A Tempered Particle Filter to Enhance the Assimilation of SAR-Derived Flood Extent Maps Into Flood Forecasting Models.

Data assimilation (DA) is a powerful tool to optimally combine uncertain model simulations and observations. Among DA techniques, the particle filter (PF) has gained attention for its capacity to deal with nonlinear systems and for its relaxation of the Gaussian assumption. However, the PF may suffer from degeneracy and sample impoverishment.

Rain-Induced Stratification of the Equatorial Indian Ocean and Its Potential Feedback to the Atmosphere.

Surface freshening through precipitation can act to stably stratify the upper ocean, forming a rain layer (RL). RLs inhibit subsurface vertical mixing, isolating deeper ocean layers from the atmosphere. This process has been studied using observations and idealized simulations.

Dynamics and Predictability of Tropical Cyclone Rapid Intensification in Ensemble Simulations of Hurricane Patricia (2015).

Hurricane Patricia (2015) over the eastern Pacific was a record-breaking tropical cyclone (TC) under a very favorable environment during its rapid intensification (RI) period, which makes it an optimal real case for studying RI dynamics and predictability. In this study, we performed ensemble Kalman filter analyses at Patricia's early development stage using both traditional observations and the Office of Naval Research Tropical Cyclone Intensity (TCI) field campaign data. It is shown that assimilating the inner-core TCI observations produces a stronger initial vortex and significantly improves the prediction of RI.

A framework for causal discovery in non-intervenable systems.

Many frameworks exist to infer cause and effect relations in complex nonlinear systems, but a complete theory is lacking. A new framework is presented that is fully nonlinear, provides a complete information theoretic disentanglement of causal processes, allows for nonlinear interactions between causes, identifies the causal strength of missing or unknown processes, and can analyze systems that cannot be represented on directed acyclic graphs. The basic building blocks are information theoretic measures such as (conditional) mutual information and a new concept called certainty that monotonically increases with the information available about the target process.

A particle flow filter for high-dimensional system applications.

A novel particle filter proposed recently, the particle flow filter (PFF), avoids the long-existing weight degeneracy problem in particle filters and, therefore, has great potential to be applied in high-dimensional systems. The PFF adopts the idea of a particle flow, which sequentially pushes the particles from the prior to the posterior distribution, without changing the weight of each particle. The essence of the PFF is that it assumes the particle flow is embedded in a reproducing kernel Hilbert space, so that a practical solution for the particle flow is obtained.

Effects of mis-specified time-correlated model error in the (ensemble) Kalman Smoother.

Data assimilation is often performed under the perfect model assumption. Although there is an increasing amount of research accounting for model errors in data assimilation, the impact of an incorrect specification of the model errors on the data assimilation results has not been thoroughly assessed. We investigate the effect that an inaccurate time correlation in the model error description can have on data assimilation results, deriving analytical results using a Kalman Smoother for a one-dimensional system.

Observational Constraints on Warm Cloud Microphysical Processes Using Machine Learning and Optimization Techniques.

We introduce new parameterizations for autoconversion and accretion rates that greatly improve representation of the growth processes of warm rain. The new parameterizations capitalize on machine-learning and optimization techniques and are constrained by in situ cloud probe measurements from the recent Atmospheric Radiation Measurement Program field campaign at Azores. The uncertainty in the new estimates of autoconversion and accretion rates is about 15% and 5%, respectively, outperforming existing parameterizations.

Particle filters for high-dimensional geoscience applications: A review.

Particle filters contain the promise of fully nonlinear data assimilation. They have been applied in numerous science areas, including the geosciences, but their application to high-dimensional geoscience systems has been limited due to their inefficiency in high-dimensional systems in standard settings. However, huge progress has been made, and this limitation is disappearing fast due to recent developments in proposal densities, the use of ideas from (optimal) transportation, the use of localization and intelligent adaptive resampling strategies.

Heart rate variability categories of fluctuation amplitude and complexity: diagnostic markers of fetal development and its disturbances.

Objective: In fetal diagnosis the myriad and diversity of heart rate variability (HRV) indices prevents a comparable routine evaluation of disturbances in fetal development and well-being. The work aims at the extraction of a small set of HRV key indices that could help to establish a universal, overarching tool to screen for any disturbance.

Approach: HRV indices were organized in categories of short-term (prefix s) and long-term (prefix l) amplitude fluctuations (AMP), complexity (COMP), and patterns (PATTERN) and common representatives for each category were extracted.

Estimating model error covariances using particle filters.

A method is presented for estimating the error covariance of the errors in the model equations in observation space. Estimating model errors in this systematic way opens up the possibility to use data assimilation for systematic model improvement at the level of the model equations, which would be a huge step forward. This model error covariance is perhaps the hardest covariance matrix to estimate.

Time-correlated model error in the (ensemble) Kalman smoother.

Data assimilation is often performed in a perfect-model scenario, where only errors in initial conditions and observations are considered. Errors in model equations are increasingly being included, but typically using rather adhoc approximations with limited understanding of how these approximations affect the solution and how these approximations interfere with approximations inherent in finite-size ensembles. We provide the first systematic evaluation of the influence of approximations to model errors within a time window of weak-constraint ensemble smoothers.

