In his seminal work "Weather Prediction by Numerical Process" in 1922, Lewis Fry Richardson proposed his famous cascade picture qualitatively, for a turbulent flow where the energy is transferred from large scale structures to small scale ones, until reaching viscosity scales where it is converted to heat. This picture now has been widely adopted to describe different type of turbulent phenomena, for not only the classical hydrodynamic turbulence, but also, not limited to, the movement of atmosphere and oceans.
After 100 years of developments, the concept of cascades has been extended significantly. Now, it describes mainly the nonlinear interactions crossing a large range of scales where scale invariants might emerge spontaneously. More precisely, balances between the external forcing and the dissipation are expected for a turbulent system. However, due to the complexity of atmospheric or oceanic systems, such as earth rotation, stratification, large aspect ratio, mesoscale eddies, ocean current, tidal, waves, etc., the exact balance is still unknown. We still lack an efficient methodology to diagnose the scale-to-scale energy or other physical quantities fluxes to characterize the cascade quantitatively, e.g., strength, direction, etc.
With the increasing capability of remote sensing, computational fluid dynamics, field observation, etc., we have accumulated a large amount of field data. It is now a suitable time to celebrate the 100th Anniversary of Richardson's idea of cascades in the geosciences, and to understand it quantitatively.
This interdisciplinary session welcomes theoretical, methodological, laboratory, data analysis works that aim to characterize the cascade in atmosphere and oceans and other fields.
Abstracts 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
The dynamics of the Earth system and its components is highly nonlinear. In particular, several subsystems 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 multidisciplinary 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
Theoretical and model studies show that the ocean is a chaotic system which spontaneously generates a strong, multi-scale intrinsic chaotic variability: uncertainties in ocean model initial states may grow and strongly affect the simulated variability up to multi-decadal and basin scales, with or without coupling to the atmosphere. In addition, ocean simulations require both the use of subgrid-scale parameterizations that crudely mimic unresolved processes, and the calibration of the parameters associated with these parameterizations. In this context of multiple uncertainties, oceanographers are increasingly adopting ensemble simulation strategies, probabilistic analysis methods, and developing stochastic parameterizations for modeling and understanding ocean variability.
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 chaotic ocean variability, its relationship with atmospheric variability, and the use of dynamical system or information theories for the investigation of oceanic variability. We welcome as well studies about the propagation of chaotic ocean 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.
Analysis of the energy transfers between and within climate components has been at the core of many step changes in the understanding of the climate system. Large-scale atmospheric circulation, hydrological cycle and heat/moisture transports are tightly intertwined through radiative and heat energy absorption and transports that are sensitive to multiple forcings and feedbacks. Cross-equatorial energy exchanges by the ocean and atmosphere couple Hadley Circulation and Atlantic Overturning circulation, modulating the location and intensity of the ITCZ and the amount of precipitation in monsoon regions. In the extra-tropics, Rossby waves affect the distribution of precipitation and eddy activity, shaping the meridional heat transport from the low latitudes towards the Poles through intermittent events of persistent and co-located blockings and the occurrence of extreme heat waves or cold outbreaks. In the ocean, understanding of energy transfers from large-scale circulation to the internal wave field, through mesoscale and submesoscale eddies, is the basis for the development of new parameterizations and significant modelling advances.
We invite submissions addressing the interplay between Earth’s energy exchanges and the general circulation using modeling, theory, and observations. We encourage contributions on the forced response and natural variability of the general circulation, understanding present-day climate and past and future changes, and impacts of global features and change on regional climate.
This session focuses on advances in theoretical, methodological and applied studies in hydrologic and broader earth system dynamics, regimes, transitions and extremes, along with their physical understanding, predictability and uncertainty, across multiple spatiotemporal scales.
The session further encourages discussion on interdisciplinary physical and data-based approaches to system dynamics in hydrology and broader geosciences, ranging from novel advances in stochastic, computational, information-theoretic and dynamical system analysis, to cross-cutting emerging pathways in information physics.
Contributions are gathered from a diverse community in hydrology and the broader geosciences, working with diverse approaches ranging from dynamical modelling to data mining, machine learning and analysis with physical process understanding in mind.
The session further encompasses practical aspects of working with system analytics and information theoretic approaches for model evaluation and uncertainty analysis, causal inference and process networks, hydrological and geophysical automated learning and prediction.
The operational scope ranges from the discussion of mathematical foundations to development and deployment of practical applications to real-world spatially distributed problems.
The methodological scope encompasses both inverse (data-based) information-theoretic and machine learning discovery tools to first-principled (process-based) forward modelling perspectives and their interconnections across the interdisciplinary mathematics and physics of information in the geosciences.
Take part in a thrilling session exploring and discussing promising avenues in system dynamics and information discovery, quantification, modelling and interpretation, where methodological ingenuity and natural process understanding come together to shed light onto fundamental theoretical aspects to build innovative methodologies to tackle real-world challenges facing our planet.
