Taking inspiration from the Mathematics of Planet Earth 2013 initiative, this session aims at bringing together contributions from the growing interface between the geophysical, the mathematical, and the theoretical physical communities. Specific topics include: PDEs, numerical methods, extreme events, statistical mechanics, large deviation theory, response theory, model reduction techniques, coarse graining, stochastic processes, parametrizations, data assimilation, and thermodynamics. We invite talks and poster both related to specific applications as well as more speculative and theoretical investigations. We particularly encourage early career researchers to present their interdisciplinary work in this session.

The Earth system, consisting many interacting (sub)components, has strong internal variability on many time scales, is subject to a non-stationary forcing and mostly out of equilibrium with the changes in the radiative forcing. Large-scale transitions occur, for example due to the existence of tipping points in components of the climate system, and these in many cases depend on the complex interaction between different sub-systems. Moreover, the role of small-scale processes (in many models represented as noise) to induce these transitions is not well known for many important tipping elements.

In climate science, the concept of equilibrium and transient climate sensitivity is widely used for understanding how the climate changes in response to natural and anthropogenic radiative forcing. Over the last decade considerable progress has been made in understanding and defining climate sensitivity. Nevertheless, the uncertainty in climate sensitivity remains high. Moreover, its scope is quite limited, because it deals only with long term changes of the globally averaged surface temperature and is unable to account for the existence of tipping elements and large scale transitions.

The session aims at addressing the problem of connecting fluctuations and response for the climate system, including issues like climate sensitivity, climate variability, extreme events and tipping points. In particular, general approaches and novel measures to quantify the climate response to non-stationary forcing in the climate system are encouraged.
We also aim at studying the complex interactions between the different components and subcomponents of Earth system in order to understand how these interactions influence on system/subsystems (potentially tipping) behavior. External forcing may also impact the nature of interaction between connected subsystems. The submissions which are focused on the study of reasons and mechanisms of the emergent behavior are especially welcome. Such behavior may be inferred from time-dependent connectivity in data, first principle and data-driven modelling.

We welcome contributions that investigate specific feedbacks and their impact on climate sensitivity in all components of the climate system; processes on intermediate to long time scales that are generally difficult quantify such as ocean heat uptake are particularly encouraged. In addition, we welcome contributions studying the state dependence of climate sensitivity, including those focusing on the potential proximity of tipping points.

This is a merged session of 'Climate Sensitivity, Climate Response, and Tipping Points' and 'Networked connections in geosystems: revealing, studying of mechanisms, evolution in time, influence on emergent behavior'.

In both climate modelling and numerical weather prediction, numerical models of the Earth System are used extensively. For the both the atmosphere and ocean such models consist of a fluid dynamics solver (dynamical core) coupled to physics parameterizations to represent processes that occur below the grid scale (physics). Over time these models have become capable of sophisticated simulations, incorporating such features as multi-scale prediction, structure-preserving discretization and a detailed treatment of physics. New work is constantly being undertaken to improve the accuracy and efficiency of these models, both the dynamical core and the physics.

This session encompasses the development, testing and application of novel numerical techniques for Earth system models, including new discretizations, test cases, advection schemes, vertical discretizations, adaptive multi-scale models, physics-dynamics coupling, global and regional climate and NWP models, structure-preserving discretizations and parameterizations (that are not covered in other sessions).

The quality of predictions of weather and climate depends on both resolution and complexity of the models that are used. However, resolution and complexity are limited by the computational performance that is available on today's supercomputers. While weather and climate models run on some of the fastest supercomputers of the world, models typically fail to run close to peak performance such that there is still room for a significant speed-up if efficiency is improved. The increase in parallelisation in high performance computing and the availability of various computing platforms is imposing significant challenges for the community to find the optimal hardware/model configuration and to achieve the best performance. On the other hand, the evaluation of high resolution simulations is often tedious due to large data volumes, limited statistic that is affordable and changed model behaviour that needs to be studied (e.g. if convection or eddies are resolved explicitly or if non-hydrostatic equations need to be used).
These challenges can only be addressed appropriately in a close collaboration between Computing and Earth System Scientists. This session aims to bring together scientists who run and evaluate atmosphere and ocean models with high resolution and complexity as well as scientists who enable these models to run as efficiently as possible on existing and future high performance computing architectures (regarding both model development and model optimisation). The session will also be an opportunity for scientists from the EU projects PRIMAVERA, ESCAPE and ESiWACE as well as HighResMIP from CMIP6 to meet and interact.

V. Balaji from Princeton University will be our keynote speaker invited by the ESiWACE EU Horizon2020 COE (grant number 675191).

Prediction of the areas threatened by landslides and gravity-driven mass flows are a key part of hazard assessment in mountainous regions. Whatever the material transported (debris, snow, etc.), the granular flow process involves determining the initiation mechanisms, initial volume, physical transport, entrainment processes as well as deposition and phase-separation mechanisms. Because of the number of scientific disciplines needed to solve it, there is a substantial benefit from interdisciplinary research. Furthermore, the definition of a unified rheology that accounts for the different regimes characterizing granular-fluid mixture flows is still lacking. The co-existence of the
collisional regime and the dense regime that have a very different behavior, makes the definition of a proper rheology quite challenging. So is the transition from dilute to dense regimes in granular-fluid
mixture flows.

This session aims to bring together new research results from a variety of different approaches to understanding these kinds of processes. In particular, we encourage presentations on physical modelling, innovative laboratory research, theoretical studies on the physics of multiphase and multiscale phenomena and detailed field observations, which yield insight into the triggering mechanisms, the mass movement or mass flow process. Another important aspect, still unclear, that will be addressed in the session, is the mechanism and consequence of grain sorting and particle-fluid separation, entrainment and deposition in debris and hyperconcentrated flows. A proper description of the granular-fluid mixture flow phenomena is fundamental in order to properly define the design criteria of the protection structures and to have reliable risk maps. So, contributions related to the numerical modelling of landslides and granular geophysical flows, including torrential sediment transport, debris flows, rock and snow avalanches, and similar flows are expected.

Selected contributions will be considered for a special issue of a relevant international journal.

Tipping elements in the Earth's climate system are continental-scale subsystems that are characterized by a threshold behavior. It has been suggested that these include biosphere components (e.g. the Amazon rainforest and coral reefs), cryosphere components (e.g. the Greenland and Antarctic ice sheets) and large-scale atmospheric and oceanic circulations (e.g. the thermohaline circulation, ENSO and Indian summer monsoon). Once operating near a threshold or tipping point, these components can transgress into a qualitatively different state by small external perturbations. The large-scale environmental consequences could impact the livelihoods of millions of people.

In this session, we aim to bring together experts presenting and discussing the state-of-the-art research on tipping elements in the Earth's climate system, both in empirical data and numerical modelling of past, present and future climate. Among other topics, issues to be addressed in this session include critical thresholds for specific tipping elements, typical time scales of tipping, interactions and feedbacks between tipping elements, the potential for tipping cascades as well as environmental and socio-economic impacts of tipping.

Papers are solicited related to the understanding and prediction of weather, climate and geophysical extremes, from both an applied sciences and theoretical viewpoint.

In this session we propose to group together the traditional geophysical sciences and more mathematical/statistical approaches to the study of extremes. We aim to highlight the complementary nature of these two viewpoints, with the aim of gaining a deeper understanding of extreme events.

Potential topics of interest include but are not limited to the following:

· How extremes have varied or are likely to vary under climate change;
· How well climate models capture extreme events;
· Attribution of extreme events;
· Emergent constraints on extremes;
· Linking dynamical systems extremes to geophysical extremes;
· Geophysical flows as a dynamical system: classification of large-scale flows and metastable states;
· Advances in diagnosing local and mean properties of the climate system as a dynamical system (e.g. maximum entropy production principles);
· Extremes in dynamical systems;
· Dynamical systems metrics as indicators of climate change;
· Dynamical downscaling of weather and climate extremes.

Confirmed Invited Speakers are:
-David Barriopedro (Complutense University of Madrid, Spain)
-Pascale Braconnot (IPSL, France)
-Nikki Vercauteren (Freie Universitaet Berlin, Germany)

Recent years have seen a substantial progress in the understanding of the nonlinear and stochastic processes responsible for important dynamical aspects of the complex Earth system. The Earth system is a complex system with a multitude of spatial and temporal scales which interact nonlinearly with each other. For understanding this complex system new methods from dynamical systems, complex systems theory, complex network theory, statistics and climate and Earth sciences are needed.

In this context the session is open to contributions on all aspects of the nonlinear and stochastic dynamics of the Earth system, including the atmosphere, the ocean and the climate system. Communications based on theoretical and modeling studies, as well as on experimental investigations are welcome. Studies that span the range of model hierarchy from idealized models to complex Earth System Models (ESM), data driven models, use observational data and also theoretical studies are particularly encouraged.

Invited speaker: Cecile Penland (NOAA)

ENSO is the dominant source of interannual climate variability in the tropics and across the globe. Understanding ENSO's dynamics, predicting El Niño and La Niña, and anticipating changes in ENSO's characteristics and impacts are thus of vital importance for society. This session invites contributions regarding the dynamics of ENSO, including multi-scale interactions; low frequency, decadal and paleo ENSO variability; ENSO theory; ENSO diversity; ENSO impacts on climate, society and ecosystems; ENSO teleconnections; seasonal forecasting of ENSO; and climate change projections of ENSO. Studies aimed at understanding ENSO in models of a range of complexity are especially welcomed, including analysis of CMIP model intercomparisons.