An ensemble framework for time delay synchronization.

Synchronization based state estimation tries to synchronize a model with the true evolution of a system via the observations. In practice, an extra term is added to the model equations which hampers growth of instabilities transversal to the synchronization manifold. Therefore, there is a very close connection between synchronization and data assimilation.

Differences between racing and non-racing drivers: A simulator study using eye-tracking.

Motorsport has developed into a professional international competition. However, limited research is available on the perceptual and cognitive skills of racing drivers. By means of a racing simulator, we compared the driving performance of seven racing drivers with ten non-racing drivers.

An Integrated Maximum Current Density Approach for Noninvasive Detection of Myocardial Infarction.

We present a new approach of integrated maximum current density (IMCD) for the noninvasive detection of myocardial infarction (MI) using magnetocardiography (MCG) data acquired from a superconducting quantum interference device (SQUID) system. In this paper, we investigated the relationship of the maximum current density (MCD) in the current density map and the underlying equivalent current dipole (ECD) based on a novel method of reconstructing the ECD in the extremum circle of the magnetic field map. The performance of IMCD and the integrated ECD (IECD) approaches were also evaluated by using 61-channel MCG data from 39 healthy subjects and 102 patients with ST elevation myocardial infarction (STEMI).

Validation of functional fetal autonomic brain age score fABAS in 5 min short recordings.

With the objective of evaluating the functional maturation age and developmental disturbances we have previously introduced the fetal autonomic brain age score (fABAS) using 30 min fetal magnetocardiographic recordings (fMCG, Jena). The score is based on heart rate pattern indices that are related to universal principles of developmental biology. The present work aims at the validation of the fABAS methodology on 5 min recordings from an independent database (fMCG, Bochum).

Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings.

Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales.

Symbolic transformations of heart rate variability preserve information about cardiac autonomic control.

Traditional measures of heart rate variability (HRV) in the time or frequency domain (e.g. standard deviation of normal-to-normal intervals, SDNN, or the high frequency component of spectral analysis, HF) may be used to track vagal and sympathetic modulation directed to the sinus node.

Effects of visual fidelity on curve negotiation, gaze behaviour and simulator discomfort.

Unlabelled: Technological developments have led to increased visual fidelity of driving simulators. However, simplified visuals have potential advantages, such as improved experimental control, reduced simulator discomfort and increased generalisability of results. In this driving simulator study, we evaluated the effects of visual fidelity on driving performance, gaze behaviour and subjective discomfort ratings.

Strategies of symbolization in cardiovascular time series to test individual gestational development in the fetus.

The analysis of symbolic dynamics applied to physiological time series retrieves dynamical properties of the underlying regulation which are robust against the symbolic transformation. In this study, three different transformations to produce a symbolic series were applied to fetal RR interval series to test whether they reflect individual changes of fetal heart rate variability in the course of pregnancy. Each transformation was applied to 215 heartbeat datasets obtained from 11 fetuses during the second and the third trimester of pregnancy (at least 10 datasets per fetus, median 17).

Aerobic exercise during pregnancy and presence of fetal-maternal heart rate synchronization.

Unlabelled: It has been shown that short-term direct interaction between maternal and fetal heart rates may take place and that this interaction is affected by the rate of maternal respiration. The aim of this study was to determine the effect of maternal aerobic exercise during pregnancy on the occurrence of fetal-maternal heart rate synchronization.

Methods: In 40 pregnant women at the 36th week of gestation, 21 of whom exercised regularly, we acquired 18 min.

Fetal electrocardiographic measurements in the assessment of fetal heart rate variability in the antepartum period.

This study examines signal availability in fetal electrocardiogram (FECG) beat-to-beat acquisition and the accuracy of fetal heart rate variability (HRV) analysis in the clinical setting using a commercially available FECG monitor. Signal availability was examined in 130 FECG recordings of 0.3-17.

Obstacle avoidance, visual detection performance, and eye-scanning behavior of glaucoma patients in a driving simulator: a preliminary study.

The objective of this study was to evaluate differences in driving performance, visual detection performance, and eye-scanning behavior between glaucoma patients and control participants without glaucoma. Glaucoma patients (n = 23) and control participants (n = 12) completed four 5-min driving sessions in a simulator. The participants were instructed to maintain the car in the right lane of a two-lane highway while their speed was automatically maintained at 100 km/h.

Different approaches of symbolic dynamics to quantify heart rate complexity.

The analysis of symbolic dynamics applied to physiological time series is able to retrieve information about dynamical properties of the underlying system that cannot be gained with standard methods like e.g. spectral analysis.

Symbolic patterns of heart rate dynamics reflect cardiac autonomic changes during childhood and adolescence.

Symbolic dynamics derived from heart rate variability (HRV) is able to reflect changes of cardiac autonomic modulations in healthy subjects. It has been shown that linear measures of HRV in children and adolescents monotonically increase or decrease (depending on the measure) with age whereas non-linear measures show a local extreme value at the age of 7 to 9 years. In this study, the age-related variations of dynamical features of the R-R interval series during childhood and adolescence were addressed.