About this Research Topic
Non-linear dynamic analysis of environmental processes plays a significant role in understanding the intricate behaviors of environmental systems. These systems often exhibit complex, non-linear interactions that cannot be adequately explained by simple linear models. Linear models may fail to capture the emergent behaviors and intricate feedback mechanisms inherent in natural systems, leading to inaccurate predictions and models. Recent studies have highlighted the importance of non-linear dynamics in various environmental contexts, such as climate change, renewable energy, air pollution, oceanography, hydrological processes, and ecosystems. Despite these advancements, there remains a need for more comprehensive research to fully understand and model these non-linear interactions. Addressing these gaps is crucial for improving our predictive capabilities and informing sustainable management practices.
This Research Topic aims to address the importance of non-linear properties in environmental processes and explore recent advances in this field. By capturing the complexity and dynamics of natural systems, non-linear properties offer valuable insights into system behavior, emergent phenomena, feedback mechanisms, thresholds, tipping points, resilience, adaptability, and modeling capabilities. The goal is to enhance our understanding and predictive capacities, ultimately aiding in the development of sustainable management practices and informed decision-making.
To gather further insights into the non-linear dynamic analysis of environmental processes, we welcome articles addressing, but not limited to, the following themes:
- Scaling and multifractality
- Stochastic models
- Artificial intelligence (machine learning, deep learning)
- Turbulence
- Chaotic analysis
- Multiscale spectral analysis
- Entropy
This Research Topic aims to address the importance of non-linear properties in environmental processes and explore recent advances in this field. By capturing the complexity and dynamics of natural systems, non-linear properties offer valuable insights into system behavior, emergent phenomena, feedback mechanisms, thresholds, tipping points, resilience, adaptability, and modeling capabilities. The goal is to enhance our understanding and predictive capacities, ultimately aiding in the development of sustainable management practices and informed decision-making.
To gather further insights into the non-linear dynamic analysis of environmental processes, we welcome articles addressing, but not limited to, the following themes:
- Scaling and multifractality
- Stochastic models
- Artificial intelligence (machine learning, deep learning)
- Turbulence
- Chaotic analysis
- Multiscale spectral analysis
- Entropy
Keywords: modelling, Non-linear Dynamics, environmental processes, stochastic methods, scaling
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
