Preprints
Filtering by Subject: Non-linear Dynamics
Efficient Estimation of Climate State and Its Uncertainty Using Kalman Filtering with Application to Policy Thresholds and Volcanism
Published: 2022-10-18
Subjects: Longitudinal Data Analysis and Time Series, Non-linear Dynamics, Planetary Sciences, Statistical Models
We present the Energy Balance Model – Kalman Filter (EBM-KF), a hybrid model of the global mean surface temperature (GMST) and ocean heat content anomaly (OHCA). It combines an annual energy balance model (difference equations) with 17 parameters drawn from the literature and a statistical Extended Kalman Filter assimilating GMST and OHCA, either observed timeseries or simulated by earth [...]
Diapycnal Displacement, Diffusion, and Distortion of Tracers in the Ocean
Published: 2022-01-07
Subjects: Applied Mathematics, Fluid Dynamics, Non-linear Dynamics, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
Small-scale mixing drives the diabatic upwelling that closes the abyssal ocean overturning circulation. Indirect microstructure measurements of in situ turbulence suggest that mixing is bottom enhanced over rough topography, implying downwelling in the interior and stronger upwelling in a sloping bottom boundary layer. Tracer release experiments (TREs), in which inert tracers are purposefully [...]
Nonlinear time series analysis of palaeoclimate proxy records
Published: 2021-11-08
Subjects: Applied Statistics, Climate, Dynamic Systems, Earth Sciences, Geology, Longitudinal Data Analysis and Time Series, Multivariate Analysis, Non-linear Dynamics, Physical Sciences and Mathematics, Sedimentology, Statistical, Nonlinear, and Soft Matter Physics
Identifying and characterising dynamical regime shifts, critical transitions or potential tipping points in palaeoclimate time series is relevant for improving the understanding of often highly nonlinear Earth system dynamics. Beyond linear changes in time series properties such as mean, variance, or trend, these nonlinear regime shifts can manifest as changes in signal predictability, [...]
Goal-Oriented Error Estimation and Mesh Adaptation for Shallow Water Modelling
Published: 2019-12-31
Subjects: Applied Mathematics, Computer Sciences, Engineering, Non-linear Dynamics, Numerical Analysis and Computation, Numerical Analysis and Scientific Computing, Partial Differential Equations, Physical Sciences and Mathematics
Numerical modelling frequently involves a diagnostic quantity of interest (QoI) - often of greater importance than the PDE solution - which we seek to accurately approximate. In the case of coastal ocean modelling the power output of a tidal turbine farm is one such example. Goal-oriented error estimation and mesh adaptation can be used to provide meshes which are well-suited to achieving this [...]
Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM
Published: 2019-06-20
Subjects: Applied Mathematics, Artificial Intelligence and Robotics, Atmospheric Sciences, Climate, Computer Sciences, Dynamic Systems, Earth Sciences, Fluid Dynamics, Non-linear Dynamics, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Physics
In this paper, the performance of three deep learning methods for predicting short-term evolution and for reproducing the long-term statistics of a multi-scale spatio-temporal Lorenz 96 system is examined. The methods are: echo state network (a type of reservoir computing, RC-ESN), deep feed-forward artificial neural network (ANN), and recurrent neural network with long short-term memory [...]
River deltas as Multiplex networks: A framework for studying multi-process multi-scale connectivity via coupled-network theory
Published: 2018-04-13
Subjects: Applied Mathematics, Dynamic Systems, Earth Sciences, Environmental Sciences, Geomorphology, Hydrology, Mathematics, Non-linear Dynamics, Physical Sciences and Mathematics, Physics, Statistical, Nonlinear, and Soft Matter Physics
Transport of water, nutrients or energy fluxes in many natural or coupled human-natural systems occurs along different pathways that often have a wide range of transport timescales and might exchange fluxes with each other dynamically (e.g., surface-subsurface). Understanding this type of transport is key to predicting how landscapes will change under changing forcing. Here, we present a general [...]