The virus is still with us, with more potent variants. It remains the most immediate challenge for geosciences and health, including its impacts on geoscience development (data collection, training, dissemination) and the achievement of the UN Sustainable Development Goals, in particular that urban systems should increase well-being and health.
Long-term visions based on transdisciplinary scientific advances are therefore essential. As a consequence, this session, like the ITS1.1 session in 2021, calls for contributions based on data-driven and theory-based approaches to health in the context of global change. This includes :
- main lessons from lockdowns?
- how to get the best scientific results during a corona pandemic?
- how to manage field works, geophysical monitoring and planetary missions?
- qualitative improvements in epidemic modelling, with nonlinear, stochastic, and complex system science approaches;
- eventual interactions between weather and/or climate factors and epidemic/health problems
- new surveillance capabilities (including contact tracing), data access, assimilation and multidimensional analysis techniques;
- a fundamental revision of our urban systems, their greening and their need for mobility;
- a special focus on urban biodiversity, especially to better manage virus vectors;
- urban resilience must include resilience to epidemics, and therefore requires revisions of urban governance.
The Earth's climate is highly variable on all spatial and temporal scales, and this has direct consequences for society. For example, changes in variability (spatial or temporal) can impact the recurrence frequency of extreme events. Yet it is unclear if a warmer future is one with more or with less climate variability, and at which scales, as a multitude of feedbacks is involved and the instrumental record is short.
The session is multidisciplinary and brings together people working in the geosciences, atmospheric science, oceanography, glaciology, paleoclimatology and environmental physics, to examine the complementarity of ideas and approaches. Members of the PAGES working group on Climate Variability Across Scales (CVAS) and others are welcome.
This session also aims to nurture the development of fractals, multifractals and related nonlinear methodologies applicable to a wide range of geophysical systems and their multiscale interactions. Theories considering scalar and vector fields, applications ranging from urban geosciences (e.g., land use patterns, water management, ecosystems) to atmospheric and oceanic turbulence (e.g., wind energy, mesoscale scaling anisotropy) and climate (e.g., multiscale evolution of extremes), analysis of in-situ, remotely sensed and simulated data are of interest.
Our aim is to provide a forum to present work on:
1- the characterization of climate dynamics using a variety of techniques (e.g. scaling and multifractal techniques and models, recurrence plots, or variance analyses) to study its variability including periodicities, noise levels, or intermittency)
2- the relationship between changes in the mean state (e.g. glacial to interglacial or preindustrial to present to future), and higher-order moments of relevant climate variables, to changes in extreme-event occurrence and the predictability of climate
3- the role of ocean, atmosphere, cryosphere, and land-surface processes in fostering long-term climate variability through linear – or nonlinear – feedbacks and mechanisms
4- the attribution of climate variability to internal dynamics, or the response to natural (volcanic or solar) and anthropogenic forcing
5- the interaction of external forcing (e.g. orbital forcing) and internal variability such as mechanisms for synchronization and pacing of glacial cycles
6- the characterization of probabilities of extremes, including linkage between slow climate variability and extreme event recurrence
The goal of this session is to reconcile short-time/small-scale and long-time/large-scale observations, including geodynamic processes such as subduction, collision, rifting, or mantle lithosphere interactions. Despite the remarkable advances in experimental rock mechanics, the implications of rock-mechanics data for large temporal and spatial scale tectonic processes are still not straightforward, since the latter are strongly controlled by local lithological stratification of the lithosphere, its thermal structure, fluid content, tectonic heritage, metamorphic reactions, and deformation rates.
Mineral reactions have mechanical effects that may result in the development of pressure variations and thus are critical for interpreting microstructural and mineral composition observations. Such effects may fundamentally influence element transport properties and rheological behavior.
Here, we encourage presentations focused on the interplay between metamorphic processes and deformation on all scales, on the rheological behavior of crustal and mantle rocks, and time scales of metamorphic reactions in order to discuss
(1) how and when up to GPa-level differential stress and pressure variations can be built and maintained at geological timescales and modeling of such systems,
(2) deviations from lithostatic pressure during metamorphism: fact or fiction?
(3) the impact of deviations from lithostatic pressure on geodynamic reconstructions.
(4) the effect of porous fluid and partial melting on the long-term strength.
We, therefore, invite the researchers from different domains (rock mechanics, petrographic observations, geodynamic and thermo-mechanical modeling) to share their views on the way forward for improving our knowledge of the long-term rheology and chemo-thermo-mechanical behavior of the lithosphere and mantle.
Environmental systems often span spatial and temporal scales covering different orders of magnitude. The session is oriented toward 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, special attention is devoted to the studies focused on the development of new techniques and integrated instrumentation for multiscale monitoring of high natural risk areas, such as volcanic, seismic, energy exploitation, slope instability, floods, coastal instability, climate changes, and another 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.
Downscaling aims to process and refine global climate model output to provide information at spatial and temporal scales suitable for impact studies. In response to the current challenges posed by climate change and variability, downscaling techniques continue to play an important role in the development of user-driven climate information and new climate services and products. In fact, the "user's dilemma" is no longer that there is a lack of downscaled data, but rather how to select amongst the available datasets and to assess their credibility. In this context, model evaluation and verification is growing in relevance and advances in the field will likely require close collaboration between various disciplines.