Hydrology is a rich multidisciplinary field encompassing a complex process network involving interactions of diverse nature and scales. Still, it abides to core dynamical principles regulating individual and cooperative processes and interactions, ultimately relating to the overall Earth System dynamics. This session focuses on advances in theoretical and applied studies in hydrologic dynamics, regimes, transitions and extremes along with their physical understanding, predictability and uncertainty. Moreover, it welcomes research on dynamical co-evolution, feedbacks and synergies among hydrologic and other earth system processes at multiple spatiotemporal scales. The session further encourages discussion on physical and analytical approaches to hydrologic dynamics ranging from traditional stochastic, information-theoretical and dynamical analysis to general frameworks addressing non-ergodic and thermodynamically unstable processes and interactions.
Contributions are welcome from a diverse community in hydrology and the broader physical geosciences, working with diverse approaches ranging from dynamical modelling to data mining and analysis with physical understanding in mind.

This session will highlight scaling and nonlinear dynamics modelling, and the analysis of scaling properties of climate, atmosphere, ocean, and geophysical fields. Contributions dealing with models of various degrees of complexity around these topics are welcome. This session focuses on methods, observations, and data analyses aiming to identify such scaling ranges and characterize them using different methods and models.

This session also aims at bringing together climatologists and paleoclimatologists from the modelling and proxy-data acquisition communities in addition to scientists from the nonlinear geoscience community with the aim to develop tools for understanding, comparing and modelling time series and spatial distributions over wide scale ranges so as to better understand and quantify the climate variability in time and space while taking into account intrinsic uncertainties. Members of the PAGES working group on Climate Variability Across Scales (CVAS) are welcome.

Contributions that improve the quantification, understanding and prediction of climate variability in the Earth System across space and time scales are encouraged. This includes case studies, idealized or realistic modeling, synthesis, and model-data comparison studies that provide insights into past, present and future climate variability on local to global, and synoptic to orbital timescales.

Specific topics include:
• theoretical and experimental studies of turbulence, and related cascade models;
• passive and active scalar diffusion/transport (including clouds and precipitation);
• variability and coupling across a broad range of scales in climate;
• scaling properties in climate models;
• land/atmosphere and ocean/atmosphere interactions;
• geological, geophysical, geochemical and remote sensing for mineral exploration and geological assessment;
• scaling and nonlinear aspects of physical, biological, chemical fields in the ocean and freshwaters;
• Multiscale analysis; Methods for fractal and multifractal analysis of data;
• Scaling time series analysis in the atmosphere, ocean and geosciences.

Scheduling notes:
• Richardson medal lecture by Shaun Lovejoy
• invited talk: “The stochastic climate model shows that underestimated Holocene trends and variability represent two sides of the same coin” by Gerrit Lohmann

This session addresses two sub-topics: the small scale variability of precipitation, and the atmospheric water cycle. It adopts a PICO format which aims at employing the most modern and captivating environment of scientific exchange (i.e., a 2-minute oral presentation, nicknamed "2-minute madness", followed by an interactive poster presentation on dedicated touch-screens, https://egu2019.eu/guidelines/pico_presenter_guidelines.html).

Precipitation variability: from drop scale to lot scale

The understanding of small scale spatio-temporal variability of precipitation from seconds in time and drop scale in space to 5 minutes in time and 1 km in space is essential for larger scale studies, including more and more hydrological applications, especially in highly heterogeneous areas (mountains, cities). Nevertheless grasping this variability remains an open challenge. An illustration of the range of scales involved is the ratio between the effective sampling areas of the commonly used point measurement devices (rain gauges and disdrometers) and weather radars, which is greater than 10^7! This session will bring together scientists and practitioners that aim at bridging this scale gap and improving the understanding of small scale precipitation variability, both liquid and solid, as well as its consequences at larger scales.
Contributions addressing one or several of the following issues are especially targeted:
- Novel measurement devices, combinations of devices (both in situ and remote sensors), or experimental set ups enabling to grasp small scale precipitation variability;
- Novel modelling or characterization tools of small scale precipitation variability relying on a wide range of approaches (e.g. scaling, (multi-)fractal, statistic, deterministic, numerical modelling);
- Precipitation drop (or particle) size distribution and its small scale variability, including its consequences for rain rate retrieval algorithms for radars and other remote sensors;
- Physical processes leading to the small-scale rainfall variability
- Examples of hydrological applications where small scale precipitation variability input is required.


The atmospheric water cycle: feedbacks, management, land-use and climate change

Traditionally, hydrologists have always considered precipitation and temperature as input to their models and evaporation as a loss. However, more than half of the evaporation globally comes back as precipitation on land. Land-use changes alter, not only, the local water cycle, but through atmospheric water and energy feedbacks also effect the water cycle in remote locations.
This session aims to:
- show applied studies using fundamental characteristics of the atmospheric branch of the hydrologic cycle on different scales. These fundamentals include, but are not limited to, atmospheric circulation, humidity, residence times, recycling ratios, sources and sinks of atmospheric moisture, energy balance and climatic extremes.
- investigate the remote and local atmospheric feedbacks from human interventions such as irrigation and deforestation on the water cycle, precipitation and climate, based on observations and coupled modelling approaches.
- explore the implications of atmospheric feedbacks on the hydrologic cycle for land and water management. Can we favourably alter atmospheric hydrology and precipitation by means of ground based interventions of changing land cover, and thus changing evaporation, albedo and surface roughness?

Urban hydrological processes are characterised by high spatial variability and short response times resulting from a high degree of imperviousness. Therefore, urban catchments are especially sensitive to space-time variability of precipitation at small scales. High resolution precipitation measurements in cities are crucial to properly describe and analyse urban hydrological response. At the same time, urban landscapes pose specific challenges to obtaining representative precipitation and hydrological observations.
This session focuses on high resolution precipitation and hydrological measurements in cities and on approaches to improve modelling of urban hydrological response:
- Novel techniques for high resolution precipitation measurement in cities and approaches for merging remote sensing data with in situ measurements to obtain representation of urban precipitation fields;
- Novel approaches to hydrological field measurements in cities, including data obtained from citizen observatories;
- Novel approaches to modelling urban catchment properties and hydrological response, from physics-based models, fully and semi-distributed modelling to stochastic and statistical conceptualisation;
- Applications of measured precipitation fields in urban hydrological models to improve prediction of flood response and real-time control of stormwater systems for pollution load reduction;
- rainfall modelling for urban applications, including stochastic rainfall generators.

Hydroclimatic variability is an emerging challenge with increasing implications on water resources management, planning, and the mitigation of water-related natural hazards. The above variability, along with the continuous development of water demands, and aging water supply system infrastructure make the sustainability of water use a high priority for modern society. In fact, the Global Risk 2015 Report of the World Economic Forum highlights global water crises as being the biggest threat facing the planet over the next decade.
To mitigate the above concerns we need to shed light on hydroclimatic variability and change. Several questions and mysteries are still unresolved regarding natural fluctuations of climate, anthropogenic climate change and associated variability, and changes in water resources. What is a hydroclimatic trend? What is a (long term) cycle? How can we distinguish between a trend and a cycle? Is such discrimination technically useful? How do human activities affect rainfall, hydrological change and water resources availability? How to set priorities and take action to ensure sustainability in light of variability and change?
The objective of this session is to explore hydrological and climatic temporal variability and their connections and feedbacks. More specifically, the session aims to:
1. investigate the hydrological cycle and climatic variability and change, both at regional and global scales;
2. explore the interplay between change and variability and its effect on sustainability of water uses;
3. advance our understanding of the hydrological cycle, benefiting from hydrological records and innovative techniques; and
4. improve the efficiency, simplicity, and accurate characterization of data-driven modeling techniques to quantify the impacts of past, present and future hydroclimatic change on human societies.
This session is sponsored by the International Association of Hydrological Sciences (IAHS) and the World Meteorological Organization – Commission for Hydrology (WMO CHy) and it is also related to the scientific decade 2013–2022 of IAHS, entitled “Panta Rhei - Everything Flows”.

This interdisciplinary session welcomes contributions on novel conceptual approaches and methods for the analysis of observational as well as model time series and associated uncertainties from all geoscientific disciplines.

