer? Then this is the short course for you!

During this coursee, we will provide you with tips and tricks on how to handle this large conference and how to make the most out of your week at this year's General Assembly. We'll explain the EGU structure, the difference between EGU and the General Assembly, we will dive into the program groups and we will introduce some key persons that help the Union function.

Feel free to join us, we are looking forward to meeting you!

The European Geosciences Union is a the largest Geoscientific Union in Europe, largely run by volunteers. Perhaps you have been to the General Assembly before, maybe you have published in one of the EGU journals, or are you following EGU and/or several EGU divisions on social media.

Whatever your closest link with EGU, would you like to get involved?

This short course is aimed at Early Career Scientists and will provide an overview of all the activities of EGU, which are much more than just the General Assembly. We will give practical tips on how to get involved, who to contact and where to find specific information if you want to organise a event.

More than 50% of EGU's members consist of ECS, let's get active!

Recent publications show that many people working in academia experience mental health issues. Factors like job insecurity, limited amount of time and poor management often cause high stress levels and can lead to mental health problems, such as depression, anxiety or emotional exhaustion. Following the EGU blog series and short course ‘Mind your Head’ in 2019-2020, and the successful ECS Great Debate at the General Assembly in 2019, we aim to continue the dialogue and reduce the stigma surrounding mental illness.

In this short course we invite panelists to share their experiences, how they dealt with it and what support they received. Afterwards we aim to actively engage the audience to discuss how to take control of their mental wellbeing and prioritise it in the current academic environment. We invite people from all career stages and disciplines to come and join us for this short course.

COVID-19 has affected our daily lives in an unprecedented range of ways. It is a human, economic and social crisis that has potentially changed the way we live, work and interact with each other forever. Researchers have not been spared from this, facing numerous challenges since the start of the outbreak, both personal and professional. This session will focus on a couple of these challenges in detail and discuss the lessons that we can learn to strengthen the scientific community and research in the future.

The first challenge that this session will address is the impact COVID-19 has had on research activities directly. Since the introduction of lockdowns in Europe, many researchers have had to reduce their research activities due to additional responsibilities at home while others have been locked out of laboratories and libraries, of all kinds, or been unable to undertake fieldwork to collect primary data. This has not only impacted the careers of many scientists but also led to project goals becoming unachievable, issues with funding and PhD candidates unable to complete their research. In this short course we will look at what can be done on an individual level to improve the current situation that many researchers find themselves in.

In addition to the financial, structural difficulties, many researchers are starting to view the way that they do science as more flexible than they might have considered possible before the coronavirus outbreak. This short course will also make space for discussions about how the practicalities of doing research (be it infrastructure, work patterns or styles of employment) could change in the light of what we have learned during this challenging time. We will also ask the question ‘how can large organisations and institutions attempt to better prepare in case another global crisis arises in the future?’

The European Research Council (ERC) is a leading European funding body supporting excellent investigator-driven frontier research across all fields of science. ERC calls are open to researchers around the world. The ERC offers various different outstanding funding opportunities with grants budgets of €1.5 to €3.5 million for individual scientists. All nationalities of applicants are welcome for projects carried out at a host institution in Europe (European Union member states and associated countries). At this session, the main features of ERC funding individual grants will be presented.

Drafting your first grant proposal can be daunting. Grant writing improves with experience, so how do early career scientists compete on equal footing with those who are more established? In this short course, a panel of scientists and funding agencies will share their experience on applying to different funding bodies and provide top tips to early career scientists. You can gain insight and (even better) inspiration by discussing with the panel the bits and pieces you may struggle with when writing a strong grant proposal. This session will be followed by a ‘pop-up’ session in the Networking and ECS lounge, for more specific questions to our panel.
NOTE - this course has a broader scope than the more specific ERC and Marie Curie short courses. This course gives broad tips and hints on how to write a successful proposal irrespective of the funding body.

After the PhD, a new challenge begins: finding a position where you can continue your research or a job outside academia where you can apply your advanced skills. This task is not always easy, and frequently a general overview of the available positions is missing. Furthermore, in some divisions, up to 70% of PhD graduates will go into work outside of academia. There are many different careers which require or benefit from a research background. But often, students and early career scientists struggle to make the transition due to reduced support and networking.
In this panel discussion, scientists with a range of backgrounds give their advice on where to find jobs, how to transition between academia and industry and what are the pros and cons of a career inside and outside of academia.
In the final section of the short course, a Q+A will provide the audience with a chance to ask their questions to the panel. This panel discussion is aimed at early career scientists but anyone with an interest in a change of career will find it useful. An extension of this short course will run in the networking and early career scientist lounge, for further in-depth or one-on-one questions with panel members.

Diversity has many dimensions including, but not limited to, race/ethnicity, gender, disability status, nationality, language, religious affiliation, sexual orientation, and socioeconomic background. Diversity is key for scientific progress and society because different perspectives and life experiences give rise to diversity in scientific questions and approaches to address them, and stimulate collaboration between academics and local communities. Nevertheless, geosciences remain the least diverse of all STEM (science, technology, engineering and mathematics) fields.
In this short course, early career scientists will be presented with practical advice on how they can contribute to promoting diversity in both their present and future career stages and help to build a geoscience community that is welcoming and supporting to marginalized scientists.

The short course will consist of the following invited talks, followed by discussion with the speakers:

(1) Asmeret Asefaw Berhe: "Forms of diversity and how can early career scientists support it"

(2) Bala Chaudhary: "Building an anti-racist lab"

(3) Budiman Minasny: "The fair-play of scientific collaborations - beyond helicopter research"

Scientists of all career stages are welcome to participate and join the discussions!

Bullying and discrimination within academia are widespread and impact science at all levels. Early Career Scientists of underprivileged and underrepresented groups are those most affected by such work environments. Thus, discriminatory work environments further contribute to the continued lack of diversity within the geosciences, ultimately hampering scientific advancement. Systemic power dynamics within academia lead to the fear of retaliation and the impunity of professors, which is why culprits get away with abuse far too often. Despite increased discussions about this topic, institutions tend to provide little or ineffective support for those affected, nor clear steps forward. In this interactive short course, an expert panel will (i) provide practical recommendations on how to combat discriminatory work environments and (ii) explain strategies for bystander intervention. This will be followed by an open discussion between the expert panel and all participants about how to battle discriminatory work environments in the geosciences.
This Short Course is a joint effort of the Equality, Diversity and Inclusion Working Group of EGU, the Young Hydrologic Society and EGU.
With Prof. Dr. Aradhna E. Tripati, Prof. Dr. Erika Marin-Spiotta, Dr. Anjana Khatwa and Dr. Moses Milazzo we have a great panel consisting of a diverse group of experts and ambassadors for more diversity and equity within the geosciences.

Careers in academia exist beyond research and publications. There are always aspects more than what meets the eye. Often, we tend to learn about what is made available and evident, leaving behind many questions. It is only natural for aspiring scientists to have questions that shape their minds and impact their research. Some questions pertain to professional realms, others may relate to more broader perspectives on ambitions, inspirations, and what one deems as meaningful. Not every day do we get the opportunity to present these floating concerns at a forum and have experts address and pay heed to the same. In this session, a successful scientist with many years of experience will provide a look back to give a personal perspective of her/his career.

This year, we have the absolute pleasure of having with us Professor Todd A. Ehlers, who is an all-round geologist, head of the Earth Surface Dynamics group at the University of Tuebingen, Germany. Todd’s work has been contributing to better understand how tectonic, climatic and biogenic forces interact and drive landscape evolution, using an ensemble of techniques such as thermochronology, cosmogenic nuclides, numerical modelling, near-surface geophysics. Besides his research expertise, we shall engage in conversations regarding the challenges that came his way, and the manner in which he overcame those, and how his research shaped his life and in turn, how his life is impacted by the research he does. The discussions shall offer a unique opportunity to learn and empathise with a scholar’s work and life that has inspired many. The session shall conclude with the prospect of questions that Todd shall be happy to answer.

