Division meeting for Nonlinear Processes in Geosciences (NP)
Wed, 06 May, 12:45–13:45 (CEST)
NP1 – Mathematics for Planet Earth
Programme group scientific officer:
Mathematics of Planet Earth
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, pattern formation and emergence, (random and non-autonomous ) dynamical systems, large deviation theory, response theory, tipping points, 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.
Several subsystems of the Earth system have been suggested to react abruptly at critical levels of anthropogenic forcing. Well-known examples of such Tipping Elements include the Atlantic Meridional Overturning Circulation, the polar ice sheets and sea ice, tropical and boreal forests, as well as the Asian monsoon systems. Interactions between the different Tipping Elements may either have stabilizing or destabilizing effects on the other subsystems, potentially leading to cascades of abrupt transitions. The critical forcing levels at which abrupt transitions occur have recently been associated with Tipping Points.
It is paramount to determine the critical forcing levels (and the associated uncertainties) beyond which the systems in question will abruptly change their state, with potentially devastating climatic, ecological, and societal impacts. For this purpose, we need to substantially enhance our understanding of the dynamics of the Tipping Elements and their interactions, on the basis of paleoclimatic evidence, present-day observations, and models spanning the entire hierarchy of complexity. Moreover, to be able to mitigate - or prepare for - potential future transitions, early warning signals have to be identified and monitored in both observations and models.
This interdisciplinary session invites contributions that address Tipping Points in the Earth system from the different perspectives of all relevant disciplines, including
- the mathematical theory of abrupt transitions in (random) dynamical systems,
- paleoclimatic studies of past abrupt transitions,
- data-driven and process-based modelling of past and future transitions,
- early-warning signals
- the implications of abrupt transitions for Climate sensitivity and response,
- ecological and societal impacts, as well as
- decision theory in the presence of uncertain Tipping Point estimates
Hydroinformatics: computational intelligence, systems analysis, optimisation, data science
Hydroinformatics has emerged over the last decades to become a recognised and established field of independent research within the hydrological sciences. Hydroinformatics is concerned with the development and hydrological application of mathematical modelling, information technology, systems science and computational intelligence tools. We also have to face the challenges of Big Data: large data sets, both in size and complexity. Methods and technologies for data handling, visualization and knowledge acquisition are more and more often referred to as Data Science.
The aim of this session is to provide an active forum in which to demonstrate and discuss the integration and appropriate application of emergent computational technologies in a hydrological modelling context. Topics of interest are expected to cover a broad spectrum of theoretical and practical activities that would be of interest to hydro-scientists and water-engineers. The main topics will address the following classes of methods and technologies:
* Predictive and analytical models based on the methods of statistics, computational intelligence, machine learning and data science: neural networks, fuzzy systems, genetic programming, cellular automata, chaos theory, etc.
* Methods for the analysis of complex data sets, including remote sensing data: principal and independent component analysis, time series analysis, information theory, etc.
* Specific concepts and methods of Big Data and Data Science
* Optimisation methods associated with heuristic search procedures: various types of genetic and evolutionary algorithms, randomised and adaptive search, etc.
* Applications of systems analysis and optimisation in water resources
* Hybrid modelling involving different types of models both process-based and data-driven, combination of models (multi-models), etc.
* Data assimilation and model reduction in integrated modelling
* Novel methods of analysing model uncertainty and sensitivity
* Software architectures for linking different types of models and data sources
Applications could belong to any area of hydrology or water resources: rainfall-runoff modelling, flow forecasting, sedimentation modelling, analysis of meteorological and hydrologic data sets, linkages between numerical weather prediction and hydrologic models, model calibration, model uncertainty, optimisation of water resources, etc.
Hydrologic Dynamics, Analytics and Predictability: Physical and Data-based Approaches for Improving Hydrologic Understanding and Prediction
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 stochastic, computational and system dynamic analysis, to more 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, machine learning and analysis with physical understanding in mind.
NP2 – Dynamical Systems and Stochastic Approaches in Geosciences
Programme group scientific officer:
Nonlinear Multiscale and Stochastic Dynamics of the Earth System
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: Anna von der Heydt (Utrecht University)
Extremes in Geophysical Sciences: Dynamics, Thermodynamics and Impacts
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;
· Extremes in dynamical systems;
· Downscaling of weather and climate extremes.
· Linking the dynamics of climate extremes to their impacts
High-impact climate and weather events typically result from the interaction of multiple hazards across various spatial and temporal scales. These events, also known as Compound Events, often cause more severe socio-economic impacts than single-hazard events, rendering traditional univariate extreme event analyses and risk assessment techniques insufficient. It is therefore crucial to develop new methodologies that account for the possible interaction of multiple physical drivers when analysing high-impact events. Such an endeavour requires (i) a deeper understanding of the interplay of mechanisms causing Compound Events and (ii) an evaluation of the performance of climate/weather, statistical and impact models in representing Compound Events.
The European COST Action DAMOCLES coordinates these efforts by building a research network consisting of climate scientists, impact modellers, statisticians, and stakeholders. This session creates a platform for this network and acts as an introduction of the work related to DAMOCLES to the research community.