Methods to be discussed include, but are not limited to:
- linear and nonlinear methods of time series analysis
- time-frequency methods
- predictive approaches
- statistical inference for nonlinear time series
- nonlinear statistical decomposition and related techniques for multivariate and spatio-temporal data
- nonlinear correlation analysis and synchronisation
- surrogate data techniques
- filtering approaches and nonlinear methods of noise reduction

We particularly encourage submissions addressing the problem of uncertainty of geoscientific time series and its treatment in the context of statistical and dynamical analysis, including:
- representation of time series with uncertain dating (in particular paleoclimatic records from ice cores, sediments, speleothems etc.)
- uncertainties in change point / transition detection
- uncertainty propagation in time series methods like correlation, synchronization, spectral analysis, PCA, networks, and similar techniques
- uncertainty propagation in empirical (i.e., data-derived) inverse models

This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and detailed modeling efforts across various fields of geosciences. Topics of this session will include the identification and handling of specific problems arising from the need to analyze such large-scale data sets, together with methodological approaches towards semi or fully automated inference of relevant patterns in time and space aided by computer science-inspired techniques. Among others, this session shall address approaches from the following fields:
• Dimensionality and complexity of big data sets
• Data mining in Earth sciences
• Machine learning, including deep learning and other advanced approaches
• Visualization and visual analytics of big data
• Informatics and data science
• Emerging big data paradigms, such as datacubes

The mid-Pleistocene Transition (MPT) is a crucial changes in climate dynamics, leading us into our current regime of long, asymmetric glacial cycles. However, evidence about the differences in how climate behaved before and after the MPT remains sparse and we also lack evidence to decide between theories that aim to explain the MPT. Here we hope to gather new datasets that compare climate on either side of the MPT or that offer new evidence about glacial cycles before it. Modelling and conceptual work about the causes of the MPT are also wlecome. Finally we would like to hear about work that paves the way for new projects, including plans and methodologies to obtain pre-MPT ice cores such as (but not limited to) the IPICS Oldest Ice challenge, like Beyond EPICA and other endeavours.

Environmental systems often span spatial and temporal scales covering different orders of magnitude. The session is oriented in collecting studies relevant to understand multiscale aspects of these systems and in proposing adequate multi-platform surveillance networks monitoring tools systems. It is especially aimed to emphasize the interaction between environmental processes occurring at different scales. In particular, a special attention is devoted to the studies focused on the development of new techniques and integrated instrumentation for multiscale monitoring high natural risk areas, such as: volcanic, seismic, slope instability and other environmental context.
We expect contributions derived from several disciplines, such as applied geophysics, seismology, geodesy, geochemistry, remote sensing, volcanology, geotechnical and soil science. In this context, the contributions in analytical and numerical modeling of geodynamics processes are also welcome.
Finally, a special reference is devoted to the integration through the use of GeoWeb platforms and the management of visualization and analysis of multiparametric databases acquired by different sources

Over the past several years, interest in earthquake foreshocks has experienced considerable growth. This can, on one side, be explained by a largely improved observational database that spans all seismic scales. A development that is driven by a growing number of permanent seismic stations and large-scale campaign networks, the development of advanced detection and analysis techniques, and by the improvement of laboratory equipment and techniques. In addition, the ongoing endeavor to better understand induced seismicity has been contributing to this upgrowth with densely-monitored underground lab-scale experiments and enhanced microseismic monitoring. On the other side, earthquake foreshocks are widely perceived as one of the few and, as of now, most direct observations of earthquake nucleation processes.

Foreshocks are generally thought to arise by one of two mechanisms: cascading failure or preslip. The cascading model proposes that a mainshock following a foreshock has an identical origin to that of aftershocks. In this case, earthquake frequency-magnitude statistics predict that occasionally an aftershock will be larger than the prior event, which makes the prior event a foreshock only after the fact. The mechanism proposed by the preslip model is that premonitory processes - perhaps fault creep related to mainshock nucleation - result in stress changes that drive the foreshock process. Seismologists have found no agreement so far; this is made more difficult by two facts: that no agreed-upon, universal strategy to identify foreshocks in a seismic catalog exists and that data quality and quantity vary considerably over spatial and temporal scales.

In this session, we want to bring together scientists from all disciplines working on, or interested in, earthquake foreshock occurrence. We invite reports on observational and theoretical studies on all scales. This includes laboratory and deep underground experimental earthquakes, as well as microseismic to megathrust earthquakes. We also encourage submissions from colleagues working on advanced detection and analysis techniques for improved foreshock identification.

As the number of palaeoclimate data from glacial, marine, and continental archives is growing continuously, large-scale compilation and cross-comparison of these data is the imperative next phase in paleoclimate research. Large data sets require meticulous database management and new analysis methodologies to unlock their potential for revealing supra-regional and global trends in palaeoclimate conditions. The compilation of large scale datasets from proxy archives faces challenges related to record quality and data stewardship. This requires record screening and formulation of principles for quality check, as well as transparent communication.

This session aims to bring together contributions from paleoclimatic studies benefiting from the existence of such large data sets, e.g., providing a novel perspective on a proxy and the represented climate variables from the local to the global scale. We want to bridge the gap between data generation and modelling studies. In particular, comparing such large proxy-based datasets with climate modelling data is crucial for improving our understanding of palaeoclimate archives (e.g., bias effects and internal processes), to identify signal and noise components and their temporal dynamics, and to gain insight into the quality of model data comparisons.

We encourage submissions on data compilations, cross-comparison and modelling studies utilizing data repositories and databases (e.g., SISAL, PAGES2k, ACER, EPD), including, but not limited to:
-Comparative studies using one or several archives (e.g., including tests of temporal and spatial synchronicity of past regional to global climate changes)
-Proxy system models (and their tuning)
-Model data comparisons (including isotope enabled models or local calibration studies)
-Integrative multi-proxy/multi archive approaches at multiple study sites
-Large scale age model comparisons and record quality assessment studies, including methods aimed at cross validation between different records and variable spatial and temporal scales.

The availability of high spatial resolution Synthetic Aperture Radar (SAR) data, the advances in SAR processing techniques (e.g. interferometric, polarimetric, and tomographic processing), and the fusion of SAR with optical imagery as well as geophysical modelling allow ever increasing use of Imaging Geodesy using SAR/InSAR as a geodetic method of choice for earth system monitoring and investigating geohazard, geodynamic and engineering processes. In particular, the exploitation of data from new generation SAR missions such as Sentinel-1 that provide near real-time measurements of deformation and changes in land cover/use has improved significantly our capabilities to understand natural and anthropogenic hazards and then helped us mitigate their impacts. The development of high-resolution X-band SAR sensors aboard missions such as Italian COSMO-SkyMed (CSK) and German TerraSAR-X (TSX) has also opened new opportunities over the last decade for very high-resolution radar imaging from space with centimetre geometric accuracy for detailed analysis of a variety of processes in the areas of the biosphere, geosphere, cryosphere and hydrosphere. All scientists exploiting radar data from spaceborne, airborne and/or ground-based SAR sensors are cordially invited to contribute to this session. The main objective of the session is to present and discuss the progress, state-of-the-art and future perspectives in scientific exploitation of SAR data, mitigating atmospheric effects and error sources, cloud computing, machine learning and big data analysis, and interpretation methods of results obtained from SAR data for various types of disasters and engineering applications such as earthquakes, volcanoes, landslides and erosion, infrastructure instability and anthropogenic activities in urban areas. Contributions addressing scientific applications of SAR/InSAR data in biosphere, cryosphere, and hydrosphere are also welcome.

Many situations occur in Geosciences where one wants to obtain an accurate description of the present, past or future state of a particular system. Examples are prediction of weather and climate, assimilation of observations, or inversion of seismic signals for probing the interior of the planet. One important aspect is the identification of the errors affecting the various sources of information used in the estimation process, and the quantification of the ensuing uncertainty on the final estimate.

The session is devoted to the theoretical and numerical aspects of that broad class of problems. A large number of topics are dealt with in the various papers to be presented: algorithms for assimilation of observations, and associated mathematical aspects (particularly, but not only, in the context of the atmosphere and the ocean), predictability of geophysical flows, with stress on the impact of initial and model errors, inverse problems of different kinds, and also new aspects at the crossing between data assimilation and data-driven methods. Applications to specific physical problems are presented.


Solicited Speakers
Olivier Pannekoucke (Météo-France, Toulouse)
Manuel Pulido (University of Reading)

Statistical post-processing techniques for weather, climate, and hydrological forecasts are powerful approaches to compensate for effects of errors in model structure or initial conditions, and to calibrate inaccurately dispersed ensembles. These techniques are now an integral part of many forecasting suites and are used in many end-user applications such as wind energy production or flood warning systems.

Many of these techniques are now flourishing in the statistical, meteorological, climatological, hydrological, and engineering communities. The methods range in complexity from simple bias correction up to very sophisticated distribution-adjusting techniques that take into account correlations among the prognostic variables.

In this session, we invite papers dealing with both theoretical developments in statistical post-processing and evaluation of their performances in different practical applications oriented toward environmental predictions.

As the societal impacts of hazardous weather and other environmental pressures grow, the need for integrated predictions which can represent the numerous feedbacks and linkages between physical and chemical atmospheric processes is greater than ever. This has led to development of a new generation of high resolution multi-scale coupled prediction tools to represent the two-way interactions between aerosols, chemical composition, meteorological processes such as radiation and cloud microphysics.

Contributions are invited on different aspects of integrated model and data assimilation development, evaluation and understanding. A number of application areas of new integrated modelling developments are expected to be considered, including:

i) improved numerical weather prediction and chemical weather forecasting with feedbacks between aerosols, chemistry and meteorology,

ii) two-way interactions between atmospheric composition and climate variability.

This session aims to share experience and best practice in integrated prediction, including:

a) strategy and framework for online integrated meteorology-chemistry modelling;
b) progress on design and development of seamless coupled prediction systems;
c) improved parameterisation of weather-composition feedbacks;
d) data assimilation developments;
e) evaluation, validation, and applications of integrated systems.

This Section is organised in cooperation with the Copernicus Atmosphere Monitoring Service (CAMS), the "Pan-Eurasian Experiment" (PEEX) multidisciplinary program and the WMO Global Atmosphere Watch (GAW) Programme, celebrating its 30 years anniversary in 2019.

