45 research outputs found
Effects of vertical shear in modelling horizontal oceanic dispersion
Abstract. The effect of vertical shear on the horizontal dispersion properties of passive tracer particles on the continental shelf of the South Mediterranean is investigated by means of observation and model data. In situ current measurements reveal that vertical gradients of horizontal velocities in the upper mixing layer decorrelate quite fast ( ∼  1 day), whereas an eddy-permitting ocean model, such as the Mediterranean Forecasting System, tends to overestimate such decorrelation time because of finite resolution effects. Horizontal dispersion, simulated by the Mediterranean sea Forecasting System, is mostly affected by: (1) unresolved scale motions, and mesoscale motions that are largely smoothed out at scales close to the grid spacing; (2) poorly resolved time variability in the profiles of the horizontal velocities in the upper layer. For the case study we have analysed, we show that a suitable use of deterministic kinematic parametrizations is helpful to implement realistic statistical features of tracer dispersion in two and three dimensions. The approach here suggested provides a functional tool to control the horizontal spreading of small organisms or substance concentrations, and is thus relevant for marine biology, pollutant dispersion as well as oil spill applications
Entropy of the Nordic electricity market: anomalous scaling, spikes, and mean-reversion
The electricity market is a very peculiar market due to the large variety of
phenomena that can affect the spot price. However, this market still shows many
typical features of other speculative (commodity) markets like, for instance,
data clustering and mean reversion. We apply the diffusion entropy analysis
(DEA) to the Nordic spot electricity market (Nord Pool). We study the waiting
time statistics between consecutive spot price spikes and find it to show
anomalous scaling characterized by a decaying power-law. The exponent observed
in data follows a quite robust relationship with the one implied by the DEA
analysis. We also in terms of the DEA revisit topics like clustering,
mean-reversion and periodicities. We finally propose a GARCH inspired model but
for the price itself. Models in the context of stochastic volatility processes
appear under this scope to have a feasible description.Comment: 16 pages, 7 figure
Extreme times for volatility processes
We present a detailed study on the mean first-passage time of volatility
processes. We analyze the theoretical expressions based on the most common
stochastic volatility models along with empirical results extracted from daily
data of major financial indices. We find in all these data sets a very similar
behavior that is far from being that of a simple Wiener process. It seems
necessary to include a framework like the one provided by stochastic volatility
models with a reverting force driving volatility toward its normal level to
take into account memory and clustering effects in volatility dynamics. We also
detect in data a very different behavior in the mean first-passage time
depending whether the level is higher or lower than the normal level of
volatility. For this reason, we discuss asymptotic approximations and confront
them to empirical results with a good agreement, specially with the ExpOU
model.Comment: 10, 6 colored figure
Memory beyond memory in heart beating: an efficient way to detect pathological conditions
We study the long-range correlations of heartbeat fluctuations with the
method of diffusion entropy. We show that this method of analysis yields a
scaling parameter that apparently conflicts with the direct evaluation
of the distribution of times of sojourn in states with a given heartbeat
frequency. The strength of the memory responsible for this discrepancy is given
by a parameter , which is derived from real data. The
distribution of patients in the (, )-plane yields a neat
separation of the healthy from the congestive heart failure subjects.Comment: submitted to Physical Review Letters, 5 figure
Towards the Thermodynamics of Localization Processes
We study the entropy time evolution of a quantum mechanical model, which is
frequently used as a prototype for Anderson's localization. Recently Latora and
Baranger [V. Latora, M. Baranger, Phys. Rev.Lett. 82, 520(1999)] found that
there exist three entropy regimes, a transient regime of passage from dynamics
to thermodynamics, a linear in time regime of entropy increase, namely a
thermodynamic regime of Kolmogorov kind, and a saturation regime. We use the
non-extensive entropic indicator recently advocated by Tsallis [ C. Tsallis, J.
Stat. Phys. 52, 479 (1988)] with a mobile entropic index q, and we find that
with the adoption of the ``magic'' value q = Q = 1/2 the Kolmogorov regime
becomes more extended and more distinct than with the traditional entropic
index q = 1. We adopt a two-site model to explain these properties by means of
an analytical treatment and we argue that Q =1/2 might be a typical signature
of the occurrence of Anderson's localization.Comment: 13 pages, 8 figures submitted to Phys. Rev.