We invite papers studying all aspects of Compound Events, which might relate to (but are not limited to) the following topics:
Synthesis and Analysis: What are common features for different classes of Compound Events? Which climate variables need to be assessed jointly in order to address related impacts? How much is currently known about the dependence between these variables?
Stakeholders and science-user interface: Which events are most relevant for stakeholders? What are novel approaches to ensure continuous stakeholder engagement?
Impacts: What are the currently available sources of impact data? How can they be used to link observed impacts to climate and weather events?
Statistical approaches, model development and evaluation: What are possible novel statistical models that could be applied in the assessment of Compound Events?
Realistic model simulations of events: What are the physical mechanisms behind different types of Compound Events? What type of interactions result in the joint impact of the hazards that are involved in the event? How do these interactions influence risk assessment analyses?
ENSO and Tropical Basins Interactions: Dynamics, Predictability and Modelling
ENSO and its interactions with other tropical basins are the dominant source of interannual climate variability in the tropics and across the globe. Understanding the dynamics, predictability, and impacts of ENSO and tropical basins interactions, and anticipating their future changes are thus of vital importance for society. This session invites contributions regarding all aspects of ENSO and tropical basins interactions, including: dynamics, multi-scale interactions; low frequency, decadal and paleo variability; theoretical approaches; ENSO diversity; global teleconnections; impacts on climate, society and ecosystems; seasonal forecasting and climate change projections of ENSO and its tropical basins interactions. Studies aimed at understanding ENSO and its tropical basins interactions in models of a range of complexity are especially welcomed, including analysis of CMIP model intercomparisons.
welcome to the virtual EGU 2020. This is just a reminder that we will have the "ENSO and Tropical Basins Interactions: Dynamics, Predictability and Modelling" (CL4.20/AS1.12/NP2.6/OS1.27) session Thu, 07 May, 14:00–15:45 (Vienna time zone). It will be an online chat only session.
In addition to the EGU chat session on Thursday we plan to do a video meeting for the "ENSO and Tropical Basins Interactions: Dynamics, Predictability and Modelling" session with presentations from the authors (you) some time later this year (e.g. June/July). More on this we will discuss on Thursday in the EGU chat of this session.
Best regards and hope to chat with you on Thursday!
Dietmar Dommenget, Antonietta Capotondi, Daniela Domeisen and Eric Guilyardi
Programme group scientific officer:
François G. Schmitt
Urban Geoscience Complexity: Transdisciplinarity for the Urban Transition
Last year sessions ITS6.1-3 on urban geosciences have largely confirmed the urgency to develop inter-/trans-disciplinary approaches of urban geosciences to respond to the huge societal demand to radically improve urban systems and their interactions with their environment and climate. The session ITS.6.1 focussed on the need to develop holistic approaches going beyond specialised domains such as urban meteorology, hydrology, climatology, ecology and resilience to grasp the urban-geophysical systems in their multi-component and multiscale complexity. This in particular indispensable to resolve long lasting questions like multi-hazard threats and upscaling of climate solutions. The recent IPCC report 1.5°C confirms the necessity to fully take into account the multi-component complexity of the urban-geophysical systems to achieve the urban and infrastructure transition, one of the main four system transitions to be achieved
The present session calls therefore for contributions on the development transdisciplinary concepts, methodologies and tools, as well as their applications to urban-geophysical systems in view of this transition. Jean Jouzel (former IPCC vice-president) will open this session.
ITS2.10 invites you to actively participate (audio and/or pdf slide sharing) to the Great Debate: "Epidemics, Urban Systems and Geosciences"
Monday 4 May, 12:30-14:00 ECT
e-room COVID-19 https://vmi270945.contaboserver.net/b/pau-guy-rwr
(no app to upload, just click on this link).
This debate is focused on a major upset of the geosciences agenda, particularly those dealing with urban systems so that they contribute more to well-being and health. This great debate will be an opportunity to take stock and open up perspectives, particularly on epidemics and mobility, the dynamics of Covid-19, cities, health and geosciences
Do not miss the opportunity to e-debate with:
Theo Geisel (Max Planck Institute, Göttingen)
Jacques Demongeot (Université Grenoble Alpes)
Mark J. Nieuwenhuijsen (Institute for Global Health, Barcelona)
This debate is a follow-up of ITS2.10 and is organised with the UNESCO UniTwin CS-DC (Complex Systems Digital Campus).
Precipitation Modelling: uncertainty, variability, assimilation, ensemble simulation and downscaling
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.
Precipitation small scale variability, hydrometeorologic extremes, and land-use feedbacks in the atmospheric water cycle, and beyond
This PICO session addresses three sub-topics :
Precipitation variability: from drop scale to lot scale:
The understanding of small scale (sec – drop scale to min -km) spatio-temporal variability of precipitation is essential for larger scale studies, 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 point measurement devices (rain gauges and disdrometers) and weather radars, which is greater than 10^7! This session aims at bridging this scale gap and improving the understanding of small scale precipitation variability, both liquid and solid, as well as its hydro-meteorological consequences at larger scales.