Weather and climate models used for weather forecasts, seasonal predictions and climate projections, are essential for decision making on timescales from hours to decades. However, information about future weather and climate relies on complex, though imperfect, numerical models of the Earth-system. Systematic biases and random errors have detrimental effects on predictive skill for dynamically driven fields on weather and seasonal time scales. Biases in climate models also contribute to the high levels of uncertainty in many aspects of climate change as the biases project strongly on future changes. A large source of uncertainty and error in model simulations is unresolved processes, represented through parameterization schemes. However, these errors typically materialize at large spatial scales. Our physical understanding of the mechanical and dynamical drivers of these large-scale biases is incomplete. Incomplete mechanistic understanding hinders marked improvements in models, including identification of the parameterizations most in need of improvement.

Understanding and reducing the errors in weather and climate models due to parameterizations and poorly represented mesoscale to regional scales processes is a necessary step towards improved weather and climate prediction. This session aims to bring together these two perspectives, and unite the weather and climate communities to address this common problem and accelerate progress in this area.

This session seeks submissions that aim to quantify, understand, and reduce sources of error and bias in weather and climate models. Themes covered in this session include:

- Theory and development of parameterization. Impact on errors in mean state, model variability and physical process representation;

- Improved physical understanding of the drivers of large-scale biases including the use of process studies, idealized modeling studies and studies with strong observational components;

- Growth and propagation of error and bias in models; model errors across temporal and spatial scales; dependency of errors on model resolution and the development of scale-aware parameterization schemes;

- Use of “emergent constraints” to relate present day model biases with the climate change signal;

- Understanding and representing random model error.

Invited presentations: Felix Pithan (AWI) and Bob Plant (University of Reading)

Lead Convenors: Hannah Christensen and Stefan Sobolowski
Co-convenors: Craig Bishop, Ariane Frassoni, Daniel Klocke, Erica Madonna, Isla Simpson, Keith Williams, Giuseppe Zappa

Data assimilation is becoming more important as a method to make predictions of Earth system states. Increasingly, coupled models for different compartments of the Earth system are used. This allows for making advantage of varieties of observations, in particular remotely sensed data, in different compartments. This session focuses on weakly and strongly coupled assimilation of in situ and remotely sensed measurement data across compartments of the Earth system. Examples are data assimilation for the atmosphere-ocean system, data assimilation for the atmosphere-land system and data assimilation for the land surface-subsurface system. Optimally exploiting observations in a compartment of the terrestrial system to update also states in other compartments of the terrestrial system still has strong methodological challenges. It is not yet clear that fully coupled approaches, where data are directly used to update states in other compartments, outperform weakly coupled approaches, where states in other compartments are only updated indirectly, through the action of the model equations. Coupled data assimilation allows to determine the value of different measurement types, and the additional value of measurements to update states across compartments. Another aspect of scientific interest for weakly or fully coupled data assimilation is the software engineering related to coupling a data assimilation framework to a physical model, in order to build a computationally efficient and flexible framework.

We welcome contributions on the development and applications of coupled data assimilation systems involving models for different compartments of the Earth system like atmosphere and/or ocean and/or sea ice and/or vegetation and/or soil and/or groundwater and/or surface water bodies. Contributions could for example focus on data value with implications for monitoring network design, parameter or bias estimation or software engineering aspects. In addition, case studies which include a precise evaluation of the data assimilation performance are of high interest for the session.

The assessment of precipitation variability and uncertainty is crucial in a variety of applications, such as flood risk forecasting, water resource assessments, evaluation of the hydrological impacts of climate change, determination of design floods, and hydrological modelling in general. Within this framework, this session aims to gather contributions on research, advanced applications, and future needs in the understanding and modelling of precipitation variability, and its sources of uncertainty.
Specifically, contributions focusing on one or more of the following issues are particularly welcome:
- Novel studies aimed at the assessment and representation of different sources of uncertainty versus natural variability of precipitation.
- Methods to account for different accuracy in precipitation time series, e.g. due to change and improvement of observation networks.
- Uncertainty and variability in spatially and temporally heterogeneous multi-source precipitation products.
- Estimation of precipitation variability and uncertainty at ungauged sites.
- Precipitation data assimilation.
- Process conceptualization and modelling approaches at different spatial and temporal scales, including model parameter identification and calibration, and sensitivity analyses to parameterization and scales of process representation.
- Modelling approaches based on ensemble simulations and methods for synthetic representation of precipitation variability and uncertainty.
- Scaling and scale invariance properties of precipitation fields in space and/or in time.
- Physically and statistically based approaches to downscale information from meteorological and climate models to spatial and temporal scales useful for hydrological modelling and applications.

Models of the class used in the CMIP6 experiment to make global
climate projections are imperfect representations of reality that
differ widely in regard to the overall magnitude of warming, in their
regional projections, and in their short-range predictions. While
better models of the underlying physical processes are ultimately
needed, immediate improvement may come simply from better methods to
combine existing models. Contributions are solicited on new methods to
fuse models of climate and weather ranging from output averaging techniques to methods that
dynamically combine model components in a synchronizing, interactive
ensemble. The importance (or lack thereof) of nonlinearities in
determining the sufficiency of output averaging is a topic of special
interest.

One of the big challenges in Earth system science consists in providing reliable climate predictions on sub-seasonal, seasonal, decadal and longer timescales. The resulting data have the potential to be translated into climate information leading to a better assessment of multi-scale global and regional climate-related risks.
The latest developments and progress in climate forecasting on subseasonal-to-decadal timescales will be discussed and evaluated in this session. This will include presentations and discussions of predictions for a time horizon of up to ten years from dynamical ensemble and statistical/empirical forecast systems, as well as the aspects required for their application: forecast quality assessment, multi-model combination, bias adjustment, downscaling, etc.
Following the new WCPR strategic plan for 2019-2029, prediction enhancements are solicited from contributions embracing climate forecasting from an Earth system science perspective. This includes the study of coupled processes, impacts of coupling and feedbacks, and analysis/verification of the coupled atmosphere-ocean, atmosphere-land, atmosphere-hydrology, atmosphere-chemistry & aerosols, atmosphere-ice, ocean-hydrology, ocean-ice, ocean-chemistry and climate-biosphere (including human component). Contributions are also sought on initialization methods that optimally use observations from different Earth system components, on assessing and mitigating the impacts of model errors on skill, and on ensemble methods.
We also encourage contributions on the use of climate predictions for climate impact assessment, demonstrations of end-user value for climate risk applications and climate-change adaptation and the development of early warning systems.

A special focus will be put on the use of operational climate predictions (C3S, NMME, S2S), results from the CMIP5-CMIP6 decadal prediction experiments, and climate-prediction research and application projects (e.g. EUCP, APPLICATE, PREFACE, MIKLIP, MEDSCOPE, SECLI-FIRM, S2S4E).

Solicited talk:
Multi-year prediction of ENSO
By Jing-Jia Luo from the Institute for Climate and Application Research (ICAR), Nanjing University of Science Information and Technology, China

Geophysical Fluid Dynamics (GFD) deals with various aspects of the mathematical descriptions of rotating stratified fluids starting from the physical laws of hydro-thermo-dynamics. Physicists and Mathematicians originating from various disciplines developed physical and numerical models with increasing complexity, adding to our fundamental understanding of such flows and thereby unifying these fields. Today GFD is a truly interdisciplinary field of its own, which encompasses multiscale flows of planetary atmospheres and oceans, their weather and climate, and the motions of 'the solid Earth'.

In this session we invite contributions expanding our understanding of the complex behavior of geophysical flows and Turbulence, presenting novel techniques that either facilitate a deeper understanding or improve the efficiency of numerical procedures involved, and/or reviewing major advances in a particular aspect of geophysical fluid dynamics. In these contexts, the role of waves (non-linear, inertial, internal, vorticity or helicity waves), turbulence and transport are an important factor in the understanding of GFD flows.

The interdisciplinary character of dynamical and computational aspects of this session encourages an exchange of ideas and contributions across various fields, such as meteorology, oceanography, astrophysics, geological fluid dynamics, applied mathematics, and computational fluid dynamics with applications to ocean and atmosphere and their Biological influences.
The recent improvements in Remote Sensing of the Earth and other Planets also allows comparison with Laboratory and Numerical Experiments involving Stratification, Rotation, Magnetic Fields, body forces, etc... Other NP6.x sessions address complementary aspects affecting Geo-Astrophysical Turbulence.

The multitude of processes of various scales occurring simultaneously under strong winds in the air and sea boundary layers presents a true challenge for nonlinear science. We want to understand the physics of these processes, their specific role, their interactions and how they can be probed remotely, how these processes differ from their counterparts under moderate/weak winds. We welcome theoretical, experimental and numerical works on all aspects of processes in turbulent boundary layers above and below the ocean surface. Although we are particularly interested in the processes and phenomena occurring under strong wind conditions, the works concerned with similar processes under weaker winds which might provide an insight for rough seas are also welcomed. We are also very interested in works on remote sensing of these processes.
The areas of interest include the processes at and in the vicinity of the interface (nonlinear dynamics of surface water, wave-current-turbulence interactions, , including wave and current stability, wave breaking, generation and dynamics of spray and air bubbles, thermodynamics of the processes in the boundary layers, heat and gas exchange), all the processes above and below the air/water interface, as long as they are relevant for strong wind conditions (such as, e.g. inertial waves generated by changing winds). Relevant nonlinear biological phenomena are also welcomed.