Over the last decades, research in the Solar-Terrestrial sciences has greatly advanced our understanding of this huge and complex system. For half a century, satellites and a continuously growing network of ground-based observatories have allowed us to make observations in more remote regions of the Sun-Earth system and with higher precision than ever before. Besides, high-performance computing has enabled the development of powerful numerical models, which gives us an unprecedented insight into each level of solar-terrestrial couplings. As new space missions and breakthroughs in numerical simulations fill in today’s missing pieces of knowledge, new questions arise, that need to be tackled by new thoughts. Being an Early Career Scientist, it is often hard to identify which questions are new and what has been answered before. In this short course, we have invited a panel of renowned researchers. They will give their view on how far we have come in our understanding, and most importantly, on what open questions and challenges lie ahead for the young scientists to embark upon. This is an excellent opportunity to meet with the experts and discuss the future of our community. The target audience is students and early-career scientists who want to increase their awareness of current and future research challenges within solar-terrestrial sciences and to discuss their potential contributions. The audience is invited to propose specific topics and/or questions for discussion in advance to ecs-st@egu.eu.

How do you peer-review? Apparently you are just supposed to miraculously know. Many of us never receive formal training in peer review, yet our peer-reviews are the cornerstone of scientific legitimacy. Constructive, respectful, coherent reviews nurture dialogue and advance research. So, how can we review papers in an efficient way? In this course, we suggest a process to help ensure that we give the authors the most useful feedback? We will hear from peer-review experts about how they go about the process and have an open discussion with the audience.

Publishing your research in a peer reviewed journal is essential for a career in research. The EGU Journals are fully open access which is great, but the open discussion can be daunting for first time submitters and early career scientists. This short course will cover all you need to know about the publication process from start to end for EGU journals, and give you a chance to ask the editors some questions. This includes: what the editor looks for in your submitted paper, how to deal with corrections or rejections, and how best to communicate with your reviewers and editors for a smooth transition from submission to publication. An open discussion will be served to give you time for questions to the editors,and for them to suggest some ‘top tips’ for a successful publication. This course is aimed at early-career researchers who are about to step into the publication process, and those who are yet to publish in EGU journals. Similarly, this course will be of interest to those looking to get involved in the peer-review process through reviewing and editing.

Writing a scientific paper is an essential part of research, and is a skill that needs practice.

This session is organized in cooperation with the Young Hydrologic Society (http://younghs.com/).

Meet editors of internationally renowned journals in biogeosciences and soil system science and gain exclusive insights into the publishing process. After a short introduction into some basics, we will start exploring various facets of academic publishing with short talks given by the editors on - What are the duties and roles of editors, authors and reviewers? - How to choose a suitable journal for your manuscript and what is important for early career authors? - How can early career scientists get involved in successful peer-reviewing? - What is important for appropriate peer-reviewing? - What are ethical aspects and responsibilities of publishing? - Together with the audience and the editors, we will have an open discussion of all steps and factors shaping the publication process of a manuscript. This short course aims to provide early career scientists across several EGU divisions (e.g. BG, SSS, NH and GM) the opportunity of using first hand answers of experienced editors of international journals to successfully publish their manuscripts and get aware of the potentials and pitfalls in academic publishing.

The short course aims to present the current status of the training and education in raw materials in the world, the evolution of skills and competences in the raw materials sector and show to attendants the free online educational platform developed by the INTERMIN Team. Users will be guided through the diverse facilities of the portal such as a searchable wiki of training centres database interlinked with a geographic information system of the available raw materials training programmes at a global scale. This facility shall be organised by the user based on the interesting skill to be acquired with the different training programmes.
The platform is a tool to help career guidance and lifelong learning within the raw materials community. It encompasses details of the database of training programmes, its strengths, weaknesses, protagonists, languages, content in relation to other courses, number of participants, target audience, duration & workload, and nature of classes. The platform facilitates discussions to support career guidance with the aim of enhancing collaboration between students, career guidance services, employers, education and training institutions, and NGOs. The portal and its network are thus expected to pave the way for establishing common training programmes in the raw materials sectors.
The International Network of Raw Materials Training Centres (INTERMIN) involves a network that represents more than 550 000 geoscientists working in academic research, industry, governments, and NGOs in 5 continents. The network develops synergies and international cooperation with the relevant EU Member States and the leading counterparts in third countries, based on specific country expertise in the primary and secondary raw materials sectors. The network has mapped skills and knowledge in the EU and the third countries, identified key knowledge gaps and emerging needs, developed a roadmap for improving skills and knowledge, as well as established common training programmes in the raw materials sectors.


INTERMIN project has received funding from the EU Horizon2020 research and innovation programme under Grant Agreement No 776642

Preparation and presentation of research findings at conferences are an important and time-consuming part of a scientist’s life. From a scientific perspective, the lack of time and orientation on how to create the poster one would like to present, can be very dissatisfying. Similar sensations are coming up while attending poster sessions at a conference: often, it’s just being overwhelmed by the amount of information presented in a non-reader-friendly way. Although a properly designed poster gains more attention, is easier to understand and can therefore improve visibility and the chances of having interesting discussions about one’s research, it is still difficult to achieve a well-designed poster. Why is this still the case in times where we can easily look up the Do’s and Don’ts of poster design online?
One reason is that there is more to professional graphic and information design than choosing the right font size or deciding upon the best color combination. Therefore, in this short course we will take a step back and have a look on how professional designers are planning their projects, starting their workflow and how this can help a scientist to design a poster for a conference effectively and properly. The design thinking process consists of a phase of emphasizing, defining the problem, ideating, creating a prototype, testing - and most important: improving again. Implementing this process helps to develop a detailed plan, which can give guidelines and structure when designing posters.
We will go through the design process theoretically and then discuss the different questions together addressing the scientific poster. All you need is curiosity when it comes to visual communication of your research and the willingness to discuss the topic with other participants of the course. Furthermore, it will be useful to bring something to note your thoughts during the course to create your own cheat-sheet to which you can come back to when starting the work on your next poster.

The work of scientists does not end with publishing their results in peer-reviewed journals and presenting them at specialized conferences. One side of the work that is becoming more and more relevant and often is required by funding agencies to be specified in one’s project proposal is outreach. What does outreach mean? Very simply, it means to engage with the non-scientific public and a wider audience than you are commonly used to. There are many ways to do outreach, from blogging and vlogging, using social media, write for a science dissemination journal, participate as a speaker to local science festivals, organize open-days in the laboratory and so on.
With this short course, we aim at giving you some practical examples of different outreach activities and tips and suggestions from personal and peers experiences. In the last part of the course, you will work singularly to come up with an outreach idea based on your research activity. You may use it on your next proposal, you never know!

“Science isn't finished until it's communicated. The communication to wider audiences is part of the job of being a scientist, and so how you communicate is absolutely vital.” - Professor Sir Mark Walport, Chief Scientific Advisor to the UK government

Science is vital to society. It allows civilisations to advance, economies to prosper and provides solutions to societal problems. Unfortunately, the benefits of science aren’t automatically understood by the wider public – they must be communicated!

Communicating your science to a broader audience can also be hugely beneficial on a personal level – potentially boosting you profile as an expert, connecting you with new research and/or industry partners, and sparking ideas for new areas of research. Communicating your research to citizens is obviously important but how to communicate effectively to a non-scientific community isn’t always so straightforward. The first half of this session will outline some tips to communicate your research with the public, the challenges that scientists may face and how these can be overcome.