Hydroclimatic and hydrometeorologic stochastics: Extremes, scales, probabilities:
The departure of statistical properties of hydrometeorological processes from the classical statistical prototype has been established. This session aims at presenting the latest developments on:
- Coupling stochastic approaches with deterministic hydrometeorological predictions;
- Stochastic-dynamic approaches;
- Variability at climatic scales and its interplay with the ergodicity of space-time probabilities;
- Linking underlying physics and scaling stochastics of hydrometeorological extremes;
- Development of parsimonious representations of probability distributions of hydrometeorological extremes over a wide range of scales and states; as well as their applications in risk analysis and hazard predictions
The session is co-sponsored by the ICSH-IAHS, former STAHY.
The atmospheric water cycle under change: feedbacks, land use, hydrological changes and implications :
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. Anthropogenic pressure through land-use changes (and greenhouse gasses) alter, not only, the local hydrology, but through atmospheric water and energy feedbacks also effect the water cycle in remote locations. This session aims to:
- investigate the remote and local atmospheric feedbacks from human interventions, based on observations and coupled modelling approaches.
- explore the implications of atmospheric feedbacks on the hydrologic cycle for land and water management (ex. changing land cover)
New frontiers of multiscale monitoring, analysis, modeling and decisional support (DSS) of environmental systems
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 and inter-disciplinary 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, energy exploitation, slope instability, floods, coastal instability, climate changes and other environmental context.
We expect contributions derived from several disciplines, such as applied geophysics, geology, seismology, geodesy, geochemistry, remote and proximal sensing, volcanology, geotechnical, soil science, marine geology, oceanography, climatology and meteorology. In this context, the contributions in analytical and numerical modeling of geological and environmental processes are also expected.
Finally, we stress that the inter-disciplinary studies that highlight the multiscale properties of natural processes analyzed and monitored by using several methodologies are welcome.
Scaling soil processes across space and time: leveraging models and data syntheses
Soil organic matter (SOM) is an ecosystem property that emerges from a suite of complex biological, geochemical, and physical interactions across scales. As the largest pool of actively-cycling terrestrial carbon, understanding how SOM persistence and vulnerability will respond to global change is critical. However, Earth System Models (ESMs) are often unable to capture emergent SOM patterns and feedbacks at across smaller spatial and temporal scales. Identifying, prioritizing, and scaling key driving mechanisms from detailed process models to advance ESMs is crucial, and better empirical constraints on SOM pools and fluxes are urgently needed to advance understanding and provide model benchmarks. Interdisciplinary research and observation networks collecting long-term, geographically-distributed data can help elucidate key mechanisms, and international efforts that synthesize and harmonize these data are needed to inform data-model comparisons.
We invite theoretical and empirical contributions that investigate controls on SOM across scales, from detailed process understanding to emergent landscape-scale dynamics in natural and managed ecosystems. We seek modelling studies that work across scales, data analyses that leverage multi-site networks and/or long-term experiments, or collaborations between empiricists and modelers within and across networks. Studies that use novel tools across scales, from microbial -omics to remote sensing, are also welcome.
This session has been promoted by:
• Sustainable Agro-ecosystems (AGRISOST, https://www.agrisost.org/en/)
• International Soil Modeling Consortium (ISMC, https://soil-modeling.org/)
Precipitation measurement: techniques, processes and hydrological applications at the catchment scale
The hydrological response to precipitation at the catchment scale is the result of the interplay between the space-time variability of precipitation, the catchment geomorphological / pedological / ecological characteristics and antecedent hydrological conditions. Therefore, (1) accurate measurement and prediction of the spatial and temporal distribution of precipitation over a catchment and (2) the efficient and appropriate description of the catchment properties are important issues in hydrology. This session focuses on the following aspects of the space-time variability of precipitation:
- Novel techniques for measuring liquid and solid precipitation at hydrologically relevant space and time scales, from in situ measurements to remote sensing techniques, and from ground-based devices to spaceborne platforms.
- Novel approaches to better identify, understand and simulate the dominant microphysical processes at work in liquid and solid precipitation.
- Applications of measured and/or modelled precipitation fields in catchment hydrological models for the purpose of process understanding or predicting hydrological response.
Future insights from a constantly varying past, and climate variability across scales.
State of the art climate models are now run for past, present and future climates. This has opened up the opportunity for paleoclimate modelling and data together to inform on future climate changes. To date, most research in this area has been on constraining basic metrics such a climate sensitivity. In addition, and just as importantly for mankind, the Earth's climate is highly variable on all spatial and temporal scales with implications for understanding both the industrial epoch
and future climate projections. These changes in variability (spatial or temporal) can impact the recurrence frequency of extreme events which can have catastrophic effects on society. Yet, it is unclear if a warmer future is one with more or less climate variability, and at which scales. A multitude of feedbacks are involved.
We welcome contributions that improve quantification, understanding and prediction of past, present and future climate and its variability in the Earth System across space and time scales. This includes contributions looking at "steady state" climate features such as climate sensitivity as well as those investigating changes in climate variability and scaling properties. The session is multidisciplinary and brings together studies related to atmospheric science, oceanography, glaciology, paleoclimatology and nonlinear geoscience, to examine the complementarity of ideas and approaches. We particularly encourage submissions that combine models run for the past, present and future with data syntheses to constrain the spread of future predictions, submissions which combine models and data in the past to make strong conclusions or testable hypotheses about the future, as well as work highlighting future experiments and data required to strengthen the link to the future. We welcome contributions using case studies, idealised or realistic modelling, 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. Members of the PAGES working group on Climate Variability Across Scales (CVAS) are welcome.