The main aims of the session is to initiate discussion of the multitude of processes active under strong winds across the narrow specializations as a step towards creating an integrated picture. Theoretical, numerical, experimental and observational works are welcomed.

Turbulence, reconnection and shocks are fundamental non-linear processes observed in solar, heliospheric, magnetospheric and laboratory plasmas. These processes are not separate, but rather appear to be interconnected. For instance, a close link exists between reconnection and turbulence. On the one hand the turbulence cascade favors the onset of magnetic reconnection between magnetic islands and, on the other hand, magnetic reconnection is able to trigger turbulence in the reconnection outflows and separatrices. Similarly, shocks may form in collisional and collisionless reconnection processes and can be responsible for turbulence formation, as for instance in the turbulent magnetosheath.

This session welcomes simulations, observational and theoretical works relevant for the study of these non-linear phenomena. Particularly welcome will be works focusing on the link between them in a range of scale going from fluid MHD to kinetic. The topic of this session is relevant for the understanding of solar atmosphere (from the photosphere to the solar wind), interaction of solar wind with planetary magnetospheres, planetary magnetospheric physics and particle acceleration and transport throughout the heliosphere. The session is also relevant to past and present space missions in plasma astrophysics such as Cluster, MMS and Parker Solar Probe.

Public information:
Julia E. Stawarz will give a solicited talk

The energy of a closed system is steady. It is not lost but rather converted into other forms, such as when kinetic energy is transferred into thermal energy. However, this fundamental principle of natural science is often still a problem for climate research. For example, in case of the calculation of ocean currents and circulation, where small-scale vortices as well as diapycnal mixing and the deep convection processes they induce, need to be considered, to compute how heat content is redistributed along the entire water column and how such processes may change in the future. Similarly, in the atmosphere, the conversion of available potential energy into kinetic energy is the key driver of atmospheric dynamics at a variety of scales, from the zonal-mean general circulation to mesoscale convection. Local turbulent processes can drive larger movements and waves on a larger scale can disintegrate into small structures. All these processes are important for the Earth’s climate and determine its evolution in the future.

How exactly the energy transfers between waves, eddies, local turbulence and mixing in the ocean and the atmosphere works, often remains unclear. This session wants to discuss this by inviting contributions from oceanographers, meteorologists, climate modelers, and mathematicians. We are particularly interested in coupled atmosphere-ocean studies, we are also aiming at filling a knowledge gap on deep ocean processes, as well as novel subgrid-scale parameterizations, and studies of the energy budget of the complex Earth system, including the predictability of the global oceanic thermohaline circulation and thus climate variability.

Invited speakers:
Martin Wild, ETH, Zürich, Switzerland
Raffaele Ferrari, MIT, USA
Robert Weller, WHOI and OOI Research Infrastructures, USA

Mesoscale and submesoscale structures such as fronts, meanders, eddies, and filaments are found worldwide, from the global ocean down to marginal seas. During the last years it has been shown that these features play a key role on the advection of heat, salt, biogeochemical properties, and on the enhancement of biological activity gathering all trophic levels. Due to their typical spatial and temporal scales, direct observations of these features remain currently an open challenge and their study requires a joint multi-platform effort combining in situ and remote sensing observations with theory and numerical models.

This session will provide a forum to properly address the new scientific advances associated with:
• Variability of (sub)mesoscale structures through observations (in situ and remote sensing), theory, and numerical simulations.
• 3D dynamics related to (sub)mesoscale features.
• Temporal and spatial interactions between different structures.
• Impact on mixing and transport of hydrographic properties.
• Physical and biogeochemical interactions.
• Limitations and improvements of the observational platforms and numerical simulations.
• A particular emphasis is put on challenges associated with the observation and numerical representation of subsurface (sub)mesoscale eddies.

Solicited speaker: Marina Levy et al., The role of submesoscale currents in structuring phytoplankton diversity

Analysing the propagation of stress waves in heterogeneous geomaterials with internal reflections and non-linearity as well as in granular materials is central to geophysics. Recently new observations and theoretical concepts were introduced that point out to the limitations of the traditional concept. These are:
• Multiscale nature of waves in geomaterials
• Existence of non-reflective waves in the atmosphere and the ocean and the theoretically discovered continuously inhomogeneous media capable of transmitting elastic waves without reflection.
• Indications of slow transmission of disturbances with velocities in the neighborhood of 1000 km/year
• Evidence of the presence and propagation of rotational waves in geomaterials
• Strong rock and rock mass non-linearity (such as bilinear stress-strain curve with high modulus in compression and low in tension) and its effect on wave propagation
• The presence of apparent negative stiffness associated with rotation of non-spherical constituents and its effect on wave propagation
• Active nature of geomaterials (such as seismic emission induced by stress and pressure wave propagation)

Complex waves are now a key problem of the physical oceanography and atmosphere physics. They are called rogue or freak waves. It may be expected that similar waves are also present in non-linear solids (e.g., granular materials), which suggests the existence of new types of seismic waves.

It is anticipated that studying these and related phenomena can lead to breakthroughs in understanding of the stress transfer and multiscale failure processes in the Earth's crust, ocean and atmosphere and facilitate developing better prediction and monitoring methods.

The session is designed as a forum for discussing these and relevant topics.

In many respects internal gravity waves (IGWs) still pose major questions both to the atmospheric and ocean sciences, and to stellar physics. Important issues are IGW radiation from their various relevant sources, IGW reflection at boundaries, their propagation through and interaction with a larger-scale flow, wave-induced mean flow, wave-wave interactions in general, wave breaking and its implications for mixing, and the parameterization of these processes in models not explicitly resolving IGWs. Also the observational record, both on a global scale and with respect to local small-scale processes, is not yet sufficiently able to yield appropriate constraints. The session is intended to bring together experts from all fields of geophysical and astrophysical fluid dynamics working on related problems. Presentations on theoretical, modelling, experimental, and observational work with regard to all aspects of IGWs are most welcome.

Invited speakers: Early career scientist Claudia Stephan (MPI), and Louis Gostiaux (CNRS / École Centrale de Lyon).

We invite presentations on ocean surface waves: their dynamics, modelling and applications. Wind-generated waves are a large topic of the physical oceanography in its own right, but it is also becoming clear that many large-scale geophysical processes are essentially coupled with the surface waves, and those include climate, weather, tropical cyclones, Marginal Ice Zone and other phenomena in the atmosphere and many issues of the upper-ocean mixing below the interface. This is a rapidly developing area of research and geophysical applications, and contributions on wave-coupled effects in the lower atmosphere and upper ocean are strongly encouraged.

The scopes of the session involve different aspects of large-amplitude wave phenomena in the Ocean (such as freak or rogue waves): surface and internal waves, and also waves trapped by currents and bathymetry. The session is focused on the understanding of the physical mechanisms which cause extreme events, and proposing appropriate mathematical models for their description and advanced methods for their analysis. An essential part of such studies are the results of verification of the new models and techniques versus laboratory and in-situ data. Special attention is paid to the description of the wave breaking process, and also large-amplitude wave interaction with coastal structures.

This session welcomes contributions presenting advances in, and approaches to, studying, modelling, monitoring, and forecasting of internal waves in stratified estuaries, lakes and the coastal oсean.

Internal solitary waves (ISWs) and large-amplitude internal soliton packets are a commonly observed event in oceans and lakes. In the oceans ISWs are mainly generated by the interaction of the barotropic tides with the bottom topography. Large amplitude solitary waves are energetic events that generate strong currents. They can also trap fluid with larvae and sediments in the cores of waves and transport it a considerable distance. ISWs can cause hazards to marine engineering and submarine navigation, and significantly impact on marine ecosystems and particle transport in the bottom layer of the ocean and stratified lakes. Contributions studying flows due to internal waves, their origin, propagation and influence on the surrounding environment are of great importance.
The scope of the session involves all aspects of ISWs generation, propagation, transformation and the interaction of internal waves with bottom topography and shelf zones, as well as an evaluation of the role of internal waves in sediment resuspension and transport. Breaking of internal-waves also drives turbulent mixing in the ocean interior that is important for climate ocean models. Discussion of parameterizations for internal-wave driven turbulent mixing in global ocean models is also invited.

As discussed by EGU2017 DB2 and EGU 2018 TM16, there had been an impressive series of international agreements and development of large networks of cites that call for qualitative improvements of urban systems and their interactions with their environment. The main goal of this ITS is to mobilise geoscientists, highlight their present contributions and encourage holistic approaches beyond the traditional silos of urban meteorology/hydrology/climatology/ecology/resilience, as well as some other terms.

Karst environments are characterized by distinctive landforms and unique hydrologic behaviors. Karst systems are commonly extremely complex, heterogeneous, and very difficult to manage because their formation and evolution are controlled by a wide range of geological, hydrological, geochemical and biological processes. Further, karst systems are extremely vulnerable due to the direct connection between the surface and subsurface compartments through conduit networks.
The great variability and unique connectivity may result in serious engineering problems: on one hand, karst groundwater resources are readily contaminated by pollution because of the rapidity of conduit flow; on the other hand, the presence of karst conduits that weakens the strength of the rock mass may lead to serious natural and human-induced hazards. The plan and development of engineering projects in karst environments thus require: 1) an enhanced understanding of natural processes that govern the initiation and evolution of karst systems through both field and modelling approaches, and 2) specific interdisciplinary approaches aiming at at better assessing the associated uncertainties and minimizing the detrimental effects of hazardous processes and environmental problems.
This session calls for abstracts on research related to geomorphology, hydrogeology, engineering geology, and/or hazard mitigation in karst environments in the context of climate change and increased human disturbance. It also aims to discuss various characterization and modelling methods applied in each specific research domain, with their consequences on the understanding of the whole process of karst genesis and functioning.