Properties making a chaotic system a good Pseudo Random Number Generator
We discuss two properties making a deterministic algorithm suitable to
generate a pseudo random sequence of numbers: high value of Kolmogorov-Sinai
entropy and high-dimensionality. We propose the multi dimensional Anosov
symplectic (cat) map as a Pseudo Random Number Generator. We show what chaotic
features of this map are useful for generating Pseudo Random Numbers and
investigate numerically which of them survive in the discrete version of the
map. Testing and comparisons with other generators are performed.Comment: 10 pages, 3 figures, new version, title changed and minor correction
Renewal processes and fluctuation analysis of molecular motor stepping
We model the dynamics of a processive or rotary molecular motor using a
renewal processes, in line with the work initiated by Svoboda, Mitra and Block.
We apply a functional technique to compute different types of multiple-time
correlation functions of the renewal process, which have applications to
bead-assay experiments performed both with processive molecular motors, such as
myosin V and kinesin, and rotary motors, such as F1-ATPase
Boltzmann entropy and chaos in a large assembly of weakly interacting systems
We introduce a high dimensional symplectic map, modeling a large system
consisting of weakly interacting chaotic subsystems, as a toy model to analyze
the interplay between single-particle chaotic dynamics and particles
interactions in thermodynamic systems. We study the growth with time of the
Boltzmann entropy, S_B, in this system as a function of the coarse graining
resolution. We show that a characteristic scale emerges, and that the behavior
of S_B vs t, at variance with the Gibbs entropy, does not depend on the coarse
graining resolution, as far as it is finer than this scale. The interaction
among particles is crucial to achieve this result, while the rate of entropy
growth depends essentially on the single-particle chaotic dynamics (for t not
too small). It is possible to interpret the basic features of the dynamics in
terms of a suitable Markov approximation.Comment: 21 pages, 11 figures, submitted to Journal of Statistical Physic
Effects of vertical shear in modelling horizontal oceanic dispersion
The effect of vertical shear on the horizontal dispersion properties
of passive tracer particles on the continental shelf of the South
Mediterranean is investigated by means of observation and model data.
In situ current measurements reveal that vertical gradients of
horizontal velocities in the upper mixing layer decorrelate quite fast
( ∼  1 day), whereas an eddy-permitting ocean model, such as
the Mediterranean Forecasting System, tends to overestimate such
decorrelation time because of finite resolution effects. Horizontal
dispersion, simulated by the Mediterranean sea Forecasting System, is
mostly affected by: (1) unresolved scale motions, and mesoscale motions
that are largely smoothed out at scales close to the grid spacing; (2)
poorly resolved time variability in the profiles of the horizontal
velocities in the upper layer. For the case study we have analysed, we
show that a suitable use of deterministic kinematic parametrizations
is helpful to implement realistic statistical features of tracer
dispersion in two and three dimensions. The approach here suggested
provides a functional tool to control the horizontal spreading of
small organisms or substance concentrations, and is thus relevant for
marine biology, pollutant dispersion as well as oil spill
applications
Seascape connectivity of European anchovy in the Central Mediterranean Sea revealed by weighted Lagrangian backtracking and bio-energetic modelling
Ecological connectivity is one of the most important processes that shape marine populations and ecosystems, determining their distribution, persistence, and productivity. Here we use the synergy of Lagrangian back-trajectories, otolith-derived ages of larvae, and satellite-based chlorophyll-a to identify spawning areas of European anchovy from ichthyoplanktonic data, collected in the Strait of Sicily (Central Mediterranean Sea), i.e., the crucial channel in between the European and African continents. We obtain new evidence of ecosystem connectivity between North Africa and recruitment regions off the southern European coasts. We assess this result by using bio-energetic modeling, which predicts species-specific responses to environmental changes by producing quantitative information on functional traits. Our work gives support to a collaborative and harmonized use of Geographical Sub-Areas, currently identified by the General Fisheries Commission for the Mediterranean. It also confirms the need to incorporate climate and environmental variability effects into future marine resources management plans, strategies, and directives