Complex geoscientific time series: linear, nonlinear, and computer science perspectives
This interdisciplinary session welcomes contributions on novel conceptual approaches and methods for the analysis of observational as well as model time series from all geoscientific disciplines.
Methods to be discussed include, but are not limited to:
- linear and nonlinear methods of time series analysis
- time-frequency methods
- 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
- artificial intelligence and machine learning based analysis and prediction for univariate and multivariate time series
Contributions on methodological developments and applications to problems across all geoscientific disciplines are equally encouraged.
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, deep learning and Artificial Intelligence applications in geosciences
• Visualization and visual analytics of big and high-dimensional data
• Informatics and data science
• Emerging big data paradigms, such as datacubes
|AttendanceThu, 07 May, 08:30–12:30 (CEST),
AttendanceThu, 07 May, 14:00–15:45 (CEST)
Deep Learning in Hydrological Science
Machine learning (ML) is now widely used across the Earth Sciences and especially its subfield deep learning (DL) has recently enjoyed increased attention in the context of Hydrology. The goal of this session is to highlight the continued integration of ML, and DL in particular, into traditional and emerging Hydrology-related workflows. Abstracts are solicited related to novel theory development, novel methodology, or practical applications of ML and DL in Hydrology. This might include, but is not limited to, the following:
(1) Identifying novel ways for DL in hydrological modelling.
(2) Testing and examining the usability of DL based approaches in hydrology.
(3) Improving understanding of the (internal) states/representations of DL models.
(4) Integrating DL with traditional hydrological models.
(5) Creating an improved understanding of the conditions for which DL provides reliable simulations. Including quantifying uncertainty in DL models.
(6) Clustering and/or classifying hydrologic systems, events and regimes.
(7) Using DL for detecting, quantifying or cope with nonstationarity in hydrological systems and modeling.
(8) Deriving scaling relationships or process-related insights directly from DL.
(8) Using DL to model or anticipate human behavior or human impacts on hydrological systems.
(10) DL based hazard analysis, detection/mitigation, event detection, etc.
(11) Natural Language Processing to analyze, interpret, or condense hydrologically-relevant peer-reviewed literature or social media data or to assess trends within the discipline.
Data Science and Machine Learning for Natural Hazards and Seismology
Smart monitoring and observation systems for natural hazards, including satellites, seismometers, global networks, unmanned vehicles (e.g., UAV), and other linked devices, have become increasingly abundant. With these data, we observe the restless nature of our Earth and work towards improving our understanding of natural hazard processes such as landslides, debris flows, earthquakes, floods, storms, and tsunamis. The abundance of diverse measurements that we have now accumulated presents an opportunity for earth scientists to employ statistically driven approaches that speed up data processing, improve model forecasts, and give insights into the underlying physical processes. Such big-data approaches are supported by the wider scientific, computational, and statistical research communities who are constantly developing data science and machine learning techniques and software. Hence, data science and machine learning methods are rapidly impacting the fields of natural hazards and seismology. In this session, we will see research from natural hazards and seismology for processes over a broad range of time and spatial scales.
Dr. Pui Anantrasirichai of the University of Bristol, UK will give the invited presentation:
Application of Deep Learning to Detect Ground Deformation in InSAR Data
There are many ways in which machine learning promises to provide insight into the Earth System, and this area of research is developing at a breathtaking pace. If unsupervised, supervised as well as reinforcement learning can hold this promise remains an open question, particularly for predictions. Machine learning could help extract information from numerous Earth System data, such as satellite observations, as well as improve model fidelity through novel parameterisations or speed-ups. This session invites submissions spanning modelling and observational approaches towards providing an overview of the state-of-the-art of the application of these novel methods.
Spatio-temporal data science: theoretical advances and applications in computational geosciences
Most of the processes studied by geoscientists are characterized by variations in both space and time. These spatio-temporal phenomena have been traditionally investigated using linear statistical approaches, as in the case of physically-based models and geostatistical models. Additionally, the rising attention toward machine learning, as well as the rapid growth of computational resources, opens new horizons in understanding, modelling and forecasting complex spatio-temporal systems through the use of stochastics non-linear models.
This session aims at exploring the new challenges and opportunities opened by the spread of data-driven statistical learning approaches in Earth and Soil Sciences. We invite cutting-edge contributions related to methods of spatio-temporal geostatistics or data mining on topics that include, but are not limited to:
- advances in spatio-temporal modeling using geostatistics and machine learning;
- uncertainty quantification and representation;
- innovative techniques of knowledge extraction based on clustering, pattern recognition and, more generally, data mining.
The main applications will be closely related to the research in environmental sciences and quantitative geography. A non-complete list of possible applications includes:
- natural and anthropogenic hazards (e.g. floods; landslides; earthquakes; wildfires; soil, water, and air pollution);
- interaction between geosphere and anthroposphere (e.g. land degradation; urban sprawl);
- socio-economic sciences, characterized by the spatial and temporal dimension of the data (e.g. census data; transport; commuter traffic).