The session aims to collect original or review contributions on the use of data from Low-Earth-Orbiting (LEO) satellites making measurements in the thermosphere-ionosphere to investigate ionospheric anomalies related to space weather, geophysical and artificial sources. In fact, data from LEO satellites can provide a global view of near-Earth space variability and are complementary to ground-based observations, which have limited global coverage. The AMPERE project and integration of the Swarm data into ESA’s Space Weather program are current examples of this. The availability of thermosphere and ionosphere data from the DEMETER satellite and the new operative CSES mission demonstrates that also satellites that have not been specifically designed for space weather studies can provide important contributions to this field. On the other hand, there are evidences that earthquakes can generate electromagnetic anomalies into the near Earth space. A multi-instrumental approach, by using ground observations (magnetometers, magnetotelluric stations, GNSS receivers, etc.) and LEO satellites (DEMETER, Swarm, CSES, etc.) measurements can help in clarifying the missing scientific knowledge of the lithosphere-atmosphere-ionosphere coupling (LAIC) mechanisms before, during and after large earthquakes. We also solicit contributions on studies about other phenomena, such as tropospheric and anthropogenic electromagnetic emissions, that influence the near-Earth electromagnetic and plasma environment on all relevant topics including data processing, data-assimilation in models, space weather case studies, superimposed epoch analyses, etc.

The nature of science has changed: it has become more interconnected, collaborative, multidisciplinary, and data intensive. Accordingly, the main aim of this session is to create a common space for interdisciplinary scientific discussion, where EGU-GA delegates involved in geoscientific networks can share ideas and present the research activities carried out in their networks. The session represents an invaluable opportunity for different networks and their members to identify possible synergies and establish new collaborations, find novel links between disciplines, and design innovative research approaches.

Part of the session will be focused on COST (European Cooperation in Science and Technology) Actions*. The first edition of the session (successfully held in 2018) was actually entirely dedicated to the COST networking programme and hosted scientific contributions stemming from 25 Actions, covering different areas of the geosciences (sky, earth and subsurface monitoring, terrestrial life and ecosystems, earth's changing climate and natural hazards, sustainable management of resources and urban development, environmental contaminants, and big data management). Inspiring and fruitful discussions took place; the session was very well attended. We are looking forward to continuing the dialogue this year and to receiving new contributions from COST Action Members.

Another part of the session will be dedicated to the activities of other national and international scientific networks, associations, as well teams of scientists who are carrying out collaborative research projects.

Finally, the session is of course open to everyone! Accordingly, abstracts authored by scientists not involved in wide scientific networks are most welcome, too! In fact, in 2018 we received a good number of such abstracts, submitted by individual scientists or small research teams who wished to disseminate the results of their studies in front of the multidisciplinary audience that characterizes this session, as an alternative to making a presentation in a thematic session. This may be a productive way to broaden the perspective and find new partners for future interdisciplinary research ventures. We hope to receive this kind of abstracts this year, as well.


-- Notes --

* COST (www.cost.eu) is a EU-funded programme that enables researchers to set up their interdisciplinary research networks (the “Actions”), in Europe and beyond. COST provides funds for organising conferences, workshops, meetings, training schools, short scientific exchanges and other networking activities in a wide range of scientific topics. Academia, industry, public- and private-sector laboratories work together in Actions, sharing knowledge, leveraging diversity, and pulling resources. Every Action has a main objective, defined goals and clear deliverables. This session was started as a follow up initiative of COST Action TU1208 “Civil engineering applications of Ground Penetrating Radar” (2013-2017, www.GPRadar.eu).

Hydroclimatic conditions and the availability of water resources in space and time constitute important factors for maintaining an adequate food supply, the quality of the environment, and the welfare of inhabitants, in the context of sustainable growth and economic development. This session is designed to explore the impacts of hydroclimatic variability, climate change, and the temporal and spatial availability of water resources on: food production, population health, the quality of the environment, and the welfare of local ecosystems. We particularly welcome submissions on the following topics:

Complex inter-linkages between hydroclimatic conditions, food production, and population health, including: extreme weather events, surface and subsurface water resources, surface temperatures, and their impacts on food security, livelihoods, and water- and food-borne illnesses in urban and rural environments.

Quantitative assessment of surface-water and groundwater resources, and their contribution to agricultural system and ecosystem statuses.

Spatiotemporal modeling of the availability of water resources, flooding, droughts, and climate change, in the context of water quality and usage for food production, agricultural irrigation, and health impacts over a wide range of spatiotemporal scales

Intelligent infrastructure for water usage, irrigation, environmental and ecological health monitoring, such as development of advanced sensors, remote sensing, data collection, and associated modeling approaches.

Modelling tools for organizing integrated solutions for water, precision agriculture, ecosystem health monitoring, and characterization of environmental conditions.

Water re-allocation and treatment for agricultural, environmental, and health related purposes.

Impact assessment of water-related natural disasters, and anthropogenic forcings (e.g. inappropriate agricultural practices, and land usage) on the natural environment; e.g. health impacts from water and air, fragmentation of habitats, etc.

The occurrence of extremes such as droughts, flash floods, hailstorms, storm surges and tropical storms can have significant and sometimes catastrophic consequences to society. However, not all low probability weather/climate events will lead to “high impacts” on human or natural systems or infrastructure. Rather, the severity of such events depend also intrinsically on the exposure, vulnerability and/or resilience to such hazards of affected systems, including emergency management procedures. Similarly, high impact events may be compounded by the interaction of several, e.g., in their own right less severe hydro-meteorological incidents, sometimes separated in time and space. Or they may similarly result from the joint failures of multiple human or natural systems. Consequently, it is a deep transdisciplinary challenge to learn from past high impact events, understand the mechanisms behind them and ultimately to project how they may potentially change in a future climate.

The ECRA (European Climate Research Alliance) Collaborative Programme on “High Impact Events and Climate Change” aims to promote research on the mechanisms behind high impact events and climate extremes, simulation of high impact events under present and future climatic conditions, and on how relevant information for climate risk analysis, vulnerability and adaptation may be co-created with users, e.g., in terms of tailored climate services. For this aim, this Interdisciplinary and Transdisciplinary Session invites contributions that will serve to (i) better understand the mechanisms behind high impact events from a transdisciplinary and interdisciplinary perspective, e.g. case studies and the assessment of past high impact events, including detection and attribution; (ii) project changes to high impact events through, e.g. high resolution climate and impacts modelling (including economic modelling); (iii) produce climate information at the relevant scales (downscaling); and co-create climate services with users to help deal with the risk and/or impacts of high-impact events, e.g. risk analysis and climate adaptation. Abstracts that highlight recent advances from a transdisciplinary perspective for example through the innovation of climate services will be particularly encouraged. Authors and contributors to this session will be offered to present their work in a Special Issue of the journal “Sustainability”.

This session aims to bridge the existing gap between the process-focused fields (hydrology, geomorphology, soil sciences, natural hazards, planetary science, geo-biology, archaeology) and the technical domain (engineering, computer vision, machine learning, and statistics) where terrain analysis approaches are developed.
The rapid growth of survey technologies and computing advances and the increase of data acquisition from various sources (platforms and sensors) has led to a vast data swamp with unprecedented spatio-temporal range, density, and resolution (from submeter to global scale data), which requires efficient data processing to extract suitable information. The challenge is now the interpretation of surface morphology for a better understanding of processes at a variety of scales, from micro, to local, to global.

We aim to foster inter-disciplinarity with a focus on new techniques in digital terrain analysis and production from any discipline which touches on geomorphometry, including but not exclusive to geomorphology (e.g., tectonic/volcanic/climatic/glacial), planetary science, archaeology, geo-biology, natural hazards, computer vision, remote sensing, image processing.
We invite submissions related to the successful application of geomorphometric methods, innovative geomorphometric variables as well as their physical, mathematical and geographical meanings. Submissions related to new techniques in high-resolution terrain or global scale data production and analysis, independent of the subject, as well as studies focused on the associated error and uncertainty analyses, are also welcome. We actively encourage contributors to present work “in development”, as well as established techniques being used in a novel way. We strongly encourage young scientists to contribute and help drive innovation in our community, presenting their work to this session.

We want to foster collaboration and the sharing of ideas across subject-boundaries, between technique developers and users, enabling us as a community to fully exploit the wealth of knowledge inherent in our digital landscape. Just remember, the driver for new ideas and applications often comes from another speciality, discipline or subject: Your solution may already be out there waiting for you!

State estimation theory in geosciences is commonly referred to as data assimilation. This term encompasses the entire sequence of operations that, starting from the observations of a system, and from additional statistical and/or dynamical information (such as an evolution model), provides the best possible estimate of its state. Data assimilation is common practice in numerical weather prediction but its application is becoming widespread in many other areas of climate, atmosphere, ocean and environment modelling; in all those circumstances where one intends to estimate the state of a large dynamical system based on limited information. While the complexity of data assimilation, and of the methods thereof, stands on its interdisciplinary nature across statistics, dynamical systems and numerical optimisation, when applied to geosciences an additional difficulty arises by the, constantly increasing, sophistication of the environmental models.

