A joint state and parameter estimation scheme for nonlinear dynamical systems

We present a novel algorithm for concurrent model state and parameter estimation in nonlinear dynamical systems. The new scheme uses ideas from three dimensional variational data assimilation (3D-Var) and the extended Kalman filter (EKF) together with the technique of state augmentation to estimate uncertain model parameters alongside the model state variables in a sequential filtering system. The method is relatively simple to implement and computationally inexpensive to run for large systems with relatively few parameters. We demonstrate the efficacy of the method via a series of identical twin experiments with three simple dynamical system models. The scheme is able to recover the parameter values to a good level of accuracy, even when observational data are noisy. We expect this new technique to be easily transferable to much larger models.

Neurofuzzy design and model construction of nonlinear dynamical processes from data

A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

Dynamical complexity in a mean-field model of human EEG

A recently proposed mean-field theory of mammalian cortex rhythmogenesis describes the salient features of electrical activity in the cerebral macrocolumn, with the use of inhibitory and excitatory neuronal populations (Liley et al 2002). This model is capable of producing a range of important human EEG (electroencephalogram) features such as the alpha rhythm, the 40 Hz activity thought to be associated with conscious awareness (Bojak & Liley 2007) and the changes in EEG spectral power associated with general anesthetic effect (Bojak & Liley 2005). From the point of view of nonlinear dynamics, the model entails a vast parameter space within which multistability, pseudoperiodic regimes, various routes to chaos, fat fractals and rich bifurcation scenarios occur for physiologically relevant parameter values (van Veen & Liley 2006). The origin and the character of this complex behaviour, and its relevance for EEG activity will be illustrated. The existence of short-lived unstable brain states will also be discussed in terms of the available theoretical and experimental results. A perspective on future analysis will conclude the presentation.

Towards a general theory of extremes for observables of chaotic dynamical systems

In this paper we provide a connection between the geometrical properties of the attractor of a chaotic dynamical system and the distribution of extreme values. We show that the extremes of so-called physical observables are distributed according to the classical generalised Pareto distribution and derive explicit expressions for the scaling and the shape parameter. In particular, we derive that the shape parameter does not depend on the cho- sen observables, but only on the partial dimensions of the invariant measure on the stable, unstable, and neutral manifolds. The shape parameter is negative and is close to zero when high-dimensional systems are considered. This result agrees with what was derived recently using the generalized extreme value approach. Combining the results obtained using such physical observables and the properties of the extremes of distance observables, it is possible to derive estimates of the partial dimensions of the attractor along the stable and the unstable directions of the flow. Moreover, by writing the shape parameter in terms of moments of the extremes of the considered observable and by using linear response theory, we relate the sensitivity to perturbations of the shape parameter to the sensitivity of the moments, of the partial dimensions, and of the Kaplan–Yorke dimension of the attractor. Preliminary numer- ical investigations provide encouraging results on the applicability of the theory presented here. The results presented here do not apply for all combinations of Axiom A systems and observables, but the breakdown seems to be related to very special geometrical configurations.

Solar influences on dynamical coupling between the stratosphere and troposphere

We use a simplified atmospheric general circulation model (AGCM) to investigate the response of the lower atmosphere to thermal perturbations in the lower stratosphere. The results show that generic heating of the lower stratosphere tends to weaken the sub-tropical jets and the tropospheric mean meridional circulations. The positions of the jets, and the extent of the Hadley cells, respond to the distribution of the stratospheric heating, with low latitude heating displacing them poleward, and uniform heating displacing them equatorward. The patterns of response to the low latitude heating are similar to those found to be associated with solar variability in previous observational data analysis, and to the effects of varying solar UV radiation in sophisticated AGCMs. In order to investigate the chain of causality involved in converting the stratospheric thermal forcing to a tropospheric climate signal we conduct an experiment which uses an ensemble of model spin-ups to analyse the time development of the response to an applied stratospheric perturbation. We find that the initial effect of the change in static stability at the tropopause is to reduce the eddy momentum flux convergence in this region. This is followed by a vertical transfer of the momentum forcing anomaly by an anomalous mean circulation to the surface, where it is partly balanced by surface stress anomalies. The unbalanced part drives the evolution of the vertically integrated zonal flow. We conclude that solar heating of the stratosphere may produce changes in the circulation of the troposphere even without any direct forcing below the tropopause. We suggest that the impact of the stratospheric changes on wave propagation is key to the mechanisms involved.

Classifying dynamical forcing mechanisms using a climatology of extratropical cyclones

A climatology of almost 700 extratropical cyclones is compiled by applying an automated feature tracking algorithm to a database of objectively identified cyclonic features. Cyclones are classified according to the relative contributions to the midlevel vertical motion of the forcing from upper and lower levels averaged over the cyclone intensification period (average U/L ratio) and also by the horizontal separation between their upper-level trough and low-level cyclone (tilt). The frequency distribution of the average U/L ratio of the cyclones contains two significant peaks and a long tail at high U/L ratio. Although discrete categories of cyclones have not been identified, the cyclones comprising the peaks and tail have characteristics that have been shown to be consistent with the type A, B, and C cyclones of the threefold classification scheme. Using the thresholds in average U/L ratio determined from the frequency distribution, type A, B, and C cyclones account for 30\%, 38\%, and 32\% of the total number of cyclones respectively. Cyclones with small average U/L ratio are more likely to be developing cyclones (attain a relative vorticity $\ge 1.2 \times 10^{-4} \mbox{s}^{-1}$) whereas cyclones with large average U/L ratio are more likely to be nondeveloping cyclones (60\% of type A cyclones develop whereas 31\% of type C cyclones develop). Type A cyclogenesis dominates in the development region East of the Rockies and over the gulf stream, type B cyclogenesis dominates in the region off the East coast of the USA, and type C cyclogenesis is more common over the oceans in regions of weaker low-level baroclinicity.