Furthermore, epistemologists have started to revisit current practices of climate model validation. This new thread of discussion encourages to clarify the issue of added value of downscaling, i.e. the value gained through adding another level of complexity to the uncertainty cascade. For example, the ‘adequacy-for-purpose view’ may offer a more holistic approach to the evaluation of downscaling models (and atmospheric models, in general) as it considers, for example, user perspectives next to a model’s representational accuracy.
In our session, we aim to bring together scientists from the various geoscientific disciplines interrelated through downscaling: atmospheric modeling, climate change impact modeling, machine learning and verification research. We also invite philosophers of climate science to enrich our discussion about novel challenges faced by the evaluation of increasingly complex simulation models.
Contributions to this session may address, but are not limited to:
- newly available downscaling products,
- applications relying on downscaled data,
- downscaling method development, including the potential for machine learning,
- bias correction and statistical postprocessing,
- challenges in the data management of kilometer-scale simulations,
- verification, uncertainty quantification and the added value of downscaling,
- downscaling approaches in light of computational epistemology.
Rainfall is a “collective” phenomenon emerging from numerous drops. Understanding the relation between the physics of individual drops and that of a population of drops remains an open challenge, both scientifically and at the level of practical implications. This remains true also for solid precipitation. Hence, it is much needed to better understand small scale spatio-temporal precipitation variability, which is a key driving force of the hydrological response, especially in highly heterogeneous areas (mountains, cities). This hydrological response 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 will bring together scientists and practitioners who aim to measure and understand precipitation variability from drop scale to catchment scale as well as its hydrological consequences. Contributions addressing one or several of the following topics are especially targeted:
- Novel techniques for measuring liquid and solid precipitation variability at hydrologically relevant space and time scales (from drop to catchment scale), from in situ measurements to remote sensing techniques, and from ground-based devices to spaceborne platforms. Innovative comparison metrics are welcomed;
- Precipitation drop (or particle) size distribution and its small scale variability, including its consequences for precipitation rate retrieval algorithms for radars, commercial microwave links and other remote sensors;
- Novel modelling or characterization tools of precipitation variability from drop scale to catchment scale from various approaches (e.g. scaling, (multi-)fractal, statistic, deterministic, numerical modelling);
- 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.
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. 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.
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 accuracy in precipitation time series due to, e.g., 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 approaches to modelling of precipitation 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.
Space and astrophysical plasmas are typically in a turbulent state, exhibiting strong fluctuations of various quantities over a broad range of scales. These fluctuations are non-linearly coupled and this coupling may lead to a transfer of energy (and other quantities such as cross helicity, magnetic helicity) from large to small scales and to dissipation. Turbulent processes are relevant for the heating of the solar wind and the corona, acceleration of energetic particles. Many aspects of the turbulence are not well understood, in particular, the injection and onset of the cascade, the cascade itself, the dissipation mechanisms, as well as the role of specific phenomena such as the magnetic reconnections, shock waves, expansion, and plasma instabilities and their relationship with the turbulent cascade and dissipation.
This session will address these questions through discussion of observational, theoretical, numerical, and laboratory work to understand these processes. This session is relevant to many currently operating missions (e.g., Wind, Cluster, MMS, STEREO, THEMIS, Van Allen Probes, DSCOVR) and in particular for the Solar Orbiter and the Parker Solar Probe.
This interdisciplinary session welcomes contributions on novel conceptual and/or methodological approaches and methods for the analysis and statistical-dynamical modeling of observational as well as model time series from all geoscientific disciplines.
Methods to be discussed include, but are not limited to linear and nonlinear methods of time series analysis. time-frequency methods, statistical inference for nonlinear time series, including empirical inference of causal linkages from multivariate data, nonlinear statistical decomposition and related techniques for multivariate and spatio-temporal data, nonlinear correlation analysis and synchronisation, surrogate data techniques, filtering approaches and nonlinear methods of noise reduction, artificial intelligence and machine learning based analysis and prediction for univariate and multivariate time series.
Contributions on methodological developments and applications to problems across all geoscientific disciplines are equally encouraged. We particularly aim at fostering a transfer of new methodological data analysis and modeling concepts among different fields of the geosciences.
Big data analytics will have a primary role in addressing modern challenges such as climate change, disaster management, public health and safety, resources management, and logistics. Most of these phenomena are characterized by spatio-temporal patterns that 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, the variety of modern technologies generating massive volumes of geospatial data at local and global scales, and the rapid growth of computational resources, open new horizons in understanding, modelling, and forecasting complex spatio-temporal systems using stochastics non-linear models.
This session aims at exploring the new challenges and opportunities opened by the spread of big geospatial datasets and 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;
- software and infrastructure development for geospatial data;
- 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. public health management, census data; transport; commuter traffic).
