Force Noise Research Articles

Process, Forcing, and Signal Analysis of Global Mean TemperatureVariations by Means of a Three-Box Energy Balance Model

An analytic solution of an energy balance model (EBM) is presented which can beused as a recursive filter for time series analysis. It is shown that the EBM can reproduce the solution of a coupled atmosphere-ocean general circulation model (AOGCM) experiment. Contrary to the AOGCM, the EBM easily allows for variations in climate sensitivity to satisfy the full range of uncertainty concerned with this parameter. The recursive filter is applied to two natural and two anthropogenic forcing mechanisms which are expressed in terms of heating rate anomaly time series: volcanism, solar activity, greenhouse gases (GHG), and anthropogenic tropospheric aerosols. Thus, we obtain modelled global mean temperature variations as a response to the different forcings and with respect to the uncertainty in the forcing approximations and climate sensitivity. In addition, it is shown that the observed (ENSO-corrected) global mean temperature time series within the period from 1866 to 1997 can be explained by the external forcings which have been considered and an additional white noise forcing. In this way we are able to separate different signals and compare them. As a result, global anthropogenic climate change due to GHG forcing can be detected at a high level of significance without considering spatial patterns of climate change but including natural forcing, which is usually not done. Furthermore, it is shown that solar forcing alone does not lead to significantclimate change, whereas solar and volcanic forcing together lead to a significant natural climate change signal. Anthropogenic climate change due to GHG forcing may partly be masked by anthropogenic aerosol cooling.

The Timescale, Power Spectra, and Climate Noise Properties of Teleconnection Patterns

This study uses NCEP–NCAR reanalysis data covering the boreal winters of 1958–97 to examine the power spectral, timescale, and climate noise properties of the dominant atmospheric teleconnection patterns. The patterns examined include the North Atlantic oscillation (NAO), the Pacific–North American (PNA), and west Pacific (WP) teleconnections, and a spatial pattern associated with ENSO. The teleconnection patterns are identified by applying a rotated principal component analysis to the daily unfiltered 300-mb geopotential height field. The NAO and PNA were found to be the two dominant patterns on all timescales. The main finding is that the temporal evolution of the NAO, PNA, and WP teleconnections can be interpreted as being a stochastic (Markov) process with an e-folding timescale between 7.4 and 9.5 days. The time series corresponding to the ENSO spatial pattern did not match that of a Markov process, and thus a well-defined timescale could not be specified. The shortness of the above timescales indicates that the excitation of these teleconnection patterns is limited to a period of time less than a few days. These findings also suggest that in order to improve our understanding of the growth and decay mechanisms of teleconnection patterns, it is best to use daily, unfiltered data, rather than monthly or seasonally averaged data. The signal (interannual variance due to external forcing) to noise (interannual variance from stochastic processes) ratios were also examined. For the NAO (PNA), the signal-to-noise ratio is 0.09 (1.11). This indicates that the interannual variability of the NAO (PNA) arises primarily from climate noise (both from climate noise and external forcing). An explanation for why the NAO and PNA dominate on interannual timescales is also presented.

The response of an ENSO Model to climate noise, weather noise and intraseasonal forcing

The response of an intermediate coupled model of the tropical Pacific to different forms of stochastic wind forcing is studied. An estimate of observed Pacific wind variance that is unrelated to Pacific sea surface temperature (SST) has a red spectrum, inconsistent with standard definitions of “weather noise”. The reddening is likely due to SST outside the basin; we propose a definition of “climate noise” for such reddened variance. Effects are compared for (i) red climate noise; (ii) the corresponding white weather noise estimate; (iii) intraseasonal and interannual components of the white noise (to test frequency response); and (iv) a noise product with extra power in the 30–60 day range. Power is not effectively channeled from subannual frequencies to the frequencies associated with ENSO in this model. This suggests that ENSO impacts of the Madden‐Julian oscillation are largely restricted to the low‐frequency tail rather than the 30–60 day spectral peak. Interannual climate noise originating outside the tropical Pacific appears important.