Programme group scientific officer:
Data Assimilation, Predictability, Error Identification and Uncertainty Quantification in Geosciences
Inverse Problems are encountered in many fields of geosciences. One class of inverse problems, in the context of predictability, is assimilation of observations in dynamical models of the system under study. Furthermore, objective quantification of the uncertainty on the results obtained is the object of growing concern and interest.
This session will be devoted to the presentation and discussion of methods for inverse problems, data assimilation and associated uncertainty quantification, in ocean and atmosphere dynamics, atmospheric chemistry, hydrology, climate science, solid earth geophysics and, more generally, in all fields of geosciences.
We encourage presentations on advanced methods, and related mathematical developments, suitable for situations in which local linear and Gaussian hypotheses are not valid and/or for situations in which significant model
errors are present. We also welcome contributions dealing with algorithmic aspects and numerical implementation of the solution of inverse problems and quantification of the associated uncertainty, as well as novel methodologies at the crossroad between data assimilation and purely data-driven, machine-learning-type algorithms.
Luca Cantarello (University of Leeds)
Jean-Michel Brankart (University of Grenoble)
In the session we will encourage all participants to present their work. These brief presentations will last about 5 minutes.
New approaches to predictions and predictability estimation for geophysical fluid
Accurate predictions of geophysical fluid have enormous social and economic values but remain to have significant uncertainties at different time and spatial scales. Although some dynamical, statistical, and their combined (“scholastic”) approaches were often used to make predictions and showed their respective usefulness, there exist great limitations in improving prediction level. This session will bring together experts to jointly address new approaches to predictions of geophysical fluid and to identification and quantification of uncertainties associated with predictability, and create an exchange of ideas likely to advance the state of predictions. Papers are invited on all aspects of conventional dynamical and statistical approaches to predictions and predictability estimation, and underlying that justification of the appropriateness of the use of any of them in a particular situation is particularly welcome. Papers on techniques that combine the dynamical and statistical approaches with newly emerging techniques of machine learning are also welcome.
Our session is scheduled for a live, text-based chat on Wed, 06 May, 08:30–10:15, a total of 105 minutes. The conveners encourage all of the authors upload the presentation materials and enjoy the discussion time of the session.
The way to proceed the session discussion is as follows.
(1) Each presenting author to present their work for about 1-2 minutes, with an introduction to contents, methods and results, then the participants will have a general idea of what it is about. After it, I'll open the floor for questions or comments.
(2) For the invited talk, it will have 8 minutes for discussion. And each of other talks will have about 3-4 minutes for discussion.
(3) We'll go through the presentations as listed in the right panel of the chat room.
(4) If there are authors to be absent and time to spare is left, we will have free discussion time interval and the participants can have questions or comments to the presentation of your interests during this time interval.
Advances in statistical post-processing, blending and verification of deterministic and ensemble forecasts
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 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.
At the same time, a lot of efforts are put in combining multiple forecasting sources in order to get reliable and seamless forecasts on time ranges from minutes to weeks. Such blending techniques are currently developed in many meteorological centers.
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, papers dealing with the problem of combining or blending different types of forecasts in order to improve reliability from very short to long time scales.
Chaotic variability and modelling uncertainties in the ocean: towards probabilistic oceanography.
Theoretical and model studies show that the ocean is a chaotic system interacting with the atmosphere: uncertainties in ocean model initial states may grow and strongly affect the simulated variability up to multidecadal and basin scales, with or without coupling to the atmosphere. In addition, ocean simulations require both the use of subgrid-scale parameterizations that mimick crudely unresolved processes, and the calibration of the parameters associated with these parameterizations, while respecting numerical stability constraints. Oceanographers are increasingly adopting ensemble simulation strategies and probabilistic analysis methods, and developing stochastic parameterizations for modeling and understanding the ocean variability in this context of multiple uncertainties.
Presentations are solicited about the conception and analysis of ocean ensemble simulations, the characterization of ocean model uncertainties, and the development of stochastic parameterizations for ocean models. The session will also cover the dynamics and structure of the ocean chaotic variability, its relationship with the atmospheric variability, and the use of dynamical system or information theories for the investigation of the oceanic variability. We welcome as well studies about the propagation of the ocean chaotic variability towards other components of the climate system, about its consequences regarding ocean predictability, operational forecasts, detection and attribution of climate signals, climate simulations and projections.
OS1.5 : CHAOTIC VARIABILITY AND MODELLING UNCERTAINTIES IN THE OCEAN: TOWARDS PROBABILISTIC OCEANOGRAPHY
WEDNESDAY : 16:15 - 18:00 : TENTATIVE SCHEDULE FOR THE CHAT (Public on EGU website)
12 minutes for hightlighted talk (Sinha et al)
7 minutes for all other talks
16:20 - 17:00 FORCED AND CHAOTIC OCEAN VARIABILITY
01. D2581 | EGU2020-7226 | HIGHLIGHT —> 12 min
Quantifying uncertainty in decadal ocean heat uptake due to intrinsic ocean variability.