This session collects the abstract submitted to the session “Strategies and Applications of AI and ML in a Spatiotemporal Context” and “Spatio-temporal Data Science: Theoretical Advances and Applications in Computational Geosciences”.
Modelling past climate states, and the transient evolution of Earth’s climate remains challenging. Time periods such as the Paleocene, Eocene, Pliocene, the Last Interglacial, the Last Glacial Maximum or the mid-Holocene span across a vast range of climate conditions. At times, these lie far outside the bounds of the historical period that most models are designed and tuned to reproduce. However, our ability to predict future climate conditions and potential pathways to them is dependent on our models' abilities to reproduce just such phenomena. Thus, our climatic and environmental history is ideally suited to thoroughly test and evaluate models against data, so they may be better able to simulate the present and make future climate projections.
We invite papers on palaeoclimate-specific model development, model simulations and model-data comparison studies. Simulations may be targeted to address specific questions or follow specified protocols (as in the Paleoclimate Modelling Intercomparison Project – PMIP or the Deep Time Model Intercomparison Project – DeepMIP). They may include anything between time-slice equilibrium experiments to long transient climate simulations (e.g. transient simulations covering the entire glacial cycle as per the goal of the PalMod project) with timescales of processes ranging from synoptic scales to glacial cycles and beyond. Comparisons may include past, historical as well as future simulations and focus on comparisons of mean states, gradients, circulation or modes of variability using reconstructions of temperature, precipitation, vegetation or tracer species (e.g. δ18O, δD or Pa/Th).
Evaluations of results from the latest phase of PMIP4-CMIP6 are particularly encouraged. However, we also solicit comparisons of different models (comprehensive GCMs, isotope-enabled models, EMICs and/or conceptual models) between different periods, or between models and data, including an analysis of the underlying mechanisms as well as contributions introducing novel model or experimental setups.
Unsupervised, supervised, semi-supervised as well as reinforcement learning are now increasingly used to address Earth system related challenges.
Machine learning could help extract information from numerous Earth System data, such as in-situ and 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 application of these novel methods for predicting and monitoring our earth system. This includes (but it is not restricted to):
- the use of machine learning to improve forecast skill
- generate significant speedups
- design new parameterization schemes
- emulate numerical models.
Please consider submitting abstracts focussed on ML applied to observations and modelling of climate processes to the companion "ML for Climate Science" session.
Recent developments in machine learning (ML) are transforming Earth observation data analysis and modelling of the Earth system and its constituent processes. While statistical models have been used for a long time, state-of-the-art machine and deep learning algorithms allow encoding non-linear, spatio-temporal relationships robustly without sacrificing interpretability. These advances have the potential to accelerate climate science by improving our understanding of the underlying processes, reducing and better quantifying uncertainty, and even making predictions directly from observations across different spatio-temporal scales.
This session aims to provide a venue to present the latest progress in the use of ML applied to all aspects of climate science including, but not limited to:
- Causal discovery and inference
- Learning (causal) process and feature representations in observations
- Hybrid models (physically informed ML)
- Novel detection and attribution approaches
- Probabilistic modelling and uncertainty quantification
- Explainable AI applications to climate science
Please consider submitting abstracts focussed on ML for model improvement, particularly for near-term (including seasonal) forecasting to the companion “ML for Earth System modelling” session.
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 presentations dealing with both theoretical developments in statistical post-processing and evaluation of their performances in different practical applications oriented toward environmental predictions, and new developments dealing with the problem of combining or blending different types of forecasts in order to improve reliability from very short to long time scales.
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 during data assimilation, prediction and validation 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 or observation errors are present. Specific problems arise in situations where coupling is present between different components of the Earth system, which gives rise to the so called coupled data assimilation.
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.
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 global and regional climate-related risks.
The latest developments and progress in climate forecasting on subseasonal-to-decadal and longer timescales will be discussed and evaluated. This will include presentations and discussions of predictions for the different time horizons 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, exploration of artificial-intelligence methods, etc.
Following the new WCRP 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 between atmosphere, land, ocean, and sea-ice components, as well as the impacts of coupling and feedbacks in physical, chemical, biological, and human dimensions. 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.
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.
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 evaluating and improving model simulations of ENSO, the tropical mean state and the tropical basins interactions basin are especially welcomed.
Since its inception, data assimilation has proven to be enormously useful in the most varied fields throughout the Earth Sciences. It is certainly essential in meteorology, where the short-range forecasts would otherwise be almost impossible. In oceanography, its development has been slower, partly due to the smaller number of continuous and stable observations, and partly due to the fewer studies that show the importance of ocean forecasts for societal benefit. However, recently, these techniques are used more and more widely, both in operational oceanography and to produce climate reconstructions. Although the techniques are similar to those used in the atmospheric field, they have to deal with particularities due to the different environment, where the boundary conditions, open and closed, have greater importance, and the sparsity of observations poses unique challenges.