CHAOS AND PHASE SYNCHRONIZATION IN ECOLOGICAL SYSTEMS

An ecological population model is presented for the purposes of exploring complex synchronization phenomena in biological systems. The model describes a three level predator–prey–resource system which oscillates with Uniform Phase evolution, yet has Chaotic Abundance levels or Amplitudes (UPCA). We investigate the phase synchronization of two nonidentical diffusively coupled phase coherent models (i.e. with UPCA dynamics) and extend the analysis to study the models' "funnel" regimes and response to noise forcing. Similar synchronization effects are reported for a two-dimensional lattice of chaotic population models coupled via nearest neighbors. With weak coupling, a collective phase synchronization emerges yet the peak population abundance levels are chaotic and largely uncorrelated. The synchronization patterns and traveling wave structures found in the spatial model correspond to those observed in natural systems — in particular, Ecology's well-known Canadian hare–lynx cycle. We show that phase synchronization has important applications in the study of ecological communities where the spatial coupling of populations can lead to large scale complex synchronization effects.

On decadal-scale ocean-atmosphere interactions in the extended ECHAM1/LSG climate simulation

The last 810 years of a control integration with the ECHAM1/LSG coupled model are used to clarify the nature of the ocean-atmosphere interactions at low frequencies in the North Atlantic and the North Pacific. To a first approximation, the atmosphere acts as a white noise forcing and the ocean responds as a passive integrator. The sea surface temperature (SST) variability primarily results from short time scale fluctuations in surface heat exchanges and Ekman currents, and the former also damp the SST anomalies after they are generated. The thermocline variability is primarily driven by Ekman pumping. Because the heat, momentum, and vorticity fluxes at the sea surface are correlated in space and time, the SST variability is directly linked to that in the ocean interior. The SST is also modulated by the wind-driven geostrophic fluctuations, resulting in persistent correlation with the thermocline changes and a slight low-frequency redness of the SST spectra. The main dynamics are similar in the two oceans, although in the North Pacific the SST variability is more strongly influenced by advection changes and the oceanic time scales are larger. A maximum covariance analysis based on singular value decomposition in lead and lag conditions indicates that some of the main modes of atmospheric variability in the two oceans are sustained by a very weak positive feedback between the atmosphere, SST, and the strength of the subtropical and subpolar gyres. In addition, in the North Atlantic the main surface pressure mode has a small quasi-oscillatory component at 6-year period, and advective resonance occurs for SST around 10-year period, both periods being also singled out by multichannel singular spectrum analysis. The ocean-atmosphere coupling is however much too weak to redden the tropospheric spectra or create anything more than tiny spectral peaks, so that the atmospheric and oceanic variability is dominated in both ocean sectors by the one-way interactions.

Longtime Behaviour of Stochastic Hamiltonian Systems: The Multidimensional Case

Hamiltonian systems perturbed by a white noise force are discussed in several dimensions. By using an appropriate scaling of the stochastic force a convergence theorem for the invariants of the deterministic motion is proved. This corresponds to convergence of the system to a stationary distribution. Especially motion in a central force field is considered; the energy and angular momentum processes are investigated.

TURBULENT COLD PLASMA: AN EXACTLY PATH INTEGRAL SOLUTION IN A ZERO DIMENSIONAL MODEL AND ITS GENERALIZATIONS TO THE THREE-DIMENSIONAL-CASE

We write path integrals exact solutions for a 0-dimensional noise (turbulent) force equation for an electronic plasma. We obtain that the equilibrium limit of the plasma tensor magneto conductivity coincides with the classical non-turbulent result in our 0-dimensional proposed model. Additionally, we show the usefulness of our reduced model by writing exact path integrals solutions for the probabilistic turbulent plasma occupation times. Finally, we point out three-dimensional generalizations of our path integral studies in two appendix.