This overview course is aimed at geoscientists, who are confronted with the model-to-data fusion issue and would benefit from the application of data assimilation techniques, but so far have not delved into their conceptual and methodological complexities.

The course will provide first the formulation of the problem from a Bayesian perspective and will then present the two popular families of Gaussian based approaches, the Kalman-filter/-smoother and the variational methods. Ensemble based methods will then be considered, starting from the well known Ensemble Kalman filter, in its stochastic or deterministic formulation, and then the state-of-the-art ensemble-variational methods.
The course will focus on the specific challenges that data assimilation has encountered to deal with high-dimensional chaotic systems, such as the atmosphere and ocean, and the countermeasures that have been taken and which have driven the dramatic development of the field experienced in the last decades.
It will then conclude by presenting some of the nowadays active lines of development and current challenges, including coupled data assimilation and the particle filters.

Most often observations and measurements of geophysical systems and dynamical phenomena are obtained as time series. Dynamics of the system are inferred from characteristics of these time series which usually manifest a chaotic or stochastic behavior.
In this short course different approaches, based on dynamical systems theory, will be explained, including phase-space portraits, bifurcation theory, correlation dimension and entropic approaches, Langevin and Fokker-Planck equations, fractal analysis, and other concepts of nonlinear time series analysis, like recurrence quantification analysis. Methods will be illustrated in terms of recent successful applications from various fields of geosciences, ranging from climate to solar-terrestrial relations.
The focus will be on a comparison between different methods to investigate different aspects of both known and unknown physical processes.

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.

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, data assimilation can estimate parameters that control processes in the model or fluxes, which can be difficult or impossible to measure. As such, data assimilation can use observations to provide information about non-observable quantities if the model represents those. The combination of modelled 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 ensemble not only provides estimates of uncertainties, but also of cross-correlations between different model variables or parameters. The uncertainty estimate from the ensemble is then used by the assimilation method, and the most widely known is the ensemble Kalman 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 is designed such that it can be used from small toy problems running on notebook computers up to high-dimensional Earth system models running on supercomputers.

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.

The course will first provide an introduction to the ensemble data assimilation methodology. Then, it will explain the implementation concept of PDAF and finally provide a hands-on example of building a data assimilation system based on a 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 data assimilation to their individual problems.

Participants are invited to bring their own notebook computer to run the hands-on examples themselves. For this, a Fortran compiler and the BLAS and LAPACK libraries are required. Matlab or Python would also be handy for plotting. Given the overall limited capacity of the Wifi network during the conference, it is recommended that you download PDAF from http://pdaf.awi.de before the short course if you like to do the hands-on example on your own notebook computer.

Machine learning (ML) is a well-established approach to complex data analysis and modelling in different scientific fields and in many practical applications. Nowadays, ML algorithms are widely used as efficient tools in GI Sciences, remote sensing, environmental monitoring and space-time forecasting. The short course gives an overview of ML algorithms widely applied in data exploration and modelling of high dimensional and multivariate geoscientific data. The main topics of the course, presented within the framework of a generic data-driven methodology of modelling, include detection of patterns and predictability, feature selection, unsupervised, supervised and active learning, visual analytics. Real case studies consider environmental pollution, natural hazards and renewable energy resources assessments.

The tenth short-course in this highly successful sequence of Fourier-focused short-courses will consider two important basic techniques for analysis of geoscience (and other) time-series with regard to periodic features. First, the Fast Fourier Transform (FFT) for equal-interval time-series. Second, the related Lomb-Scargle periodogram for unequal-interval time-series.

The FFT is a key underpinning technique of time-series analysis for the identification of periodic features. The session will overview the key properties of the FFT and the inherent constraints of discrete time-series and sampled data to provide a framework for understanding other, more advanced data-analytical techniques. The Lomb-Scargle periodogram is a least-squares spectral analysis (LSSA) technique and can be considered as a replacement for the FFT for unequal-interval time-series. The session will make the links between the Lomb-Scargle periodogram and the FFT and their common roots in the covariance of a time-series and sinusoids of given frequencies. Both techniques yield estimates of the power spectrum of the data in question and the session will include a consideration of the relationship between the power spectrum and the frequency distribution of the variance as a basis for assessing the statistical effect-size of periodic features in time-series.

R is probably the most important statistical computing language in academia. With more than 10,000 packages it has been extended in many directions, including a huge support for geospatial data (see https://cran.r-project.org/web/views/Spatial.html and Bivand, Pebesma, and Gómez-Rubio 2013). R’s flexibility and statistical capabilities have made it attractive for people working in Earth, planetary and space sciences and a need for geographic data science.

This course will introduce the audience to R’s geographical capabilities, building on the book Geocomputation with R (https://geocompr.robinlovelace.net/) by the workshop authors (Lovelace, Nowosad, and Muenchow 2018). It will cover four topics and provide a solid foundation for attendees to apply R to a range of geographic data:

1. R’s implementation of the two most important spatial data models - vector (Pebesma 2018) and raster (Hijmans 2017).
2. Spatial data visualization with R.
3. Bridges to dedicated GIS software such as QGIS.
4. Statistical learning with geographic data.

Understanding data models is vital for working with geographic data in R. Maps, based on the data, can display complex information in a beautiful way while allowing for first inferences about spatial relationships and patterns. R has already become a Geographic Information System (GIS) (Bivand, Pebesma, and Gómez-Rubio 2013) - a system for the analysis, manipulation and visualization of geographic data (Longley et al. 2015). However, R was not designed as a GIS, and therefore computing large amounts of geographic data in R can be cumbersome. Even more important, R is missing hundreds of geoalgorithms which are readily available in common Desktop GIS. To deal with these shortcomings R packages have been developed allowing R to interface with GIS software. As an example, we will introduce the RQGIS package (Muenchow, Schratz, and Brenning 2017) for this purpose but also comment on other R-GIS bridges such as RSAGA (Brenning, Bangs, and Becker 2018) and rgrass7 (Bivand 2017). We will use RQGIS to compute terrain attributes (catchment area, catchment slope, SAGA wetness index, etc.) which we will subsequently use to model and predict spatially landslide susceptibility with the help of statistical learning techniques such as GLMs, GAMs and random forests (James et al. 2013). Hence, we show by example how to combine the best of two worlds: the geoprocessing power of a GIS and the (geo-)statistical data science power of R. The short course will consist of a mixture of presentations, live code demos and short interactive exercises if time allows.

Learning objectives
By the end of this workshop, the participants should:

- Know how to handle the two spatial data models (vector and raster) in R.
- Import/export different geographic data formats.
- Know the importance of coordinate reference systems.
- Be able to visualize geographic data in a compelling fashion.
- Know about geospatial software interfaces and how they are integrated with R (GEOS, GDAL, QGIS, GRASS, SAGA).
- Know about the specific challenges when modeling geographic data.

Software requirements
1. Latest version of R and RStudio
2. R packages: sf, raster, RQGIS, RSAGA, spData, tmap, tidyverse, mlr
3. QGIS (including SAGA and GRASS), please follow our installation guide (http://jannes-m.github.io/RQGIS/articles/install_guide.html) to make sure that RQGIS can work with QGIS

References
Bivand, Roger. 2017. Rgrass7: Interface Between GRASS 7 Geographical Information System and R. https://CRAN.R-project.org/package=rgrass7.

Bivand, Roger S., Edzer Pebesma, and Virgilio Gómez-Rubio. 2013. Applied Spatial Data Analysis with R. 2nd ed. New York: Springer.

Brenning, Alexander, Donovan Bangs, and Marc Becker. 2018. RSAGA: SAGA Geoprocessing and Terrain Analysis. https://CRAN.R-project.org/package=RSAGA.

Hijmans, Robert J. 2017. Raster: Geographic Data Analysis and Modeling. https://CRAN.R-project.org/package=raster.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani, eds. 2013. An Introduction to Statistical Learning: With Applications in R. Springer Texts in Statistics 103. New York: Springer.

Longley, Paul, Michael Goodchild, David Maguire, and David Rhind. 2015. Geographic Information Science & Systems. Fourth edition. Hoboken, NJ: Wiley.

Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. 2018. Geocomputation with R. The R Series. CRC Press.

Muenchow, Jannes, Patrick Schratz, and Alexander Brenning. 2017. “RQGIS: Integrating R with QGIS for Statistical Geocomputing.” The R Journal 9 (2): 409–28.

Pebesma, Edzer. 2018. “Simple Features for R: Standardized Support for Spatial Vector Data.” The R Journal. https://journal.r-project.org/archive/2018/RJ-2018-009/index.html.

This year marks the 250th anniversary of the birth of Alexander von Humboldt (1769-1859), the intrepid explorer of the Andes and other regions in the world, and the most famous scientist of his time. Alexander von Humboldt is perhaps best known for his radical new vision of nature as a complex and interconnected global force, thereby becoming the founder of the field of biogeography and laying the ground for modern Earth-System Science approaches. It seems fitting to pay tribute to Alexander von Humboldt’s legacy by reviewing the state of the art in studies of the coupled lithosphere – atmosphere – hydrosphere – biosphere system with a focus on the Andean mountain belt. The Andes have become one of the main natural laboratories in the world to explore these questions and many recent studies have addressed its tectonic and geodynamic evolution, but also the two-way couplings between surface uplift, climatic evolution and biodiversity in the Andes and its foreland. This Union Session will bring together world-leading specialists on these questions with the aim to shed light on both suspected and unexpected couplings in the system.