In this session, we welcome contributions describing data assimilation techniques, both methodological and case studies, in the oceanographic field. We welcome presentations of new techniques or new types of observations that cover every aspect of data assimilation, including varied applications of data assimilation, both in coastal seas and the open ocean.
Forecasting the weather, in particular severe and extreme weather has always been the most important subject in meteorology. This session will focus on recent research and developments on forecasting techniques, in particular those designed for operations and impact oriented. Contributions related to nowcasting, meso-scale and convection permitting modelling, ensemble prediction techniques, and statistical post-processing are very welcome.
Topics may include:
Nowcasting methods and systems, use of observations and weather analysis
Mesoscale and convection permitting modelling
Ensemble prediction techniques
Ensemble-based products for severe/extreme weather forecasting
Seamless deterministic and probabilistic forecast prediction
Post-processing techniques, statistical methods in prediction
Use of machine learning, data mining and other advanced analytical techniques
Impact oriented weather forecasting
Presentation of results from relevant international research projects of EU, WMO, and EUMETNET etc.
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 aim 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.
Planktonic organisms live in suspension in marine or fresh waters where they have adapted through the slow process of natural evolution (over hundred of thousands of generations) to the harsh turbulent currents of their environment. Therefore, contrary to what the meaning of their name “marine drifter” might let to speculate, their dynamics is potentially different from the one of material bodies passively transported by fluid flows. It is indeed known that these organisms developed many adaptive strategies involving shape and density regulation, swimming activity, aggregation and other mechanisms in order to be sheltered from or to take advantage of turbulent flow features.
Bloom inceptions, thin layers formation, motility, nutrient and light uptakes, specific Lagrangian dynamics, among others are topics involving phytoplankton and turbulence. Jumps, grazing, contact rates, and vertical migration are, among others, topics concerning zooplankton in turbulence. For all planktonic species, adaptive mechanisms in response not only to mechanical, but also chemical and electro-magnetic (such as luminous) cues are topics of great interest.
This interdisciplinary session will welcome works from marine ecologists, oceanographers, fluid-dynamicists, physicists and mathematical modellers. Contributions in the fields of observation, laboratory experimentations, numerical models (such as Computational Fluid Dynamics simulations of non-spherical or motile particles) are welcome. Both phytoplankton and zooplankton will be considered, as well as marine and freshwater studies.
This session focuses on the non-linear processes that take place in space, laboratory and astrophysical plasma. These processes are usually not separated from one another and often go "hand in hand". Just to mention a few examples, magnetic reconnection is an established ingredient of the turbulence cascade and it is also responsible for the production of turbulence in reconnection outflows; shocks may form in collisional and collisionless reconnection processes and can be responsible for turbulence formation, as for instance in the turbulent magnetosheath; magnetic and velocity-shear driven instabilities triggers plasma turbulence in their non-linear phase and can locally develop in turbulent plasmas. All these non-linear processes are responsible for particle acceleration and plasma heating in the environments where they take place.
We are now in a fortunate time for the investigation of these processes, where we can use a combined approach based on simulations and observations together. Simulations can deliver output in a temporal and spatial range of scales going from fluid to electron kinetic. On the observation side, high cadence measurements of particles and fields, high resolution 3D measurements of particle distribution functions and multipoint measurements make it easier to reconstruct the 3D space surrounding the spacecrafts. In this context, the Parker Solar Probe and the Solar Orbiter mission are opening new research scenarios in heliophysics, providing a consistent amount of new data to be analysed.
This session welcomes simulations, observational, and theoretical works relevant for the study of the above mentioned plasma processes. Particularly welcome this year, will be works focusing on how non-linear processes accelerate particles and produce heating in collisionless plasmas. We also encourage papers proposing new methods in simulation techniques and data analysis, as for example those rooted in Artificial Intelligence and Machine Learning.
This session welcomes contributions presenting advances in, and approaches to, the modelling, monitoring, and forecasting of internal waves in stratified estuaries, lakes and the coastal oсean.
Internal solitary waves (ISWs) and large-amplitude internal wave 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 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 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 thus of broad scientific 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.
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 wave fields and fractures in geomaterials
• 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
• Triggering effects and instability in geomaterials
• Active nature of geomaterials (e.g., seismic emission induced by stress and pressure wave propagation)
• Non-linear mechanics of hydraulic fracturing
• Synchronization in fracture processes including 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.
We invite presentations on ocean surface waves, and wind-generated waves in particular, their dynamics, modelling and applications. This is 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.
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. 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, including those on major collaborative projects, such as DataWave.
In 2015, the UN Sustainable Development Goals and the Paris Agreement on climate recognized the deteriorating resilience of the Earth system, with planetary-scale human impacts constituting a new geological epoch: the Anthropocene. Earth system resilience critically depends on the nonlinear interplay of positive and negative feedbacks of biophysical and increasingly also socio-economic processes. These include dynamics and interactions between the carbon cycle, the atmosphere, oceans, large-scale ecosystems, and the cryosphere, as well as the dynamics and perturbations associated with human activities.