Stochastic Forcing of ENSO by the Intraseasonal Oscillation

Using the ideas of generalized linear stability theory, the authors examine the potential role that tropical variability on synoptic–intraseasonal timescales can play in controlling variability on seasonal–interannual timescales. These ideas are investigated using an intermediate coupled ocean–atmosphere model of the El Niño–Southern Oscillation (ENSO). The variability on synoptic–intraseasonal timescales is treated as stochastic noise that acts as a forcing function for variability at ENSO timescales. The spatial structure is computed that the stochastic noise forcing must have in order to enhance the variability of the system on seasonal–interannual timescales. These structures are the so-called stochastic optimals of the coupled system, and they bear a good resemblence to variability that is observed in the real atmosphere on synoptic and intraseasonal timescales. When the coupled model is subjected to a stochastic noise forcing composed of the stochastic optimals, variability on seasonal–interannual timescales develops that has spectral characteristics qualitatively similar to those seen in nature. The stochastic noise forcing produces perturbations in the system that can grow rapidly. The response of the system to the stochastic optimals is to induce perturbations that bear a strong resemblence to westerly and easterly wind bursts frequently observed in the western tropical Pacific. In the model, these “wind bursts” can act as efficient precursors for ENSO episodes if conditions are favorable. The response of the system to noise-induced perturbations depends on a number of factors that include 1) the phase of the seasonal cycle, 2) the presence of nonlinearities in the system, 3) the past history of the stochastic noise forcing and its integrated effect, and 4) the stability of the coupled ocean–atmosphere system. Based on their findings, they concur with the view adopted by other investigators that ENSO may be explained, at least partially, as a stochastically forced phenomena, the source of the noise in the Tropics being synoptic–intraseasonal variability, which includes the Madden–Julian oscillation, and westerly/easterly wind bursts. These ideas fit well with the observed onset and development of various ENSO episodes, including the 1997–98 El Niño event.

Stochastic Dynamics of El Niño–Southern Oscillation*

A stochastically forced nonlinear dynamic model for El Nino-Southern Oscillation is advanced to explore the nature of the highly irregular ENSO cycle. The model physics includes nonlinear dynamics of the coupled ocean-atmosphere system, high-frequency stochastic forcing, and the annual forcing of a prescribed climato- logical basic state. The model irregular ENSO-like oscillation arises from three different origins: stochastic resonance, coupled nonlinear instability, and stochastic transition. When the basic state is stable, the stochastic forcing excites irregular oscillations by stochastic resonance. When the system is unstable and the coupled dynamics sustains a nonlinear oscillation (stable limit cycle), the stochastic forcing perturbs the deterministic trajectory of the limit cycle in the phase space, generating irregularities and modifying the oscillation period. When the system possesses multiequilibrium states, the stochastic forcing may render the system oscillatory by randomly switching the system between a warm and a cold stable steady state. The stochastic response depends not only on the nonlinear dynamic regimes of the ENSO system but also on the temporal structure (spectrum) and strength of the stochastic forcing. White and red noises are shown to be much more effective than band-limited white noises in stochastic resonance and in altering the characteristics of the nonlinear oscillation. The intraseasonal noise can alter the dominant period of intrinsic nonlinear oscillation, favoring biennial oscillation, especially when the intraseasonal forcing is modulated by the monsoon (annual) cycle. Stronger forcing yields an enhanced resonant oscillation with a prolonged period. A sufficiently strong white noise forcing, however, can destroy the nonlinear or resonant oscillation, leading to a Markovian process. The basic-state annual variation tends to enhance the resonant oscillation but reduces the oscillation period considerably in the marginally stable regime. The model results suggest that ENSO may arise from multimechanisms. The different mechanisms may be at work in various phases of the ENSO evolution, depending on the basic state and the nonlinear dynamics of the system. The monsoon may affect ENSO through modulation of intraseasonal stochastic forcing, enhancing the biennial component of ENSO.

A Dynamic Ocean–Atmosphere Model of the Tropical Atlantic Decadal Variability

Abstract A linear model that couples an ocean mixed layer with a simple dynamic atmosphere is used to study the mechanism for decadal variability over the tropical Atlantic. An unstable mode with a dipole sea surface temperature (SST) pattern similar to observed decadal variability in the tropical Atlantic emerges in the time integration of the model. A wind–evaporation–SST feedback is responsible for the growth and oscillation of the unstable mode whereas the mean state of the Atlantic climate is essential for maintaining the spatially quasi-standing dipole structure. The oscillation period ranges from several to a few tens of years and is sensitive to coupling strength. The oscillation is not self-sustainable as the realistic damping rate exceeds the growth rate. In response to white noise forcing, the model produces a red SST spectrum without a peak at finite frequencies. Therefore it is suggested that the tropical dipole’s preferred timescales, if any, arise from the forcing by or interaction with the extratropics. In a model run where the forcing is confined to the extratropics, a dipole SST pattern still dominates the forcing-free Tropics, in support of the proposed linkage between the Tropics and extratropics.