Over the whole Earth history, the climate has encountered tipping points, shifting from one regulated system to the other. This tilting motion affects both climate and the carbon cycle and has played a major role in the evolution of the Earth climate, at all timescales. Earth History has been ponctuated by large climate changes and carbon cycle reorganizations, from large climate variations occurring in deep times (snowball events, terrestrialisation, Mesozoic and early Cenozoic warm episodes, quaternary glacial cycles…) to past and on-going abrupt events. Many potential triggers of those climate and carbon cycle shifts have been proposed and tested through modeling studies, and against field data, such as those directly or indirectly linked with tectonics (plate motion, orogenesis, opening/closing of seaways, weathering…) and orbital forcing. Given that the Earth climate is currently experiencing an unprecedented transition under anthropogenic pressure, understanding the mechanisms behind the scene is crucial.

Our aim is to point out the most recent results concerning how a complex system as the climate of the Earth has undergone many tipping points and what is the specificity of the future climate changes. Therefore, within this session, we would like to encourage talks discussing advances in our record and modeling of the forces triggering and amplifying the changes of Earth climate and carbon cycle across spatial and temporal scales.

In today’s changing world we need to tap the potential of every talented mind to develop solutions for a sustainable future. The existence of under-representation of different groups (cultural, national and gender) remains a reality across the fields of science, technology, engineering, and mathematics (STEM fields) around the world, including the geosciences. This Union Symposium will focus on remaining obstacles that contribute to these imbalances, with the goal of identifying best practices and innovative ideas to overcome obstacles.

EGU is welcoming six high-level speakers from the funding agencies and research centres on both sides of the Atlantic related to geosciences to present efforts and discuss initiatives to tackle both implicit and explicit biases. Speakers are:

Jill Karsten, AGU Diversity and Inclusion Task Force (confirmed)
Erika Marín-Spiotta, University of Wisconsin - Madison (confirmed)
Daniel Conley, Lund University (confirmed)
Giulio di Toro, University of Padua (confirmed)
Liviu Matenco, Utrecht University (confirmed)
Barbara Romanowicz, European Research Council (confirmed)

Atmospheric composition matters to climate, weather forecasting, human health, terrestrial and aquatic ecosystems, agricultural productivity, aeronautical operations, renewable energy production, and more. Hence research in atmospheric composition is becoming increasingly cross-cutting and linked to many disciplines including climate, biogeosciences, hydrology, natural hazards, computer and data sciences, socio-economic studies and many others. There is a growing need for atmospheric composition information and an improved understanding of the processes that drive changes in the composition and resulting impacts. While atmospheric composition research is advancing rapidly, there is a need to pay more attention to the translation of this research to support societal needs. Although translational research is a major focus of the health sciences and meteorology, it is in a relatively early stage in atmospheric composition. In this Union Symposium, we plan to highlight the need for, and to illustrate exciting advances in the translation of atmospheric composition research to support services. We will build upon work within the World Meteorological Organization and other communities related to the closer linkages of weather, atmospheric composition, and climate research and related services. We will also articulate the needs for advances in observing systems, models and a better understanding of fundamental processes. This session will also serve as a celebration of the 30 year anniversary of the WMO Global Atmosphere Watch programme and an opportunity for the broader community to envision partnerships needed to facilitate the effective translation of atmospheric composition research.

In October 2018, the IPCC published its special report on impacts of global warming of 1.5 deg C. Another recent, highly publicised study suggests that the planet could pass an irreversible threshold into a so called “Hothouse Earth” state for a temperature increase of as low as 2 degrees C above pre-industrial temperatures, while other studies and commentaries have emphasised the urgency on climate action, arguing that 2020 must be a turning point for global fossil fuel emissions, to increase the chance of maintaining a safe operating space for the humans on the planet. In 2018, the IPCC celebrated its 30th anniversary. The importance of taking action on human-induced climate change has been emphasised with governments around the world since the 1990s yet CO2 concentrations continue to rise and international initiatives have, to date, had limited and insufficient impact to avert some of the most serious consequences of climate change.
How close are we to one or more critical thresholds (cliff edge)? Is there time to avert passing one or more of these thresholds? What can the geoscience community do to reduce the risks? How important is bottom up versus top down action to ensuring the least worst outcome? These are some of the questions we will debate with world experts in their field and authors of the thought papers on these topics.

The geosciences are currently used by policymakers in a wide variety of areas to help guide the decision-making process and ensure that the best possible outcome is achieved. While the importance of scientific advice and the use of evidence in the policymaking process is generally acknowledged by both policymakers and scientists, how scientific advice is integrated and who is responsible is still unclear.

EU Policymakers frequently highlight institutionalised processes for integrating scientific advice into policy such as European Commission's Group of Chief Scientific Advisors (SAM) and the EU Commission’s Register of Expert Groups. But how efficient and accessible are these mechanisms really?

Some emphasise the need for scientists to have their own policy networks in place so that they can share their research outcomes with policymakers who can then use it directly or pass it on to those responsible for relevant legislation. But from funding applications to teaching and even outreach activities – scientists are often already overloaded with additional tasks on top of their own research. Can they really be held responsible for keeping up with the latest policy news and maintaining a constantly changing network of policymakers as well?

This debate will feature a mixed panel of policymakers and geoscientists who have previously given scientific advice. Some key questions that the panel will debate include:
• How can the accessibility of current EU science-advisory mechanisms be improved?
• Are scientists doing enough to share their research?
• And who is responsible for ensuring that quality scientific evidence is used in policymaking?

Speakers will be encouraged to explain any science advisory mechanism that they highlight (e.g. SAM) to ensure that the debate is understood by all those in attendance.

While the panel and subsequent debate will have an EU focus, it is likely that many of the issues discussed will be applicable to countries around the world.

The ever more challenging work environments and increasing pressures on Early Career Scientists e.g. publish or perish, securing grant proposals, developing transferable skills and many more – and all while having a lack of job security. This puts a big strain on Early Career Scientists and this can lead to neglected mental well-being which in turn increases the risk of developing anxiety, depression or other mental health issues. The graduate survey from 2017 (https://www.nature.com/nature/journal/v550/n7677/full/nj7677-549a.html) shows that 12% of respondents had sought help or advice for anxiety or depression during their PhD.

In this debate we want to discuss: Is there a problem? How ECS can take control of their mental wellbeing and prioritise this in the current research environment? And what support would ECS like to see from organisations like EGU or their employers?

"What counts may not be countable and what is countable may not count". Assessments of scientists and their institutions tend to focus on easy-to-measure metrics related to research outputs such as publications, citations, and grants. However, society is increasingly dependent on Earth science research and data for immediate decisions and long-term planning. There is a growing need for scientists to communicate, engage, and work directly with the public and policy makers, and practice open scholarship, especially regarding data and software. Improving the reward and recognition structure to encourage broader participation of scientists in these activities must involve societies, institutions, and funders. EGU, AGU, and JPGU have all taken steps to improve this recognition, from developing new awards to starting journals around the topic of engaging the public to implementing FAIR data practices in the Earth, environmental, and space sciences, but far more is needed for a broad cultural change. How can we fairly value and credit harder-to-measure, these less tangible contributions, compared to the favoured metrics? And how can we shift the emphasis away from the "audit culture" towards measuring performance and excellence? This session will present a distinguished panel of stakeholders discussing how to implement and institutionalize these changes.

Wed, 10 Apr, 12:45-14:00 / Room E1

Plastic pollution is recognized as one of the most serious and urgent problems facing our planet. Rates of manufacture, use and ultimately disposal of plastics continue to soar, posing an enormous threat to the planet’s oceans and rivers and the flora and fauna they support. There is an urgent need for global action, backed by sound scientific understanding, to tackle this problem.

This Union Symposium will address the problems posed to our planet by plastic pollution, and examine options for dealing with the threat.

The Games Night is a space to gather, socialise, and play some games. The catch is that all the games are based on Geoscience! Bring along your own games or try one of the others in the session and meet the people who created them. This will also be your chance to try games featured in the Games for Geoscience session.

Join us to help put some of the world's most vulnerable places on the map. A mapathon is a mapping marathon, where we get together to contribute to OpenStreetMap - the world's free map.
No experience is necessary - just bring your laptop and we will provide the training. Learn more about crowdsourcing, open data and humanitarian response - we will also provide some tips for how to host a mapathon at your home institution.

Plastic Oceans UK have been experts on plastic pollution for nearly a decade - solving the plastic crisis through their science, sustainability and education programmes. This all began with the award-winning documentary A Plastic Ocean, now available for streaming on Netflix.

Through changing attitudes, behaviours and practices on the use and value of plastics, we can stop plastic pollution reaching the ocean within a generation.

Come along to the screening of A Plastic Ocean to understand the impacts of plastic pollution around the world, what action we can take to stop plastics entering our natural world and pose your questions to the film's producer, Jo Ruxton, at the end of film.

http://plasticoceans.uk/