With rising anthropogenic pressures, there is an increasing risk we might be hitting the ceiling of some of the self-regulating feedbacks of the Earth System, and cross tipping points which could trigger large-scale and partly irreversible impacts on the environment, and impact the livelihood of millions of people. Potential domino effects or tipping cascades could arise due to the interactions between these tipping elements and lead to a further decline of Earth resilience. At the same time, there is growing evidence supporting the potential of positive (social) tipping points that could propel rapid decarbonization and transformative change towards global sustainability.
In this session we invite contributions on all topics relating to tipping points in the Earth system, positive (social) tipping, as well as their interaction and domino effects. We are particularly interested in various methodological approaches, from Earth system modelling to conceptual modelling and data analysis of nonlinearities, tipping points and abrupt shifts in the Earth system.
Non-destructive testing (NDT) methods are employed in a variety of engineering and geosciences applications and their stand-alone use has been greatly investigated to date. New theoretical developments, technological advances and the progress achieved in surveying, data processing and interpretation have in fact led to a tremendous growth of the equipment reliability, allowing outstanding data quality and accuracy.
Nevertheless, the requirements of comprehensive site and material investigations may be complex and time-consuming, involving multiple expertise and multiple equipment. The challenge is to step forward and provide an effective integration between data outputs with different physical quantities, scale domains and resolutions. In this regard, enormous development opportunities relating to data fusion, integration and correlation between different NDT methods and theories are to be further investigated.
This Session primarily aims at disseminating contributions from state-of-the-art NDT methods and new numerical developments, promoting the integration of existing equipment and the development of new algorithms, surveying techniques, methods and prototypes for effective monitoring and diagnostics. NDT techniques of interest are related–but not limited to–the application of acoustic emission (AE) testing, electromagnetic testing (ET), ground penetrating radar (GPR), geoelectric methods (GM), laser testing methods (LM), magnetic flux leakage (MFL), microwave testing, magnetic particle testing (MT), neutron radiographic testing (NR), radiographic testing (RT), thermal/infrared testing (IRT), ultrasonic testing (UT), seismic methods (SM), vibration analysis (VA), visual and optical testing (VT/OT).
The Session will focus on the application of different NDT methods and theories and will be related –but not limited to– the following investigation areas:
- advanced data fusion;
- advanced interpretation methods;
- design and development of new surveying equipment and prototypes;
- real-time and remote assessment and monitoring methods for material and site inspection (real-life and virtual reality);
- comprehensive and inclusive information data systems for the investigation of survey sites and materials;
- numerical simulation and modelling of data outputs with different physical quantities, scale domains and resolutions;
- advances in NDT methods, numerical developments and applications (stand-alone use of existing and state-of-the-art NDTs).
Glacial Isostatic Adjustment (GIA) describes the dynamic response of the solid Earth to ice sheet glaciation/deglaciation, which affects the spatial and temporal sea level changes, and induces surface deformation, gravitational field variation and stress changes in the subsurface. The process is influenced by the ice sheet characteristics (e.g., extent, volume, grounding line) and solid Earth structure. With more observational data (e.g., relative sea-level data, GPS data, tide gauges, terrestrial and satellite gravimetry, glacially induced faults) are available/standardized, we can better investigate the interactions between the ice sheets, solid Earth and sea levels, and reveal the ice sheet and sea-level evolution histories and rheological properties of the Earth.
This session invites contributions discussing observations, analysis, and modelling of ice sheet dynamics, solid Earth response, and the resulting global, regional and local sea-level changes and land deformation, including paleo ice sheet and paleo sea-level investigations, geodetic measurements of crustal motion and gravitational change, GIA modelling with complex Earth models (e.g., 3D viscosity, non-linear rheologies) and coupled ice-sheet/Earth modelling, investigations on glacially triggered faulting as well as the Earth’s elastic response to present-day ice mass changes. We also welcome abstracts that address the future ice sheets/shelves evolution and sea-level projection as well as GIA effects on oil migration and nuclear waste repositories. Contributions related to both polar regions and previously glaciated regions are welcomed. This session is co-sponsored by the SCAR sub-committee INSTANT-EIS, Earth - Ice - Sea level, in view of instabilities and thresholds in Antarctica https://www.scar.org/science/instant/home/.
Recently, there have been significant breakthroughs in the use of fiber-optic sensing techniques to interrogate cables at high precision both on land and at sea as well as in boreholes and at the surface. Laser reflectometry using both fit-to-purpose and commercial fiber-optic cables have successfully detected a variety of signals including microseism, local and teleseismic earthquakes, volcanic events, ocean dynamics, etc. Other laser-based techniques can be used to monitor distributed strain, temperature, and even chemicals at a scale and to an extent previously unattainable with conventional geophysical methods.
We welcome any contributions to recent development in the fields of applications, instrumentation, and theoretical advances for geophysics with fiber-optic sensing techniques. These may include - but are not limited to - application of fiber-optic cables or sensors in seismology, geodesy, geophysics, natural hazards, oceanography, urban environment, geothermal application, etc. with an emphasis on laboratory studies, large-scale field tests, and modeling. We also encourage contributions on data analysis techniques, machine learning, data management, instruments performances and comparisons as well as new experimental field studies.
Hydroclimatic conditions and availability of water resources in space and time constitute important factors for maintaining adequate food supply, the quality of the environment, and the welfare of citizens and inhabitants, in the context of a post-pandemic sustainable growth and economic development. This session is designed to explore the impacts of hydroclimatic variability, climate change, and temporal and spatial availability of water resources on different factors, such as food production, population health, environment quality, and local ecosystem welfare.
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.
• Smart infrastructure for water usage, reduction of water losses, 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 supply, 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 forcing (e.g. inappropriate agricultural practices, and land usage) on the natural environment (e.g. health impacts from water and air, fragmentation of habitats, etc.)
Extreme hydro-meteorological events drive many hydrologic and geomorphic hazards, such as floods, landslides and debris flows, which pose a significant threat to modern societies on a global scale. The continuous increase of population and urban settlements in hazard-prone areas in combination with evidence of changes in extreme weather events lead to a continuous increase in the risk associated with weather-induced hazards. To improve resilience and to design more effective mitigation strategies, we need to better understand the aspects of vulnerability, risk, and triggers that are associated with these hazards.
This session aims at gathering contributions dealing with various hydro-meteorological hazards that address the aspects of vulnerability analysis, risk estimation, impact assessment, mitigation policies and communication strategies. Specifically, we aim to collect contributions from academia, the industry (e.g. insurance) and government agencies (e.g. civil protection) that will help identify the latest developments and ways forward for increasing the resilience of communities at local, regional and national scales, and proposals for improving the interaction between different entities and sciences.
Contributions focusing on, but not limited to, novel developments and findings on the following topics are particularly encouraged:
- Physical and social vulnerability analysis and impact assessment of hydro-meteorological hazards
- Advances in the estimation of socioeconomic risk from hydro-meteorological hazards
- Characteristics of weather and precipitation patterns leading to high-impact events
- Relationship between weather and precipitation patterns and socio-economic impacts
- Hazard mitigation procedures
- Strategies for increasing public awareness, preparedness, and self-protective response
- Impact-based forecast, warning systems, and rapid damage assessment.
- Insurance and reinsurance applications
Proper characterization of uncertainty remains a major research and operational challenge in Environmental Sciences, and is inherent to many aspects of modelling impacting model structure development; parameter estimation; an adequate representation of the data (inputs data and data used to evaluate the models); initial and boundary conditions; and hypothesis testing. To address this challenge, methods for a) uncertainty analysis (UA) that seek to identify, quantify and reduce the different sources of uncertainty, as well as propagating them through a system/model, and b) the closely-related methods for sensitivity analysis (SA) that evaluate the role and significance of uncertain factors (in the functioning of systems/models), have proved to be very helpful.
This session invites contributions that discuss advances, both in theory and/or application, in methods for SA/UA applicable to all Earth and Environmental Systems Models (EESMs), which embraces all areas of hydrology, such as classical hydrology, subsurface hydrology and soil science.
Topics of interest include (but are not limited to):
1) Novel methods for effective characterization of sensitivity and uncertainty
2) Analyses of over-parameterised models enabled by AI/ML techniques
3) Single- versus multi-criteria SA/UA
4) Novel approaches for parameter estimation, data inversion and data assimilation
5) Novel methods for spatial and temporal evaluation/analysis of models
6) The role of information and error on SA/UA (e.g., input/output data error, model structure error, parametric error, regionalization error in environments with no data etc.)
7) The role of SA in evaluating model consistency and reliability
8) Novel approaches and benchmarking efforts for parameter estimation
9) Improving the computational efficiency of SA/UA (efficient sampling, surrogate modelling, parallel computing, model pre-emption, model ensembles, etc.)
Research and innovation in exploration and mining of raw materials is increasingly focused on the prospect of developing completely new methods and technologies to find and exploit new mineral deposits within Europe. Amongst these technologies, robotisation and miniaturisation of exploration/production platforms (robotic autonomous explorers & miners) allow to reconsider “non-economical” deposits (abandoned, small, ultra-depth), extract them in a socially and environmentally responsible way, and produce useful metallurgical products which can be used further-on for manufacturing.
Underground operation of an autonomous or semi-autonomous underground platform is an extremely challenging problem where solution have to come from the close collaboration of robotic engineers, mining engineers, mineralogists, geochemists, geophysicians and structuralists to solve challenges as diverse as locomotion in water or slurries, localization and mapping in relationship with an orebody, automated extraction planning, optimization of extraction tools, and real-time selective mineralogy.
Contributions from geologists, geophysicists, mining engineers, robotic engineers, software developers are welcome.
Publishing your research in a peer reviewed journal is essential for a career in research. All EGU-affiliated journals are fully open access which is great, but the unique open discussion and transparent peer review process can be daunting for first time submitters and early career scientists. This short course will cover all you need to know about the publication process from start to end for EGU journals, and give you a chance to ask the editors some questions. This includes: what the editor looks for in your submitted paper, how to deal with corrections or rejections, and how best to communicate with your reviewers and editors for a smooth transition from submission to publication. Ample time will be reserved for open discussion for the audience to ask questions to the editors, and for the editors to suggest ‘top tips’ for successful publication. This course is aimed at early-career researchers who are about to step into the publication process, and those who are yet to publish in EGU journals. Similarly, this course will be of interest to those looking to get involved in the peer-review process through reviewing and editing. This short course is part of the “Meet the EGU Journal Editors” webinar series that was held prior to the EGU General Assembly 2022.
We are excited to welcome our panelists for this session, who will be representing their respective journals:
Observations and measurements of geophysical systems and dynamical phenomena are obtained as time series or spatio-temporal data whose dynamics usually manifests a nonlinear multiscale (in terms of time and space) behavior. During the past decades, nonlinear approaches in geosciences have rapidly developed to gain novel insights on weather and climate dynamics, fluid dynamics, on turbulence and stochastic behaviors, on the development of chaos in dynamical systems, and on concepts of networks, nowadays frequently employed in geosciences.
In this short course, we will offer a broad overview of the development and application of nonlinear concepts across the geosciences in terms of recent successful applications from various fields, ranging from climate to near-Earth space physics. The focus will be on a comparison between different methods to investigate various aspects of both known and unknown physical processes, moving from past accomplishments to future challenges.
Peter Ditlevsen: "The paleoclimatic record, a tale of dynamics on many time scales: what can be learned about climate change"
Tommaso Alberti: "From global to local complexity measures: learning from dynamical systems and turbulence"
Reik Donner: "Harnessing causal discovery tools for process inference from multivariate geoscientific time series"
The climate system as a whole can be viewed as a highly complex thermal/heat engine, in which numerous processes continuously interact to transform heat into work and vice-versa. As any physical system, the climate system obeys the basic laws of thermodynamics, and we may therefore expect the tools of non-equilibrium thermodynamics to be particularly useful in describing and synthesising its properties. The main aim of this short course will be twofold. Part 1 will provide an advanced introduction to the fundamentals of equilibrium and non-equilibrium thermodynamics, irreversible processes and energetics of multicomponent stratified fluids. Part 2 will illustrate the usefulness of this viewpoint to summarize the main features of the climate system in terms of thermodynamic cycles, as well as a diagnostic tool to constrain the behavior of climate models. Although the aim is for this to be a self-contained module, some basic knowledge of the subject would be beneficial to the participants.
- The first part, chaired by Remi Tailleux, will provide an advanced introduction on the fundamentals of equilibrium and non-equilibrium thermodynamics, irreversible processes and energetics.
- The second part, chaired by Valerio Lembo and Gabriele Messori, will illustrate some applications of thermodynamics to the study of the climate system and its general circulation.
The short course will be structured as such: - Part 1 (45 mins): theoretical background, by Remi Tailleux;
- Short break (5 mins);
- Part 2 (15 mins): diagnosing thermodynamics in climate models, by Valerio Lembo;
- Part 3 (10 mins): dynamics and heat transports in the atmosphere, by Gabriele Messori;
The climate is highly variable over wide ranges of scale in both space and time so that the amplitude of changes systematically depends on the scale of observations. As a consequence, climate variations recorded in time series or spatial distributions, which are produced through modelling or empirical analyses are inextricably linked to their space-time scales and is a significant part of the uncertainties in the proxy approaches. Rather than treating the variability as a limitation to our knowledge, as a distraction from mechanistic explanations and theories, in this course the variability is treated as an important, fundamental aspect of the climate dynamics that must be understood and modelled in its own right. Long considered as no more than an uninteresting spectral “background”, modern data shows that in fact it contains most of the variance.
We review techniques that make it possible to systematically analyse and model the variability of instrumental and proxy data, the inferred climate variables and the outputs of GCM’s. These analyses enable us to cover wide ranges of scale in both space and in time - and jointly in space-time - without trivializing the links between the measurements, proxies and the state variables (temperature, precipitation etc.). They promise to systematically allow us to compare model outputs with data, to understand the climate processes from small to large and from fast to slow. Specific tools that will be covered include spectral analysis, scaling fluctuation analysis, wavelets, fractals, multifractals, and stochastic modeling; we discuss corresponding software. We also include new developments in the Fractional Energy Balance Equation approach that combines energy and scale symmetries.
Within this course, the attendees are taught how to identify possible cyclicities in paleoclimate data (e.g., sediments, speleothems) or any other geological record. We will start from the basics of which data can be analysed, go over power spectra, and discuss the application of filters and Wavelet Analysis. We will discuss the advantages and disadvantages of different methods, and give some examples from Earth Sciences to highlight common pitfalls. The aim of this course is to give a brief overview of the most common techniques and give participants the insight to prepare and analyse their data themselves. A variety of computational platforms are available for time-series analysis. In this course, we will introduce different tools and techniques by making use of the programming language R.
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