Bablu Sinha, Alex Megann, Thierry Penduff, Jean-Marc Molines, and Sybren Drijfhout
02. D2582 | EGU2020-5689 —> 7 min
Forced and chaotic variability of interannual variability of regional sea level and its causes scale over 1993-2015.
Alice Carret, William Llovel, Thierry Penduff, Jean-Marc Molines, and Benoît Meyssignac
03. D2592 | EGU2020-2737 —> 7 min
Forced and chaotic variability of basin-scale heat budgets in the global ocean: focus on the South Atlantic crossroads.
Thierry Penduff, Fei-Er Yan, Imane Benabicha, Jean-Marc Molines, and Bernard Barnier
04. D2583 | EGU2020-19875 —> 7 min
Year-to-year meridional shifts of the Great Whirl driven by oceanic internal instabilities
Kwatra Sadhvi, Iyyappan Suresh, Izumo Takeshi, Jerome Vialard, Matthieu Lengaigne, Thierry Penduff, and Jean Marc Molines.
05. D2584 | EGU2020-20309 —> 7 min
Deconstructing the subtropical AMOC variability.
Quentin Jamet, William Dewar, Nicolas Wienders, Bruno Deremble, Sally Close, and Thierry Penduff
17:00 - 17:25 OCEAN PROCESSES AND PARAMETERIZATIONS
06. D2586 | EGU2020-21330 —> 7 min
Eddy-Mean flow oscillations in the Southern Ocean.
Sebastiano Roncoroni and David Ferreira
07. D2585 | EGU2020-22418 —> 7 min
On wind-driven energetics of subtropical gyres.
William K. Dewar, Quentin Jamet, Bruno Deremble, and Nicolas Wienders
08. D2587 | EGU2020-11312 —> 7 min
Stochastic Advection for eddy parameterisation in Primitive Equation Models.
09. D2589 | EGU2020-11127 —> 7 min
Ensemble quantification of short-term predictability of the ocean fine-scale dynamics: a western mediterranean test case at kilometric-scale resolution.
Stéphanie Leroux, Jean-Michel Brankart, Aurélie Albert, Pierre Brasseur, Laurent Brodeau, Julien Le Sommer, Jean-Marc Molines, and Thierry Penduff
10. D2590 | EGU2020-6489 —> 7 min
Predictability of estuarine model using Information Theory: ROMS Ocean State Ocean Model
Aakash Sane, Baylor Fox-Kemper, David Ullman, Christopher Kincaid, and Lewis Rothstein
11. D2591 | EGU2020-6000 —> 7 min
Impact of Atmospheric and Model Physics Perturbations On a High-Resolution Ensemble Data Assimilation System of the Red Sea
Siva Reddy Sanikommu, Habib Toye, Peng Zhan, Sabique Langodan, George Krokos, Omar Knio, and Ibrahim Hoteit
17:50 - 18:00 OPEN DISCUSSION - CLOSING THE SESSION
Challenges in climate prediction: multiple time-scales and the Earth system dimensions
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).
An increasingly important aspect for climate forecast's applications is the use of most appropriate downscaling methods, based on dynamical or statistical approaches or their combination, that are needed to generate time series and fields with an appropriate spatial or temporal resolution. This is extensively considered in the session, which therefore brings together scientists from all geoscientific disciplines working on the prediction and application problems.
Earth System Models and coupled atmosphere-hydrological simulations: model development, applications and coupled data assimilation
Earth Systems Models aim at describing the full water- and energy cycles, i.e. from the deep ocean or groundwater across the sea or land surface to the top of the atmosphere. The objective of the session is to create a valuable opportunity for interdisciplinary exchange of ideas and experiences among members of the Earth System modeling community and especially atmospheric-hydrological modelers.
Contributions are invited dealing with approaches how to capture the complex fluxes and interactions between surface water, groundwater, land surface processes, oceans and regional climate. This includes the development and application of one-way or fully-coupled hydrometeorological prediction systems for e.g. floods, droughts and water resources at various scales. We are interested in model systems that make use of innovative upscaling and downscaling schemes for predictions across various spatial- and temporal scales. Contributions on novel one-way and fully-coupled modeling systems and combined dynamical-statistical approaches are encouraged. A particular focus of the session is on weakly and strongly coupled data assimilation across the different compartments of the Earth system for the improved prediction of states and fluxes of water and energy. Merging of different observation types and observations at different length scales is addressed as well as different data assimilation approaches for the atmosphere-land system, the land surface-subsurface system and the atmosphere-ocean system. The value of different measurement types for the predictions of states and fluxes, and the additional value of measurements to update states across compartments is of high interest to the session. We also encourage contributions on use of field experiments and testbeds equipped with complex sensors and measurement systems allowing compartment-crossing and multi-variable validation of Earth System Models.
Programme group scientific officer:
Lagrangian methods for atmosphere and ocean science
Lagrangian trajectories are currently used for vast range of purposes in ocean and atmosphere science. Examples include studying the connectivity of ocean basins, forecasting the spreading of ash clouds, mapping global ocean diffusivities, observing the deep ocean, or tracing plastics and other forms of pollutants in the ocean, etc. There is thus a need for numerical models capable of simulating Lagrangian particles in the ocean and atmosphere as well as accurate methods for analysing the data from surface drifters, floats, and simulated particles.