Decadal Variability in ENSO Predictability and Prediction

A simple coupled model is used to examine decadal variations in El Niño–Southern Oscillation (ENSO) prediction skill and predictability. Without any external forcing, the coupled model produces regular ENSO-like variability with a 5-yr period. Superimposed on the 5-yr oscillation is a relatively weak decadal amplitude modulation with a 20-yr period. External uncoupled atmospheric “weather noise” that is determined from observations is introduced into the coupled model. Including the weather noise leads to irregularity in the ENSO events, shifts the dominant period to 4 yr, and amplifies the decadal signal. The decadal signal results without any external prescribed changes to the mean climate of the model. Using the coupled simulation with weather noise as initial conditions and for verification, a large ensemble of prediction experiments were made. The forecast skill and predictability were examined and shown to have a strong decadal dependence. During decades when the amplitude of the interannual variability is large, the forecast skill is relatively high and the limit of predictability is relatively long. Conversely, during decades when the amplitude of the interannual variability is low, the forecast skill is relatively low and the limit of predictability is relatively short. During decades when the predictability is high, the delayed oscillator mechanism drives the sea surface temperature anomaly (SSTA), and during decades when the predictability is low, the atmospheric noise strongly influences the SSTA. Additional experiments indicate that the relative effectiveness of the delayed oscillator mechanism versus the external noise forcing in determining interannual SSTA variability is strongly influenced by much slower timescale (decadal) variations in the state of the coupled model.

Vibroacoustical modeling and modal analysis of a double wall panel

In this paper results are reported of analytical and experimental vibroacoustical modal analysis of a double wall panel. Both mechanical vibrations of panel walls as well as the modal behavior of acoustical field in cavity were identified. Special interest was focused on identification and modeling of interaction and coupling between vibratory behavior of the walls and acoustical field in the cavity and their influence on drop of the transmission loss of the panel, as measured in the laboratory. The identification was carried out using a set of combined vibratory and acoustical frequency response functions measurements as response due to random noise force and controlled volume velocity source. The identified global complex modes of the panel and an estimated model of the panel employing general parameters were of high quality. It was confirmed by very good orthogonality of the identified vibratory and acoustical mode shapes and high correlation values between the measured and synthesized frequency response functions. This result provides a robust basis for the numerical study of the transmission behavior of the panel in the low-frequency range. Application of this result on optimum placement of force actuators to increase of transmission loss over a lower-frequency range by means of active noise and vibration control will be presented.

Ergodic results for stochastic navier-stokes equation

In this paper we deal with the 2-D Navier-Stokes equation perturbed by a white noise force. Uniqueness of the invariant measure for this stochastic equation is obtained in a simpler way than in [6], proving that the two main properties of the Markov semigroup associated with this equation, i.e. irreducibility and strong Feller property, hold in the same space. Moreover, the assumptions on the noise are more general than in [6]

Measurement of inherent particle properties by dynamic light scattering: introducing electrorotational light scattering

Common dynamic light scattering (DLS) methods determine the size and zeta-potential of particles by analyzing the motion resulting from thermal noise or electrophoretic force. Dielectric particle spectroscopy by common microscopic electrorotation (ER) measures the frequency dependence of field-induced rotation of single particles to analyze their inherent dielectric structure. We propose a new technique, electrorotational light scattering (ERLS). It measures ER in a particle ensemble by a homodyne DLS setup. ER-induced particle rotation is extracted from the initial decorrelation of the intensity autocorrelation function (ACF) by a simple optical particle model. Human red blood cells were used as test particles, and changes of the characteristic frequency of membrane dispersion induced by the ionophore nystatin were monitored by ERLS. For untreated control cells, a rotation frequency of 2 s-1 was induced at the membrane peak frequency of 150 kHz and a field strength of 12 kV/m. This rotation led to a decorrelation of the ACF about 10 times steeper than that of the field free control. For deduction of ERLS frequency spectra, different criteria are discussed. Particle shape and additional field-induced motions like dielectrophoresis and particle-particle attraction do not significantly influence the criteria. For nystatin-treated cells, recalculation of dielectric cell properties revealed an ionophore-induced decrease in the internal conductivity. Although the absolute rotation speed and the rotation sense are not yet directly accessible, ERLS eliminates the tedious microscopic measurements. It offers computerized, statistically significant measurements of dielectric particle properties that are especially suitable for nonbiological applications, e.g., the study of colloidal particles.