The second half of the session will feature speakers who are working to bridge the gap between research and society. They will outline some institutionalised routes that scientists can take to connect with citizens and provide examples of when it has had unexpected benefits.

Science and policy often feel like two different worlds, working on different timescales and using different languages. Despite this, almost every policy decision has a scientific component to it. And while science alone will never make policy, it can allow policymakers to more accurately assess the benefits and potential consequences of different policy pathways.

This session will highlight some of the key messages from the European Commission Joint Research Centre's recently published ‘Science for Policy Handbook’ (https://egu.eu/0HNFV9/). It will be hosted by two of the Handbooks key authors, Marta Sienkiewicz and Lene Topp.
Some of the key topics that will be outlined include:

- The importance of strategic planning for engaging relevant policymakers
- The different policy actors and their role in the policymaking process
- Examples of how you can speak the language that policymakers understand and pay attention to
- Finding windows of opportunity and building relationships

Attendees will also be given the opportunity to ask any questions they have about the Handbook or working at the science for policy interface more generally. This session is open to all EGU scientific divisions and scientists at all stages of their careers.

The Joint Research Centre’s Science for Policy Handbook is available free online and will give you a sneak peek into some of this session’s content! https://egu.eu/0HNFV9/

Never has it been more important that geoscience research feeds into political decisions and policymaking. What is more, today many policymakers and institutions are increasingly receptive to scientific evidence. Yet, whilst researchers are increasingly keen to influence policy and policymaking, for many the mechanisms for engagement and impact seem unclear and inaccessible.

This course will demystify policymaking and give researchers the tools to be able to engage with policy through their research. Researchers will learn about how parliaments use evidence in their policy-shaping processes and the mechanisms that feed science advice into Parliament. This session will be hosted by individuals who work at the interface of science and policy, drawing from real-life examples and providing plenty of opportunities for attendees to ask questions.

This 60-minute short course aims to introduce non-geologists to structural and petrological geological principles, which are used by geologist to understand system earth.

The data available to geologists is often minimal, incomplete and representative for only part of the geological history. Besides learning field techniques to acquire and measure data, geologists need to develop a logical way of thinking to close gaps in the data to understand the system. There is a difference in the reality observed from field observation and the final geological model that tells the story.

In this course we briefly introduce the following subjects:
1) Geology rocks: Introduction to the principles of geology and field data acquisition
2) Failing rocks: From structural field data to (paleo-)stress analysis
3) Dating rocks: Absolute and relative dating of rocks using petrology and geochronology methods
4) Crossover rocks: How geology benefits from seismology and geodynamic research and vice-versa

Our aim is not to make you the next specialist in geology, but we would rather try and make you aware of the challenges a geologist faces when they go out into the field. Additionally, the quality of data and the methods used nowadays are addressed to give seismologists and geodynamicists a feel for the capabilities and limits of geological research. This course is given by Early Career Scientist geologists and geoscientists and forms a trilogy with the short course on ‘Geodynamics 101 (A&B)’ and ‘Seismology 101’. For this reason, we will also explain what kind of information we expect from the fields of seismology and geodynamics and we hope to receive some feedback in what kind of information you could use from our side.

The main goal of this short course is to provide an introduction into the basic concepts of numerical modelling of solid Earth processes in the Earth’s crust and mantle in a non-technical manner. We discuss the building blocks of a numerical code and how to set up a model to study a simple geodynamic problem. Emphasis is put on what numerical models are and how they work while taking into account the advantages and limitations of the different methods.

We go through the following topics:
(1) The basic equations used in geodynamic modelling studies, what they mean, and their assumptions
(2) A brief introduction to the various numerical methods
(3) The importance of benchmarking a code
(4) How to go from a geological problem to the model setup
(5) How to set initial and boundary conditions
(6) How to interpret the model results
We will use a simple example from the code ASPECT (https://aspect.geodynamics.org) to illustrate points 4-6 through an in-class demonstration. Participants are not required to bring a laptop or have any previous knowledge of geodynamic numerical modelling.

Armed with the knowledge of a typical numerical modelling workflow, participants will be better able to critically assess geodynamic numerical modelling papers and they will learn how to start with numerical modelling.

This short course is run by early career geodynamicists. It is dedicated to everyone who is interested in, but not necessarily experienced with, geodynamic numerical models; in particular early career scientists (BSc, MSc, PhD students and postdocs) and people who are new to the field of geodynamic modelling.

How do seismologists detect earthquakes? How do we locate them? Is seismology only about earthquakes? Seismology has been integrated into a wide variety of geo-disciplines to be complementary to many fields such as tectonics, geology, geodynamics, volcanology, hydrology, glaciology and planetology. This 90-minute course is part of the Solid Earth 101 short course series together with ‘Geodynamics 101 (A & B)’ and ‘Geology 101’ to better illustrate the link between these fields.

In ‘Seismology 101’, we will present an introduction to the basic concepts and methods in seismology. In previous years, this course was given as “Seismology for non-seismologists” and it is still aimed at those not familiar with seismology -- in particular early-career scientists. An overview will be given on various methods and processing techniques, which are applicable to investigate surface processes, near-surface geological structures and the Earth’s interior. The course will highlight the role that advanced seismological techniques can play in the co-interpretation of results from other fields. The topics will include:

- the basics of seismology, including the detection and location of earthquakes
- understanding and interpreting those enigmatic “beachballs”
- an introduction to free seismo-live.org tutorials and other useful tools
- how seismic methods are used to learn about the Earth, such as for imaging the Earth’s interior (on all scales), deciphering tectonics, monitoring volcanoes, landslides and glaciers, etc...

We likely won’t turn you in the next Charles Richter in 90 minutes but would rather like to make you aware of how seismology can help you in geoscience. The intention is to discuss each topic in a non-technical manner, emphasizing their strengths and potential shortcomings. This course will help non-seismologists to better understand seismic results and can facilitate more enriched discussion between different scientific disciplines. The short course is organised by early-career scientist seismologists and geoscientists who will present examples from their own research experience and high-impact reference studies for illustration. Questions from the audience on the topics covered will be highly encouraged.

Rationale
The proper and deep education on ethical issues in geosciences has been evolving in recent times, although not as quickly and deeply as necessary. Many of the professionals dedicated to Earth Sciences have been not in touch with such new concepts and tendencies as the concept of Geoethics. Geoethics is the research and reflection on the values which underpin appropriate behaviors and practices, wherever human activities interact with the Earth system. Geoethics provides a framework from which to define ethical professional behaviors in both geosciences and engineering, and to determine how these should be put into practice for the benefit of society and environment. The Short Course goes is directed towards introducing and training geoscientists in those new concept and ideas as well as exposing the perspectives of this field.

Course Content: (generic until we know the lecturers attending EGU2021 then, adjusted):
1. From Ethics to Geoethics: definition, values, tools
2. Responsible conduct of research and professionalism
3. Tools for Confronting (geo)ethical dilemmas
4. Geoethics for society: sustainable development and responsible mining
5. Geoethics in natural hazards
6. Geoethics in geoscience communication
7. Recent developments in geoethical thinking
8. Perspectives of Geoethics
9. Geoethics’ case studies: Paleontology, Water Management, Ocean Governance, etc.

Learning objectives
After completing this course, participants
1. Will know the basic principles of ethics and how these lead to geoethics
2. Will be aware of the dilemmas involved in making geoethical decisions
3. Will have gained some experience in taking a geoethical approach to real-world cases

Most often observations and measurements of geophysical systems and dynamical phenomena are obtained as time series whose dynamics usually manifests a nonlinear behavior. During the past decades, nonlinear approaches in geosciences have rapidly developed to gain novel insights on fluid dynamics, greatly improving weather forecasting, on turbulence and stochastic behaviors, on the development of chaos in dynamical systems, and on concepts of networks, nowadays frequently employed in climate research.

