Iterative integration of deep learning in hybrid Earth surface system modelling
Earth system modelling (ESM) is essential for understanding past, present and future Earth
processes. Deep learning (DL), with the data-driven strength of neural networks, has …
processes. Deep learning (DL), with the data-driven strength of neural networks, has …
Complex network approaches to nonlinear time series analysis
In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …
complex network methods for the characterization of dynamical systems based on time …
What we talk about when we talk about seasonality–A transdisciplinary review
O Kwiecien, T Braun, CF Brunello, P Faulkner… - Earth-Science …, 2022 - Elsevier
The role of seasonality is indisputable in climate and ecosystem dynamics. Seasonal
temperature and precipitation variability are of vital importance for the availability of food …
temperature and precipitation variability are of vital importance for the availability of food …
Theoretical and paleoclimatic evidence for abrupt transitions in the Earth system
Specific components of the Earth system may abruptly change their state in response to
gradual changes in forcing. This possibility has attracted great scientific interest in recent …
gradual changes in forcing. This possibility has attracted great scientific interest in recent …
Time averaging and emerging nonergodicity upon resetting of fractional Brownian motion and heterogeneous diffusion processes
How different are the results of constant-rate resetting of anomalous-diffusion processes in
terms of their ensemble-averaged versus time-averaged mean-squared displacements …
terms of their ensemble-averaged versus time-averaged mean-squared displacements …
A novel framework for carbon price forecasting with uncertainties
M Wang, M Zhu, L Tian - Energy economics, 2022 - Elsevier
Carbon price prediction is a key issue in the field of carbon market research. However, the
existing methods of carbon price forecasting mostly regard carbon price series as a certain …
existing methods of carbon price forecasting mostly regard carbon price series as a certain …
The market-linkage of the volatility spillover between traditional energy price and carbon price on the realization of carbon value of emission reduction behavior
Q Wu, M Wang, L Tian - Journal of Cleaner Production, 2020 - Elsevier
Establishing a carbon market is widely regarded as an effective means of controlling global
carbon emission. Purchasing carbon emission right will increase the cost of enterprises …
carbon emission. Purchasing carbon emission right will increase the cost of enterprises …
A brief introduction to nonlinear time series analysis and recurrence plots
B Goswami - Vibration, 2019 - mdpi.com
Nonlinear time series analysis gained prominence from the late 1980s on, primarily because
of its ability to characterize, analyze, and predict nontrivial features in data sets that stem …
of its ability to characterize, analyze, and predict nontrivial features in data sets that stem …
Trends in recurrence analysis of dynamical systems
N Marwan, KH Kraemer - The European Physical Journal Special Topics, 2023 - Springer
The last decade has witnessed a number of important and exciting developments that had
been achieved for improving recurrence plot-based data analysis and to widen its …
been achieved for improving recurrence plot-based data analysis and to widen its …
Automatic detection of abrupt transitions in paleoclimate records
Bifurcations and tipping points (TPs) are an important part of the Earth system's behavior.
These critical points represent thresholds at which small changes in the system's parameters …
These critical points represent thresholds at which small changes in the system's parameters …