This session aims at bringing together scientists working on all sorts of Lagrangian methods, e.g. observed or simulated particles in the atmosphere and ocean, and a variety of use cases e.g. studying oceanic mixing/diffusivity, tracing pollution in the atmosphere or ocean, iceberg tracking etc. We welcome presentations on e.g.:
- Connectivity and pathways of air- or water-masses in the atmosphere and ocean
- Development of Lagrangian particle-tracking algorithms and algorithms to model particles with active behaviours, e.g. icebergs, fish, ash clouds, plastics etc.
- Methods and new tools to analyse observed or simulated Lagrangian particles, e.g. diffusivity, spreading rates, etc.
- New instrumentations and developments of balloons, surface drifters and floats.
Turbulence, magnetic reconnection, shocks and particle acceleration: nonlinear processes in space, laboratory and astrophysical plasmas
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. This year we encourage especially papers proposing new methods, especially those rooted in Artificial Intelligence (AI) and Machine Learning (ML), to extract new knowledge from big observational and simulated data sets.
please check EGU chat for new zoom link and password
Recent development in GFD and remote sensing. Nonlinear and turbulent processes under high wind conditions
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-turbulence interactions, 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.
Geophysical Fluid Dynamics (GFD) is a truly interdisciplinary field, including different topics dealing with rotating stratified fluids. It emerges in the late 50s, when scientists from meteorology, oceanography, astrophysics, geological fluid dynamics, and applied mathematics began to mathematically model complex flows and thereby unify these fields. Since then many new aspects were added and deeper insight into many problems has been achieved. New mathematical and statistical tools were developed, standard techniques were refined, classical problems were varied. In this session we primarily focus on contributions from dynamic meteorology and physical oceanography that model flows by mathematical analysis. However, it is also a forum for experimental GFD and for astrophysical and geological aspects of GFD as well.
|AttendanceFri, 08 May, 10:45–12:30 (CEST),
AttendanceFri, 08 May, 14:00–15:45 (CEST)
NP7 – Nonlinear Waves
Programme group scientific officer:
Nonlinear Waves and Fracturing
Waves in the Earth’s crust are often generated by fractures in the process of their sliding or propagation. Conversely, the waves can trigger fracture sliding or even propagation. The presence of multiple fractures makes geomaterials non-linear. Therefore the analysis of wave propagation and interaction with pre-existing or emerging fractures 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
• The existence of rotational mechanisms of wave and fracture propagation
• 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
• Apparent negative stiffness associated with either rotation of non-spherical constituents or fracture propagation and its effect on wave propagation
• Active nature of geomaterials (such as seismic emission induced by stress and pressure wave propagation)
• Non-linear diffusion waves, shock waves and hydraulic fracturing
• Synchronization of earhtquakes and volcanic activity
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.
Please join the chat at 8:30 Vienna's time and introduce yourselves. The current version of the program is uploaded. It consists of 7 groups. The order of discussion of the talks is according to the program rather than appearance of the talks in the list of abstracts.
All submitted presentation are downloadable, please browse through them before the session. It is a good idea to write the questions in advance to safe time in this rather short session.
We would like to thank all participants for interesting presentations and stimulating questions. The format of the session presented a new and challenging experience, but there are few positive moments that can be pointed out. Firstly, it was democratic – no division between posters and orals. Secondly, we are given time and opportunity to look at the presentations in advance and formulate the questions. Finally, we were able to “talk” and ask questions at the same time without waiting for the one’s turn. This may look not to be easy for the presenter, but even then the presenter has the freedom to choose the question to answer and the order of answering. Yet, let us hope that we will meet in person next year.
Modelling the interaction of water waves with varying current is an important issue, especially in nearshore and coastal areas and for a variety of engineering applications.
These applications include wave structure interactions, with the problematics related to oil and naval industries, but also renewable energies.
The problematic is also important when considering coastal management, and harbour maintenance and exploitation.
Also, this interaction often leads to the formation of extreme wave events with detrimental effects.
Significant scientific effort was undertaken during the last fifty years to model linear, weakly or strongly nonlinear water waves with constant, or slowly varying currents.
When variations are stronger, the difficulty remains important.
In this session, contributions are invited relating experimental, numerical and theoretical works designed to improve the understanding of water waves and current interactions, including wave and current stability, wave dynamics, and energy propagation.
Contributions describing the specific problematics, from the point of the applications, are also deeply welcome.
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. Besides, this year we welcome abstracts reporting results on the SouthTRAC campaign in the Southern Hemisphere, as well as any other major collaborative projects such as MS-GWaves.
Extreme events in sea waves: physical mechanisms and mathematical models
The scope of this session includes different aspects of large-amplitude wave phenomena in the ocean such as freak or rogue waves, surface and internal waves, as well as waves trapped by currents and bathymetry. The session is focused on the understanding of the physical mechanisms which cause extreme events, and the derivation of appropriate mathematical models for their description and advanced methods for their analysis. An essential part of such studies is the validation of new models and techniques versus laboratory and in-situ data. Special attention is paid to the description of wave breaking processes, and the interaction of large-amplitude waves with coastal structures.