In this short course, we will offer a broad overview of the development and application of nonlinear concepts across the geosciences in terms of recent successful applications from various fields, ranging from climate to solar-terrestrial relations. The focus will be on a comparison between different methods to investigate various aspects of both known and unknown physical processes, moving from past accomplishments to future challenges.

Why to wait hours for computations to complete, when it could take only a few seconds? Tired of prototyping code in an interactive, high-level language like MATLAB, R or Python and rewriting it in a lower-level language such as C, C++ or Fortran to get high-performance code? Or simply curious about how GPUs and supercomputing are game changers in geosciences?

This short course covers trendy areas in modern geocomputing with broad geoscientific applications. The physical processes governing natural systems' evolution are often mathematically described as systems of differential equations. A performant numerical implementation of the solving algorithm leveraging modern hardware is key and permits to tackle problems that were technically not possible a decade ago.

The goal of this short course is to offer an interactive and tutorial-like hands-on to solve systems of differential equations in parallel on GPUs using the Julia language. Julia combines high-level language simplicity and low-level language performance. The resulting codes and applications are fast, short and readable. We will design and implement a numerical algorithm that predicts ice flow dynamics over mountainous topography using a high-performance computing approach.

The course format is online. You will work on (remote) notebooks to enable best participant experience. The course consists of 2 parts:
1. You will learn about the Julia language, parallel and distributed computing and iterative solvers.
2. You will implement a PDE solver to predict ice flow dynamics on real topography.

By the end of this short course, you will:
- Have a GPU PDE solver that predicts ice-flow;
- Have a Julia code that achieves similar performance than legacy codes (C, CUDA, MPI);
- Know how the Julia language solves the "two-language problem";
- Be able to leverage the computing power of modern GPU accelerated servers and supercomputers;
- Know about the rapidly growing and exciting Julia ecosystem and community.

We look forward to having you on board and will make sure to foster exchange of ideas and knowledge to provide an as inclusive as possible event.

Computer models are essential tools in the earth system sciences. They underpin our search for understanding the earth system functioning and support decision-making across spatial and temporal scales. Predictions of computer models though are conditional on a range of assumptions and input data that are often largely uncertain due to, among others, our limited understanding of earth systems processes and interactions, the simplified representation of spatial heterogeneity in our models, and errors and gaps in the data. To understand the implications of uncertainty and environmental variability on the identification and use of earth system models, we can rely on increasingly powerful Uncertainty and Sensitivity Analysis methods.
In this short course we will:

1) use a set of literature examples to demonstrate the benefits of using Uncertainty and Sensitivity Analysis to support the calibration, evaluation, and simplification of earth systems models and their use to inform decision-making
2) discuss some of the key methodological choices in the set-up of Uncertainty and Sensitivity Analysis and provide guidelines and best-practice examples on how to make such choices
The course will focus on Monte-Carlo methods for uncertainty propagation and Global Sensitivity Analysis (GSA) techniques, such as those discussed in (1) and (2). The course is intended for researchers and practitioners who already have experience of using these techniques as well as beginners.
For those who wants to get some hands-on understanding of GSA before and/or after the course, we have prepared some online tutorials in the form of interactive Jupyter Notebooks (these can be run from browser, no need to install any software):

https://mybinder.org/v2/gh/AndresPenuela/SAFE-Notebooks/HEAD

Uncertainty Analysis - using fully- and extra-probabilistic approaches

Uncertainty analysis is an unavoidable task of risk assessments either for natural hazards like landslides, earthquakes, floods, volcanoes, etc., or for environmental issues like groundwater or soil contamination. When dealing with uncertainties, two categories should be considered as outlined by several authors:
1) “aleatoric uncertainty” (also named “randomness” or “intrinsic variability”) and arises from the natural variability owing to either heterogeneity or to the random character of natural processes (i.e. stochasticity). A common example of aleatoric uncertainty is the variability in weather.
2) “epistemic uncertainty” and arises when dealing with “partial ignorance” i.e. when facing “vague, incomplete or imprecise information” such as limited databases and observations or “imperfect” modelling.

Although the probabilistic setting has been used in a broad range of different applications, the use of probabilities as a tool to represent epistemic uncertainties has often been criticized in situations where the available data are imprecise, scarce, incomplete, vague, qualitative, etc. In such highly uncertain situations, the challenge is to formulate appropriate mathematical tools and models in a quantitative manner, on the one hand, accounting for all data and pieces of information, but, on the other hand, without introducing unwarranted assumptions. Therefore, to overcome the shortcomings of the pure probabilistic setting, several alternative representation methods have been developed: probability boxes, possibility distributions, Dempster-Shafer structures, etc.

The purpose of the short course is to describe how these new tools can be used to handle epistemic uncertainty for the different stages:
- Uncertainty representation;
- Propagation;
- Sensitivity analysis;
- Support for decision-making.

Comparisons with fully probabilistic approaches will also be performed. The short course will be supported by real cases taken from risk assessment studies for earthquakes (Rohmer & Baudrit, Nat. Haz., 2011), sea level rise (Le Cozannet et al., ERL, 2017), and groundwater contamination (Baudrit et al., J. Cont. Hydrology, 2007). These illustrations will be performed using R package “HYRISK” (https://cran.r-project.org/web/packages/HYRISK/index.html).

Numerical models used for weather and climate prediction have traditionally been formulated in a deterministic manner. In other words, given a particular state of the resolved scale variables, the most likely forcing from sub-grid scale motions and parametrised processes is estimated and used to predict the evolution of the large-scale flow. However, knowledge uncertainties, necessary simplifications in representing the physical processes in numerical models, and the lack of scale-separation in the Earth System mean that this approach is a large source of error in forecasts. Over recent years, an alternative paradigm has developed: the use of stochastic techniques to represent the effects of uncertain small-scale and parametrised processes. Instead of predicting the most likely forcing effect of these processes on the resolved scales, a Monte-Carlo approach is used. Integrations of the numerical model sample possible realisations of the forcing.

Stochastic parametrisations are now the norm in ensemble weather and seasonal forecasts worldwide. By accounting for uncertainty in the forecast due to the limitations of numerical models, stochastic parametrisations improve the reliability of ensemble forecasts. We are now seeing their adaptation for use in climate models, with stochastic parametrisations being developed to represent a wide range of processes in the Earth System, including processes in the atmosphere, oceans, and land surface.

This course will introduce the art and science of stochastic parametrisation, including

> Purpose: model uncertainty, ensemble forecasting, climate applications
> Foundations: stochastic processes
> Theory: how to design a stochastic scheme
> Realisation: the path from a well-designed scheme to an operational implementation in a numerical model

This course is aimed at PhD students, Early Career Scientists, and all those interested in an overview of key concepts in stochastic parametrisation. The course will be taught through a combination of presentations and interactive exercises using python notebooks. No prior knowledge of python is necessary.

In order to be able to have predictive power on extreme events we need to rely on mathematical approaches that provide us with some degree of universality, so that we have rigorous ways to extrapolate information beyond what has been already recorded. In this short course we will introduce frameworks based on dynamical systems theory and statistical mechanics that allow for a rigorous and effective treatment and analysis of extreme events. We will show how extreme value theory and large deviation theory allows for a better understanding of high-impact weather and climate extremes as well as of the basic dynamical properties of the atmosphere. We will introduce the basic theory and show applications on a range of datasets, including outputs of numerical models of various levels of complexity as well as observational data.