Asymmetric motion in a double well under the action of zero-mean Gaussian white noise and periodic forcing

Residence times of a particle in both the wells of a double-well system, under the action of zero-mean Gaussian white noise and zero-averaged but temporally asymmetric periodic forcings, are recorded in a numerical simulation. The difference between the relative mean residence times in the two wells shows monotonic variation as a function of asymmetry in the periodic forcing and for a given asymmetry the difference becomes largest at an optimum value of the noise strength. Moreover, the passages from one well to the other become less synchronous at small noise strength as the asymmetry parameter (defined below) differs from zero, but at relatively larger noise strengths the passages become more synchronous with asymmetry in the field sweep. We propose that asymmetric periodic forcing (with zero mean) could provide a simple but sensible physical model for unidirectional motion in a symmetric periodic system aided by a symmetric Gaussian white noise.

Transience of stochastically perturbed classical hamiltonian systems and random wave operators

A classical Hamiltonian system perturbed by a white noise force is considered. Under suitable smallness assumptions on the deterministic force transience of the solution process is proven in all dimensions. The existence of random wave operators (almost surely with respect to Wiener measure) is proven for potentials which decrease at infinity. A remark on recurrence in one dimension when the force grows stronger than linearly at infinity is also given.

Optical corpuscular theory of semiconductor laser intensity noise and intensity squeezed-light generation

Fluctuations of the stored energy and the emitted power of a semiconductor laser are derived by classical corpuscular optical theory. The fundamental noise sources are the shot noise associated with a field’s conversion to emitting or absorbing atoms and the mirror loss noise. The latter is taken into account in the form of partition noise forces linked to laser facet reflection. The theory permits the description of the nonclassical states of light, and its results agree with quantum theory. For quiet pumping conditions and for a high-reflection coated Fabry–Perot laser, 50% of internal photon noise suppression is obtained, whereas nonfluctuating optical output is possible for negligible internal loss. The influence of gain suppression on amplitude squeezing is discussed. The effect of attenuation on the propagation of laser fluctuations is studied by use of the concept of optical partition noise. This leads to the invariance of a suitably defined relative intensity noise, which becomes negative for sub-Poissonian photon statistics. The setup for the intensity noise measurement with the balanced detection technique is analyzed by use of optical partition noise.

Stress response of Barkhausen noise and coercive force in 9Ni steel : 37494 Rautioaho, R.; Karjalainen, P.; Moilanen, M. Journal of Magnetism and Magnetic Materials, Vol. 68, No. 3, pp. 321–327 (Sep. 1987)

Stress response of Barkhausen noise and coercive force in 9Ni steel : 37494 Rautioaho, R.; Karjalainen, P.; Moilanen, M. Journal of Magnetism and Magnetic Materials, Vol. 68, No. 3, pp. 321–327 (Sep. 1987)

Comment on “Climate Drift in a Global Ocean General Circulation Model”

Abstract In a recent study it was found that the GFDL modular ocean model showed a small drift and very little variability when stochastically forced under mixed boundary conditions. This is in contrast to earlier studies that found very strong variability in a similar experiment with the Hamburg LSG ocean model. A number of possible reasons for such contrasting results, one of which is that the behavior of the two models is fundamentally different, have been discussed. In this comment, it is suggested that the main reason may be that the magnitude of the noise forcing used in the GFDL model was lower than that used in the Hamburg model.

Giant suppression of the activation rate in the presence of correlated white noise sources

We have studied the effect of two simultaneous correlated white noises, one additive and the other multiplicative, on the activation rate of a bistable system. It is proved that as a function of the (positive-valued) correlation strength between the two noise sources the activation rate can be suppressed by orders of magnitude (likewise, with a negative-valued correlation strength it can be enhanced). Hence, the correlation between the two noises provides a tool for a controlled slow-down (speed-up) of fast (slow) reactions by adding an appropriately chosen additional correlated noise force.