An objective climatology of the dynamical forcing of polar lows in the Nordic seas

A new objective climatology of polar lows in the Nordic (Norwegian and Barents) seas has been derived from a database of diagnostics of objectively identified cyclones spanning the period January 2000 to April 2004. There are two distinct parts to this study: the development of the objective climatology and a characterization of the dynamical forcing of the polar lows identified. Polar lows are an intense subset of polar mesocyclones. Polar mesocyclones are distinguished from other cyclones in the database as those that occur in cold air outbreaks over the open ocean. The difference between the wet-bulb potential temperature at 700 hPa and the sea surface temperature (SST) is found to be an effective discriminator between the atmospheric conditions associated with polar lows and other cyclones in the Nordic seas. A verification study shows that the objective identification method is reliable in the Nordic seas region. After demonstrating success at identifying polar lows using the above method, the dynamical forcing of the polar lows in the Nordic seas is characterized. Diagnostics of the ratio of mid-level vertical motion attributable to quasi-geostrophic forcing from upper and lower levels (U/L ratio) are used to determine the prevalence of a recently proposed category of extratropical cyclogenesis, type C, for which latent heat release is crucial to development. Thirty-one percent of the objectively identified polar low events (36 from 115) exceeded the U/L ratio of 4.0, previously identified as a threshold for type C cyclones. There is a contrast between polar lows to the north and south of the Nordic seas. In the southern Norwegian Sea, the population of polar low events is dominated by type C cyclones. These possess strong convection and weak low-level baroclinicity. Over the Barents and northern Norwegian seas, the well-known cyclogenesis types A and B dominate. These possess stronger low-level baroclinicity and weaker convection.

Dynamical downscaling: Assessment of model system dependent retained and added variability for two different regional climate models

The Splitting of the Stratospheric Polar Vortex in the Southern Hemisphere, September 2002: Dynamical Evolution

The polar vortex of the Southern Hemisphere (SH) split dramatically during September 2002. The large-scale dynamical effects were manifest throughout the stratosphere and upper troposphere, corresponding to two distinct cyclonic centers in the upper troposphere–stratosphere system. High-resolution (T511) ECMWF analyses, supplemented by analyses from the Met Office, are used to present a detailed dynamical analysis of the event. First, the anomalous evolution of the SH polar vortex is placed in the context of the evolution that is usually witnessed during spring. Then high-resolution fields of potential vorticity (PV) from ECMWF are used to reveal several dynamical features of the split. Vortex fragments are rapidly sheared out into sheets of high (modulus) PV, which subsequently roll up into distinct synoptic-scale vortices. It is proposed that the stratospheric circulation becomes hydrodynamically unstable through a significant depth of the troposphere–stratosphere system as the polar vortex elongates.

Can the dynamical impact of the stratosphere on the troposphere be described by large-scale adjustment to the stratospheric PV distribution?

Recent numerical experiments have demonstrated that the state of the stratosphere has a dynamical impact on the state of the troposphere. To account for such an effect, a number of mechanisms have been proposed in the literature, all of which amount to a large-scale adjustment of the troposphere to potential vorticity (PV) anomalies in the stratosphere. This paper analyses whether a simple PV adjustment suffices to explain the actual dynamical response of the troposphere to the state of the stratosphere, the actual response being determined by ensembles of numerical experiments run with an atmospheric general-circulation model. For this purpose, a new PV inverter is developed. It is shown that the simple PV adjustment hypothesis is inadequate. PV anomalies in the stratosphere induce, by inversion, flow anomalies in the troposphere that do not coincide spatially with the tropospheric changes determined by the numerical experiments. Moreover, the tropospheric anomalies induced by PV inversion are on a larger scale than the changes found in the numerical experiments, which are linked to the Atlantic and Pacific storm-tracks. These findings imply that the impact of the stratospheric state on the troposphere is manifested through the impact on individual synoptic-scale systems and their self-organization in the storm-tracks. Changes in these weather systems in the troposphere are not merely synoptic-scale noise on a larger scale tropospheric response, but an integral part of the mechanism by which the state of the stratosphere impacts that of the troposphere.

Variational data assimilation for parameter estimation: application to a simple morphodynamic model

Data assimilation is a sophisticated mathematical technique for combining observational data with model predictions to produce state and parameter estimates that most accurately approximate the current and future states of the true system. The technique is commonly used in atmospheric and oceanic modelling, combining empirical observations with model predictions to produce more accurate and well-calibrated forecasts. Here, we consider a novel application within a coastal environment and describe how the method can also be used to deliver improved estimates of uncertain morphodynamic model parameters. This is achieved using a technique known as state augmentation. Earlier applications of state augmentation have typically employed the 4D-Var, Kalman filter or ensemble Kalman filter assimilation schemes. Our new method is based on a computationally inexpensive 3D-Var scheme, where the specification of the error covariance matrices is crucial for success. A simple 1D model of bed-form propagation is used to demonstrate the method. The scheme is capable of recovering near-perfect parameter values and, therefore, improves the capability of our model to predict future bathymetry. Such positive results suggest the potential for application to more complex morphodynamic models.