Extreme Internal Wave Events: Generation, Transformation, Breaking and Interaction with the Bottom Topography
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.
Programme group scientific officer:
Henk A. Dijkstra
Climate Extremes, Tipping Dynamics, and Earth Resilience in the Anthropocene
Climate change is projected to result in an increase in extreme and compound weather events, which pose a growing threat to human well-being and the achievement of the UN Sustainable Development Goals (SDGs). Further warming is also projected to reduce the efficacy of carbon sinks acting as negative feedbacks on warming and increase the risk of crossing tipping points and triggering cascading changes in the climate and ecosystems. These processes may reduce the Earth system’s resilience, which has the potential to further amplify climate change and extremes and worsen societal impacts.
Maintaining Earth in the Holocene-like conditions that have enabled the development of the world’s societies will require better understanding of feedbacks and tipping dynamics in both the human world and the biophysical Earth. Societies will need to embark on rapid socio-economic and governance transformations in order to both reduce the risk of triggering tipping points and to improve societal resilience to increasingly likely extreme events. Earth resilience brings the complex dynamics and perturbations associated with human activities into Earth system analysis, and increasingly captures socio-economic as well as biophysical dynamics.
In this session we welcome transdisciplinary and cross-scale contributions relating to climate extremes, tipping dynamics, and Earth resilience, covering topics ranging from the cascading impacts of extreme and compound events, key feedbacks and tipping points in both biophysical and human systems, enhancing societal resilience to extreme events, and the potential for rapid social transformations to global sustainability.
EGU 2020 Session TS3.2/NH10.7
Climate Extremes, Tipping Dynamics, and Earth Resilience in the Anthropocene
6 May, 14:00-18:00
This session will run as an EGU website hosted text-based chat accessible here, as well as through a simultaneous Zoom video room (link to be provided during the livechat).
Both the EGU chatroom and the Zoom video room will be moderated.
Comments on the presentations can be made at the EGU website at any time, for asynchronous responses.
Comments and questions asked in the EGU chatroom will be forwarded to the Zoom presenters. This means all questions will get responses, but this may not happen within the timeslot of the presentation.
To facilitate real-time dialogue with the presenters, please go to the Zoom session.
When joining the Zoom session remember to mute yourself, and to ask questions please raise your hand (available from the 'participants' button) and unmute when the chair calls on you. If you are a presenter, unmute when called on and share your screen if you have a few slides to show. Each presenter gets 10 minutes max including Q&A, so we suggest presenting some summary slides for a few minutes and then taking questions for the rest.
COST Actions in geosciences: breakthrough ideas, research activities and results
The nature of science has changed: it has become more interconnected, collaborative, multidisciplinary, and data intensive. The main aim of this session, now in its third edition, is to create a common space for interdisciplinary scientific discussion where EGU-GA delegates involved in recent and ongoing COST (European Cooperation in Science and Technology)* Actions can share ideas and present the research activities carried out in their networks. The session represents an invaluable opportunity for different Actions and their members to identify possible synergies and establish new collaborations, find novel links between disciplines, and design innovative research approaches. So far, this session has hosted contributions stemming from 26 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); we are looking forward to receiving new contributions this year.
Same as in past editions, part of this session will be dedicated to presenting and discussing activities carried out in further national and international scientific networks, associations, and collaborative projects.
Moreover, this session is of course open to everyone and abstracts authored by individual scientists or small research teams are most welcome, too. Actually, in 2018 and 2019 we received a very good number of such abstracts, submitted by researchers who wanted 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. In fact, contributing to this session can be a productive way to broaden the perspective and find new partners for future interdisciplinary research ventures.
-- Notes --
* COST (www.cost.eu) is funded by the EU and enables researchers to set up their interdisciplinary and international scientific networks (the “Actions”). Academia, industry, public- and private-sector laboratories work together in the Actions, sharing knowledge, leveraging diversity, and pulling resources. Every Action has a main objective, defined goals and deliverables. This session is a follow-up initiative of COST Action TU1208 “Civil engineering applications of Ground Penetrating Radar” (www.gpradar.eu).
Deep Learning for Geosciences with MATLAB made easy
This short course will focus on modern, data driven analytical methods in the field of Deep Learning with MATLAB. Deep Learning represents powerful artificial intelligence tools used to solve complex modeling problems in earth and ocean sciences, planetary and atmospheric sciences, and related math and geoscience fields. The MATLAB based Deep Learning platform provides algorithms and tools for creating and training deep neural networks. These networks are used to simulate processes of past, present and future environmental events in this wide range of disciplines.
Participants will be able to adopt concepts of Deep Learning for their areas of research such as dynamics, preconditions, and trends related to the surface, subsurface and the atmosphere of the planets. The content level will be 80% beginner, 10% intermediate, and 10% advanced. Scientists from all disciplines are invited to participate in this course. Any previous experience with Deep Learning and distributed computing will be beneficial but not necessary for participation.
The maximum number of participants is 65, in order to guarantee direct supervision for the hands-on part of the session.
The seminar will take place on Wed, 13 May, 10:30-12:00 CEST. Register at: