NG003
Bridging physical, analytical, information-theoretic and machine learning approaches to complex system dynamics and predictability across the Earth System Sciences
Bridging physical, analytical, information-theoretic and machine learning approaches to complex system dynamics and predictability across the Earth System Sciences
Session ID#: 161524
Session Description:
This session focuses on advances in theoretical, methodological and applied studies across Earth system dynamics, regimes, transitions and extremes, along with their physical understanding, predictability and uncertainty, across multiple spatiotemporal scales.
The session also encourages advances across interdisciplinary physical and data-based approaches to system dynamics across the geosciences, ranging from novel advances in stochastic, computational, information-theoretic and dynamical system analysis, to cross-cutting emerging pathways in information physics and systems intelligence.
Contributions are welcome spanning 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, 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 session also encourages advances across interdisciplinary physical and data-based approaches to system dynamics across the geosciences, ranging from novel advances in stochastic, computational, information-theoretic and dynamical system analysis, to cross-cutting emerging pathways in information physics and systems intelligence.
Contributions are welcome spanning 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, 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.
Co-Organized:
- H - Hydrology
Index Terms:
1942 Machine learning [INFORMATICS]
3275 Uncertainty quantification [MATHEMATICAL GEOPHYSICS]
4430 Complex systems [NONLINEAR GEOPHYSICS]
4494 Instruments and techniques [NONLINEAR GEOPHYSICS]
Primary Convener: Rui A.P. Perdigão, Meteoceanics Institute for Complex System Science, North Atlantic Climate Centre, Lisbon, Portugal; Meteoceanics Institute for Complex System Science, Vienna, Austria
Conveners: Julia Hall, Meteoceanics Institute for Complex System Science, GeoSys Department, Lisbon, Portugal and Cristina Prieto Sierra, IHCantabria - Instituto de Hidráulica Ambiental de la Universidad de Cantabria, Santander, Spain
See more of: Nonlinear Geophysics