Shaun Lovejoy (lovejoy@physics.mcgill.ca)
Christian Franzke (christian.franzke@gmail.com)
Thomas Laepple (Thomas.Laepple@awi.de)

The climate is highly variable over wide ranges of scale in both space and time so that the amplitude of changes systematically depends on the scale of observations. As a consequence, climate variations recorded in time series or spatial distributions, which are produced through modelling or empirical analyses are inextricably linked to their space-time scales and is a significant part of the uncertainties in the proxy approaches. Rather than treating the variability as a limitation to our knowledge, as a distraction from mechanistic explanations and theories, in this course the variability is treated as an important, fundamental aspect of the climate dynamics that must be understood and modelled in its own right. Long considered as no more than an uninteresting spectral “background”, modern data shows that in fact it contains most of the variance.

We review techniques that make it possible to systematically analyse and model the variability of instrumental and proxy data, the inferred climate variables and the outputs of GCM’s. These analyses enable us to cover wide ranges of scale in both space and in time - and jointly in space-time - without trivializing the links between the measurements, proxies and the state variables (temperature, precipitation etc.). They promise to systematically allow us to compare model outputs with data, to understand the climate processes from small to large and from fast to slow. Specific tools that will be covered include spectral analysis, scaling fluctuation analysis, wavelets, fractals, multifractals, and stochastic modeling; we discuss corresponding software. We also include new developments in the Fractional Energy Balance Equation approach that combines energy and scale symmetries.

The climate system as a whole can be viewed as a highly complex thermal/heat engine, in which numerous processes continuously interact to transform heat into work and vice-versa. As any physical system, the climate system obeys the basic laws of thermodynamics, and we may therefore expect the tools of non-equilibrium thermodynamics to be particularly useful in describing and synthesising its properties. The main aim of this short course will be twofold. Part 1 will provide an advanced introduction to the fundamentals of equilibrium and non-equilibrium thermodynamics, irreversible processes and energetics of multicomponent stratified fluids. Part 2 will illustrate the usefulness of this viewpoint to summarize the main features of the climate system in terms of thermodynamic cycles, as well as a diagnostic tool to constrain the behavior of climate models. Although the aim is for this to be a self-contained module, some basic knowledge of the subject would be beneficial to the participants. Registration is not needed, but indication of interest would be helpful for planning purposes.

Age models are applied in paleoclimatological, paleogeographic and geomorphologic studies to understand the timing of climatic and environmental change. Multiple independent geochronological dating methods are available to generate robust age models. For example, different kinds of radio isotopic dating, magneto-, bio-, cyclostratigraphy and sedimentological relationships along stratigraphic successions or in different landscape contexts. The integration of these different kinds of geochronological information often poses challenges.
Age-depth or chronological landscape models are the ultimate result of the integration of different geochronological techniques and range from linear interpolation to more complex Bayesian techniques. Invited speakers, Sebastian Breitenbach from CL division and Rachel Smedley from the GM division, will share their experience in several modelling concepts and their application in a range of Quaternary paleoenvironmental and geomorphologic records. The Short Course will provide an overview of age models and the problems one encounters in climate science and geomorphology. Case studies and practical examples are given to present solutions for these challenges. It will prepare the participants from CL, GM and other divisions for independent application of suitable age-depth models to their climate or geomorphologic data. For registration please send a request via this email address (ecs-cl@egu.eu) prior to 15th April.

Forecasting and Early Warning Systems (EWSs) help societies prepare for and respond to all types of disasters, including those due to hydro-meteorological hazards. In recent years, there has been a consensus on the need for an interdisciplinary approach to forecasting, and communicating warnings and their inherent uncertainties. The integration of methods and knowledge such as risk, probabilistic and risk-based forecast, impact-based assessments, Information and Communication Technology (ICT) fields, social science and local knowledge can (1) improve the quality of forecast, (2) improve decision making and (3) support better communication of warnings and response. However, one of the biggest challenges is the need to collaborate across relevant disciplines. Therefore new ways of thinking are required on the necessary skills to facilitate more collaborative work.

This short course aims to highlight the benefits and skills required for an interdisciplinary approach in EWS in the form of a role-playing game and discussion. Participants will have the opportunity to understand more about the role of diverse disciplines, their importance in EWS and most importantly, collaborate with people from different backgrounds to come up with a successful solution. The game will be based on a hypothetical emergency situation, in which participants will be required to make decisions based on their assigned role. After the game, an active discussion with all participants will be carried out to propose take away action points on how to improve interdisciplinarity in EWS and how Early Career Scientist (ECS) can contribute to promoting this approach.
At the end of the short course participants should have:
(1) increased awareness and understanding of the roles of EWS actors
(2) Understanding of the necessity to engage and collaborate with professionals from different backgrounds
(3) Newly acquired skills to improve interdisciplinary working and communication

We especially encourage, but not limit, the participation of Early Career Scientists (ECS) interested in the field of Natural Hazards Social, Hydrological and Atmospheric Sciences as well as those who are already working or have in interest working in interdisciplinary fields.
This short course is organised by the Early Warning Systems Young Professionals (EWSYP) Network and the Water Youth Network (WYN)

In 2018, hydrologists from all over the world outlined twenty-three questions that remain unresolved by the scientific community, named Unsolved Problems in Hydrology (UPH). The discussion around them highlighted the need for science driven by technological innovations that is outcome- and/or product-specific. The EGU GA represents a meaningful opportunity for researchers to meet up and share their ideas, although sometimes the scale of the event makes it difficult to actually talk about future projects and develop research proposals. In this Call for Calls session, participants will engage in a sprint-like, competitive event where they will come up with innovative ideas to contribute to the solution of at least one of the UPH.

The session will provide the right atmosphere where researchers can discuss and think about a specific problem, and brainstorm initial ideas to gather information to write an abstract. Attendees are expected to make as much progress as possible. After the session, the participants will be able to continue working if needed. The expected outcome is a project with introduction and plan of action, including outputs such as a paper or collaboration, which will be presented as a short abstract and delivered before 5 pm CEST on the final day of EGU.

Given that the UPH encompasses issues across the hydrological system and human interactions, this session is open to all researchers in water resources and water security. Early-career scientists are particularly encouraged to participate to apply and enhance their current expertise and expand their research network.

With increasing data complexity and growing data volumes, effective and efficient data visualization for data analysis is becoming more important. Different data sets and analysis tasks require different visualization strategies. Geoscience data, being typically multivariate, multidimensional, time-varying, large and sometimes also with uncertainty, demands special attention and care.

This short course aims at providing an overview of commonly available visualization tools that are especially well suited to analyze earth science data sets. We demonstrate the functionality of two selected tools, the general-purpose tool ParaView (www.paraview.org) and the meteorology-specific Met.3D visualization framework (met3d.wavestoweather.de). We show how to easily create meaningful visualizations (including interactive and 3D displays) of gridded atmospheric, oceanic and earth system model data with these tools with only a few steps.

In Hamburg's geoscience community (including the German Climate Computing Centre DKRZ and Universität Hamburg), we have many years of experience in the visualization of earth science data sets. The goal of this workshop is to pass some of our knowledge on to you. More information will be available before the workshop at https://www.dkrz.de/egu2021.

Remote sensing data from Earth orbiting satellites have become indispensable in modern geo-spatial sciences. The technologies underlying the capture of remote sensing data have evolved over the decades which have resulted in an improvement in the data quality, rate of availability and processing.
The workshop will cover tasks such as generating Land Surface Temperature (LST) product from satellite imagery from scratch, extraction of information from ready-made products and raster algebra. Participants will go through a workflow that will present itself as a solution to a real life problem. The main Python libraries or frameworks to be used are rasterio, earthpy, pandas, matplotlib and geopandas. The data to be used will be Landsat 8 satellite imagery.
The first part of the workflow focuses on the extraction of intermediate products that are useful for the calculation of LST from satellite imagery. These products are Normalized Difference Vegetation Index (NDVI), Land Surface Emissivity (LSE) and Fractional Vegetation Cover (FVC). These products are not only useful for calculation of LST but are applicable in other remote sensing applications such as vegetation health monitoring and land cover classification. This section will also equip participants with raster algebra skills using Python.
The second part will cover the pre-processing activity of correcting Landsat 8 thermal bands for the extraction of LST and ultimately generate the LST. The participants will learn how to perform other mathematical operations on raster data using Python.
Finally, LST values at certain desired locations will be extracted. This will equip participants with skills on how to extract information stored as raster files to point features using geospatial Python libraries. In all sections of the workshop, intermediate results will be visualized within the Jupyter Notebook to give participants a hands-on feel of visualization with Python.
It is expected that at the end of a successful completion of the workshop, participants will be able to generate LST from scratch using Landsat 8 imagery and by extension all Landsat imagery with thermal bands. Also, participants should be able to derive other useful products like NDVI from any remote sensing image using the appropriate data and finally acquire raster processing skills useful in other applications.

Cross-cutting uses of different data allow innovations and new perspectives in different fields – research, monitoring, commercial applications development… The promise of a single access to a huge amount of Earth observation data from satellites, in situ observation networks or models about marine, land, atmospheric and climate parameters is now a reality.

The Copernicus Data and Information Access Services (DIAS) give an open and free access to datasets in accordance with the European data policy. The WEkEO DIAS service puts Copernicus and Sentinel data at the fingertips of everyone alongside cloud computing resources and tools.

This short course is an opportunity to learn about the environmental data available from the Copernicus programme and to improve your skills, meeting Earth Observation experts from EUMETSAT, ECMWF and Mercator Ocean ready to share their experiences. The sessions will be interactive, using the WEkEO DIAS service from the JupyterLab platform to the hosted processing solution.

The course covers three main lessons:
I) Introduction on WEkEO environment (environmental data catalogue & computing resources available, introduction to the JupyterLab environment...)
II) Introduction to the Harmonized Data Access and the could resources(efficient way to access and download data, example with Jupyter Notebooks)
III) Demo on use cases (data selection, cloning of a Jupyter Notebook from GitHub, area selection, results)

No experience is necessary as various exercises will be provided for a wide range of skill and applications. Participants should use their own laptops. No installation of software is needed.

Satellite data provides information on the marine environment that can be used for many applications – from water quality and early warning systems, to climate change studies and marine spatial planning. The most modern generation of satellites offer improvements in spatial and temporal resolution as well as a constantly evolving suite of products.

Data from the European Union Copernicus programme is open and free for everyone to use however they wish - whether from academic, governance, or commercial backgrounds. The programme has an operational focus, with satellite constellations offering continuity of service for the foreseeable future. There is also a growing availability of open source tools that can be used to work with this data.

This short course is an opportunity to learn about the marine data from the Copernicus Sentinel-3 satellites provided by EUMETSAT and downstream services including the Copernicus Marine Environment Monitoring service (CMEMS). The short course will be interactive, using the WEkEO DIAS hosted processing, Sentinel Applications Platform (SNAP) software, and Python programming. The short course will also offer some presentations and practical demonstrations focusing on the Copernicus Marine Service portfolio. This part is an occasion to discover the catalogue of products, to learn how to find the relevant data or information and the different way to download the data.

This short course is an opportunity to learn about Copernicus data for Atmospheric Composition and to get examples on how to develop your own workflows based on sample applications. The European Union Copernicus programme is open and free for everyone - whether from academic, government, or commercial backgrounds. The programme has an operational focus, with satellite constellations and services. Satellite data provides composition vital information on key atmospheric constituents at different spatial and temporal scales with continuous improvements in observational spatial and temporal resolution, coverage and measured species as well as a constantly evolving added value products from the Copernicus Atmospheric Monitoring Services.

The sessions will be hands-on and supported by Earth Observation and Model experts to discover data, handle them and produce plots out of a sample of the Copernicus data. You will make use of a series of freely available tools specifically developed for these applications including Jupyter Notebook modules, to have an easy and intuitive way to make use of Python programming. No experience is necessary as various exercises will be provided for a wide range of skill levels and applications. It is recommended to bring your laptop along.

Satellite based climate data records play an increasing role in climate monitoring and help to answer climate related questions. Nowadays satellite based climate data records cover a time period of several decades. EUMETSAT and it’s Satellite Application Facilities (SAF) provide a number of high quality climate data records for various geophysical variables, such as solar radiation, land surface temperature, cloud fractional cover, soil moisture, and many more, derived from both, geostationary and polar orbiting satellites.

These climate data records are free and open to everyone. They continue to be reprocessed to account for improvements of the algorithm and to include recent time periods. In addition to the data, free software tools, such as the CM SAF R Toolbox, are developed and provided by the SAF’s for users to work with the data.

This short course is an opportunity to get an overview about the climate data records available from the EUMETSAT Satellite Application Facilities, learn how to access them and gain some first experiences in how to work with the software tools provided.

EUMETSAT offers over 35 years of meteorological satellite data. New data consistency with previous satellites is ensured by intercalibration and reprocessing. This is a valuable resource for the geoscience communities. EUMETSAT produces 26% of the Essential Climate Variable records identified by the Global Climate Observing System that can be observed from space.

With the new satellite programmes, the volume and complexity of the data products will increase significantly, making it unfeasible for traditional workflows, relying on accessing local data holdings, to exploit these observations. EUMETSAT’s new Data Services, the subject of this course, address this issue.

In this short course you will learn:
• what EUMETSAT offers the geoscience communities within Europe (Data Store, Data Tailor, and visualisation service)
• how to set up access and how to use the GUIs and APIs, Jupiter notebooks and documentation will be available to take away

The Data Store provides online access for directly downloading satellite data via a web-based user interface and APIs usable in processing chains. Users can download the data in its original format or customise it before download by invoking the Data Tailor Service. The View Service provides access via standard OGC Web Map, Web Coverage and Web Feature Services (WMS, WCS, WFS) which visualise data available in the Data Store. It is accessible via a web-based interface and APIs allowing the integration of visualisations in end-user applications.

This short course is open to all attending the EGU and will give you an introduction in how to use the services. User guides will be made available before the event and there will be time for questions and answers.

Under the climate change threat, we need to quantify the spatio-temporal trend of temperature and rainfall patterns to understand and evaluate the potential impacts of climate change on ecosystems services, energy fluxes and biogeochemical processes. There are wide range of global or regional scale climate data freely available in a gridded format that can be used in spatio-temporal analysis studies. These data can be derived directly from satellite remote sensing data or based on reanalysis of time series of weather stations data. Additionally, some gridded data are also developed by the combination of time series of remote sensing data and weather stations data.

Different methodologies have combined spatial data sets and nonparametric statistical methods, such as the Mann-Kendall (MK) test, to infer about the temporal trends of climatic variables. The MK test analyzes if there is, or not, a monotonic trend in the series by calculating difference between earlier and later data points in the time series. Very high positive differences are an indicator of increasing trend whereas very low negative differences indicate decreasing trends. A statistical significance is also calculated for each trend using the normalized test statistic Z. In addition to the trend calculation, it is also possible to quantify the magnitude of the trends. The magnitudes can be estimated by using the nonparametric Sen statistic, more specifically, the Sen’s slope estimator, which is given by the median of the slopes of each pair of points. To calculate the Sen’s slope, the times series data is ordered accordingly to the time (as function of time) and a confidence interval is provided for each slope value.
The objective of this workshop is to give an overview of where to obtain gridded climate data, provide a simple workflow for data wrangling and perform trend analysis on gridded climate data. During the workshop, the participants will learn how to handle and apply different operation on raster data and vector data in R. Some of the operation are: i) crop multiple raster using vector data and save as new files; ii) raster values check (e.g. outliers and NA); iii) conversion of raster into vector polygon data; iv) conversion of spatial data in tabular data (data frames); v) modify and reorganize data frames; vi) create and apply functions; vii) use conditions statements; viii) join operations; ix) create bivariate map; and x) save the results.

Natural hazards pose significant threats to public safety, infrastructure integrity, natural resources, and economic development. In recent years, the frequency and impacts of extreme events have increased substantially in many parts of the world fostering a paradigm shift from traditional stationary statistical models towards models capable of capturing the changing properties of extremes, i.e., nonstationary statistical models. The nonstationarity in such models can be defined by a temporal or process-informed dependence of the observed extremes on an explanatory variable (i.e., a physical driver). Further, a solely statistical-based model might lead to results inconsistent with physics, e.g. unrealistic wave heights in shallow waters. This highlights the need of traditional statistical models including physical constraints in the inference process.

The proposed short course presents the Matlab toolbox ProNEVA which enables users to perform Bayesian statistical analysis under the assumption of nonstationarity, and its latest extension ProNEVAwave specific for analyzing extreme wave heights considering physical constraints in the inference process. The main features of ProNEVA are: parameters estimation of Generalized Extreme Value distribution (GEV), Generalized Pareto distribution (GP), and Log Pearson type III distribution based on Bayesian inference approach; analysis under temporal and process-informed nonstationarity; uncertainty quantification; estimation of return period-return level values for nonstationary analysis (i.e., effective return level and waiting time). The extension ProNEVAwave is developed for statistical analysis of wave heights with the following features: events selection; parameter estimation of stationary GP distribution based on Bayesian inference considering physical constraints via informative priors; uncertainty quantification; estimation of return period-return level curves.

This hands-on short course will provide attendees with some basic knowledge of extreme value analysis under stationary and nonstationary assumptions. Attendees will have hands-on experience on how to apply ProNEVA and ProNEVAwave through a number of applications (e.g., modeling extreme wave heights).

R is an open-source, versatile programming language that is suitable for multi-scale analyses from just a few observations to big data and high-performance computing. It has a growing, enthusiastic user-base (including hydrologists) that is responsible for a continuous stream of ever more efficient and useful packages and workflows.

Running for its fourth year, this EGU short course, co-organised by the Young Hydrologic Society (younghs.com), will introduce and showcase a selection of both core and recently developed R packages that can be applied to data analyses in hydrology, as well as other scientific disciplines.

The course will be delivered by hydrologists with wide experience in subjects including: hydrological modelling (including flood and drought analysis), forecasting, statistics, and eco-hydrology. Topics covered in this years’ course include:
• Data retrieval
• Extremes modelling
• Hydrological modelling
• Hydrological forecasting
• Machine learning
• Open discussion and QA

This course contributes new topics to those delivered in previous years, building upon the openly accessible Github repository for hydrologists using R in their work (https://github.com/hydrosoc).

GEOframe is a system for doing hydrology by computer (https://abouthydrology.blogspot.com/2015/03/jgrass-newage-essentials.html).  It is based on the OMS3/CSIP infrastructure, developed by USDA- ARS/Colorado State University.  OMS3/CSIP allows to build models by components, which perform simple task that can be joined together to build “Modelling Solutions”, suited to particular case studies. Components developed so far cover: meteorological data interpolation (Bancheri et al., 2018), terrain analysis (Abera et al., 2014), calibration tools (Formetta et al., 2011; Formetta et al., 2014), rainfall-runoff models (Bancheri et al., 2020; Formetta et al., 2014), evaporation and transpiration models, snow models (Formetta et al., 2014), Richards’ equations solvers, runoff propagation.

The modelling solution components are executed in parallel by the OMS3/CSIP engine. Besides, a further parallelization is made thanks to the spatial discretisation of the catchments in hydrological response units. GEOframe has been applied to catchments from few thousands of square meters to two hundred thousand square kilometers, and it is also used for operational forecasting in the Basilicata region in Italy. 

The short course introduces the system using some case studies already prepared and show how to join components, set the parameters, run the calibration and obtain results. The course will be based on the material already prepared for various Winter Schools on the topic, which allows the participants to use independently the system.

Bayesian approach to probability theory and statistics has various applications in hydrological sciences, particularly to solve inversion problems and to characterize model uncertainty. From calibrating a hydrological model to quantifying catchment transit time distribution, Bayesian approaches incorporate prior system knowledge that helps us to improve our understanding of the natural system. Using a number of practical case studies, this short course aims at providing a state-of-the-science overview of the usage of Bayesian statistics in different facets of hydrological modeling.

We kindly invite early career researchers (MSc students, PhD candidates, post-doctoral researchers) to attend this short course designed to address the fundamentals of Bayesian statistics and its particular applications in hydrology.

This will be the sixth year that the Hydroinformatics for Hydrology short course takes place during the EGU conference. Information to this and former short course topics can be found online on the homepage of the cooperating Young Hydrologic Society (http://younghs.com).

Data assimilation combines observational data with a numerical model. It is commonly used in numerical weather prediction, but is also applied in oceanography, hydrology and other areas of Earth system science. By integrating observations with models in a quantitative way, data assimilation allows to estimate model states with reduced uncertainty, e.g. to initialize model forecasts. Also, it can estimate parameters that control processes in the model or fluxes. Hence, it can provide information about non-observable quantities if the model represents those. The combination of modeled and observed data requires error estimates for both sources of information. In ensemble data assimilation the error in the model state is estimated by an ensemble of model state realizations. This uncertainty estimate is then used by the assimilation method like the ensemble Kalman filter or a particle filter.

To simplify the implementation and use of ensemble data assimilation, the Parallel Data Assimilation Framework (PDAF) has been developed. PDAF is a freely available open-source software (http://pdaf.awi.de) that provides ensemble-based data assimilation methods like the ensemble Kalman filter, but also allows to perform pure ensemble simulations. PDAF can be used from small toy problems running on notebook computers up to high-dimensional Earth system models running on supercomputers.

The course will, after a short introduction to the ensemble data assimilation methodology, provide a hands-on and interactive example of building a data assimilation system based on a simple numerical model. This practical introduction will prepare the participants to build a data assimilation system for their numerical models with PDAF and hence provide a quick start for applying ensemble assimilation to their individual problems.

This course is both for the novices as well as for data-assimilation experts. It will be useful for novices who have a modelling application and observations and are interested in applying data assimilation, but haven't found a starting point yet. Data-assimilation experts who want to enhance the performance of their applications, or are keen to accelerate development of new data-assimilation methods and new applications will also benefit from the course.

For the interactive hands-on example we will provide source code for download at http://pdaf.awi.de/EGU2021 from April 19.

During the recent years, it has become more and more obvious that soil structure plays a fundamental role in regulating processes in soils. As soil structures are hierarchical, complex and highly variable, studies involving soil structures require a relatively large number of replicate samples. Three-dimensional X-ray imaging provides an excellent tool to map out soil structure, but image analyses are still time intensive and require experience. This limits the number of X-ray images, and thus replicate samples that can be analyzed within reasonable time scales. SoilJ is an open-source and free plugin for the open-source image processing software ImageJ. It is tailor-made for the analyses X-ray images of soil and aims at automatizing the necessary image processing and analyses steps. This course gives a short introduction into X-ray image processing and analyses in general and specifically with SoilJ, provides an overview about SoilJ functionalities and offers guidance for researchers interested in participating in developing their own plugins. In the second part of this short course, hands-on for X-ray image analyses is offered.

You have observed timeseries or observed fields from hydroclimatic variables (e.g., rainfall, wind, etc.) or from other environmental variables. You wish to generate synthetic ones that reproduce precisely the observed statistical properties, but you do not how to do it. No worries! Join us and you will find out!

The short course will introduce you to a unified method of stochastic modelling and the CoSMoS R-package that makes generation of random fields and of univariate or multivariate time series piece of cake. The generated random fields or time series preserve any desired probability distribution and correlation structure including features like spatial and temporal intermittency. We will talk about the stochastic properties of hydroclimatic processes such as precipitation, streamflow, wind, temperature, etc., and highlight features such as stationarity, cyclostationarity, marginal distributions, spatiotemporal correlations structures, and intermittency. We will explain how AR and multivariate AR models work and describe step-by-step the parent-Gaussian framework that allows precise and easy simulation of random fields and time series. Real-world examples include rainfall simulation at different spatiotemporal scales as well as simulating variables such as temperature, relative humidity, etc.

Early Career Scientists (ECS) and student are more than welcome! As always, we organize this short course in cooperation with the Young Hydrologic Society (YHS; younghs.com)!

This short course introduces and gives practical examples on how to use the TRACMASS Lagrangian trajectory code version 7 to study the oceans and the atmosphere. Lagrangian trajectories are a powerful tool for studying connectivity, transport, dispersion etc. in geophysical flows. TRACMASS v7.0 includes a variety of new features and has also been extensively rewritten to make it more user-friendly and improve performance.

We will provide a brief introduction to the algorithm used to solve trajectory positions in TRACMASS as well as showcase examples of case studies on a variety of spatial and temporal scales in oceanography and meteorology. Case studies will include: tracing deep water from the Southern Ocean to the Atlantic, calculating trajectories using data from satellite altimetry, etc. We will also demonstrate a new tool to post process and analyse trajectory data from TRACMASS.

A large part of the short course will be devoted to a walkthrough on how to download, install and configure TRACMASS. This will be followed by running TRACMASS on some example data from the NEMO ocean model and atmospheric reanalysis (ERA-5) and then analyse the results. The analysis will cover e.g. calculating Lagrangian stream functions, connectivity and some Lagrangian statistics like dispersion etc.

Participants will be able to set up TRACMASS for their own application and understand the results which will be particularly useful for early-career scientists looking to add new tools to their scientific arsenal. Users should bring their own laptops.
The course is aimed for those with no previous experience with Lagrangian trajectories but more advanced participants will also have the opportunity to further develop their skills. Basic knowledge of Linux/UNIX commands is necessary. Knowledge in Fortran and Python is preferable, but not necessary.
For more information about TRACMASS, see: https://tracmass.readthedocs.io/en/latest/

Quantitative geomorphological and environmental analysis requires the adoption of well–defined spatial domains as basic mapping units. They provide local boundaries to aggregate environmental and morphometric variables and to perform calculations, thus they identify the spatial scale of the analysis. Grid cells, typically aligned with a digital elevation model, are the standard mapping unit choice. A wiser choice is represented by slope units, irregular terrain partitions delimited by drainage and divide lines that maximise geomorphological homogeneity within each unit and geomorphological heterogeneity between neighbouring units. Adoption of slope units has the advantage of enforcing a strong relation with the underlying topography, absent in grid cell–based analyses, but their objective delineation is a challenge. A given study area admits different slope unit maps differing in number and size of units. Here, we describe a parametric delineation for slope units, using the r.slopeunits software in GRASS GIS.

The r.slopeunits software implements an algorithm that defines a mosaic of SUs bounded by drainage and divide networks based on iterative extraction of the boundaries of hydrological “half-basins” from terrain information available from a DEM. To single out individual SUs from the half-basins, r.slopeunits assumes that homogeneity (heterogeneity) within (between) SUs is controlled by the variability of terrain aspect in each SU. The procedure begins with the delineation of a set of a few large half-basins characterised by a large upslope contributing area, which is iterated - for half-basins not meeting size and homogeneity criteria - with decreasing values of the contributing area, until the entire study area is covered by a mosaic of SUs, of different sizes and shapes.

The aim of the short course is to enable the attendees to use r.slopeunits in their laptops. We will provide a Linux virtual machine (intended for VirtualBox, running on any operating system) containing the software and necessary libraries. Attendees will need basic understanding of GIS concepts, and they will be guided through the specifics of processing within GRASS GIS for execution of r.slopeunits. They will be guided through a complete example of slope unit delineation, starting from the import of the DTM into the GRASS GIS environment to the production of slope units in vector layer format.

Organized in cooperation with NhET (Natural hazards Early career scientists Team)

The objective of this course is to teach geoscientists, engineers and researchers all the basics about 3D structural geological modeling using our open-source Python libraries: GemPy and GemGIS.

GemPy ([https://www.gempy.org/](https://www.gempy.org/)) is an implicit geological modeling library that in recent years have become a core component on the open source geoscientific ecosystem. Originally built to analyze uncertainty of structural models - by the use of Bayesian networks, GemPy is capable to represent complex geological geometries - e.g. folds, faults, unconformities - with a reduce number of parameters. In addition, GemPy provide an array of compatible addons and assets such as built-in visualization (powered by vtk), topology analysis, forward geophysics or volumetric kriging. GemGIS is compatible open-source geographic information processing library, capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages), raster data, data obtained from WMS services or XML/KML files.

The course will give an introduction to much of these functionality including step-by-step tutorials in Jupyter notebooks. Some of the topics will be

- Installation
- Your first model from scratch: conformable layers, unconformities, faults, geophysics, topology
- Modeling landscape: Short theoretical overview
- GemGIS: Importing data from QGIS to GemPy

The course is aimed at PhD students, early career scientist and programming enthusiasts. Jupyter notebooks will be provided and attendees are encourage to follow along programming. Simply just listening to familiarize with the software and its key features is also welcome.

The Magma Chamber Simulator (MCS) is a thermodynamically self-consistent computer code that simultaneously models complex magma mixing, crustal assimilation, and crystal fractionation processes in a user-constrained magmatic system. Using rigorous thermodynamics, MCS tracks its thermal, mass, and compositional (major/trace element, isotope, and phase equilibria) evolution.

MCS can be applied to a wide range of research subjects from the evolution and growth of the crust to origins of volcanic phenomena. More specifically, MCS can be used to model whole-rock, mineral, and melt inclusion major/trace element and isotopic data from natural systems. Among the many goals for such modeling are defining which processes dominate at a particular volcano/pluton, and documenting the temporal balance of mantle versus crust contributing to a magma system. MCS has broad appeal to interdisciplinary groups of petrologists, geochemists, and volcanologists, or anyone who is interested in how researchers try to replicate natural magmatic systems.

On this short course, we will provide an introduction on how MCS operates and what kind of input and output is related to it. To show this, we will run an example simulation accompanied with a visualization of the modeled system.

If they so wish, the attendees can run the example simulation on their personal computer or laptop. For those who want to do this, necessary information and instructions will be shared in the Session Materials.

Do you want to know something more about the Earth's magnetic field? Reconstructions based on paleomagnetic, ground observatories and satellite data are a very suitable way to provide vital information to understand the most intriguing features of the geomagnetic field such as the South Atlantic Anomaly and geomagnetic transitions. But what about their limitations? Which are the most updated models and their main characteristics? If you are interested in knowing the geomagnetic field evolution in different timescales, come on to this course and ask your expert! We are waiting for you!