Generation Of Extreme Events Research Articles

Cavity soliton inhibition of extreme events in lasers with injection.

Vortex mediated turbulence can be the key element in the generation of extreme events in spatially extended lasers with optical injection. Here, we study the interplay of vortex mediated turbulence and cavity solitons on the onset of extreme events in semiconductor lasers with injection. We first analyze and characterize these two features separately, spatiotemporal chaotic optical vortices for low values of the injection intensity and cavity solitons above the locking regime. In regimes where vortex mediated turbulence and cavity solitons coexist, localized peaks of light inhibit instead of enhancing the generation of rogue waves by locally regularizing the otherwise chaotic phase of the optical field. Cavity solitons can then be used to manipulate and control extreme events in systems displaying vortex mediated turbulence.

A Probabilistic Multi-Source Remote Sensing Approach to Evaluate Extreme Precursory Drought Conditions of a Wildfire Event in Central Chile

Forest fires are a major issue worldwide, and especially in Mediterranean ecosystems where the frequency, extension and severity of wildfire events have increased related to longer and more intense droughts. Open access remote sensing and climate datasets make it possible to describe in detail the precursory environmental conditions triggering major fire events under drought conditions. In this study, a probabilistic methodological approach is proposed and tested to evaluate extreme drought conditions prior to the occurrence of a wildfire in Central Chile, an area suffering an unprecedented prolonged drought. Using 21 years of monthly records of gridded climate and remotely sensed vegetation water status data, we detected that vegetation at the ground level, by means of fine and dead fuel moisture (FDFM), and canopy level, by means of the enhanced vegetation index (EVI) were extremely dry for a period of about 8 months prior to the fire event, showing records that fall into the 2.5% of the lowest values recorded in 21 years. These extremely dry conditions of the vegetation, consequence of low air humidity and precipitation, favored the ignition and horizontal and vertical propagation of this major wildfire. Post fire, we found high severity values for the native vegetation affected by the fire, with dNBR values >0.44 3 days after the fire and significant damage to the Mediterranean sclerophyllous and deciduous forest present in the burned area. The proposed probabilistic model is presented as an innovation and an alternative to evaluate not only anomalies of the meteorological and vegetation indices that promote the generation of extreme events, but also how unusual or extreme these conditions are. This is achieved by placing the abnormal values in the context of the reference historical frequency distribution of all available records, in this case, more than 20 years of remote sensing and climate data. This methodology can be widely applied by fire researchers to identify critical precursory fire conditions in different ecosystems and define environmental indicators of fire risk.

Statistical properties of Er/Yb co-doped random Rayleigh feedback fiber laser

In this Letter, we experimentally investigate fast temporal intensity dynamics and statistical properties of the cladding-pumped Er/Yb co-doped random Rayleigh feedback fiber laser (EYRFL) for the first time, to the best of our knowledge. By using the optical spectral filtering method, strong and fast intensity fluctuations with the generation of extreme events are revealed at the output of EYRFL. The statistics of the intensity fluctuations strongly depends on the wavelength of the filtered radiation, and the intensity probability density function (PDF) with a heavy tail is observed in the far wings of the spectrum. We also find that the PDF of the intensity in the central part of the spectrum deviates from the exponential distribution and has the dependence on the laser operating regimes, which indicates some correlations among different frequency components exist in the EYRFL radiation and may play an important role in the random lasing spectrum stabilization process.

Advent of extreme events in predator populations

We study the dynamics of a ring of patches with vegetation–prey–predator populations, coupled through interactions of the Lotka–Volterra type. We find that the system yields aperiodic, recurrent and rare explosive bursts of predator density in a few isolated spatial patches from time to time. Further, the global predator biomass also exhibits sudden uncorrelated occurrences of large deviations from the mean as the coupled system evolves. The maximum value of the predator population in a patch, as well as the maximum value of the predator biomass, increases with coupling strength. These trends are further corroborated by fits to Generalized Extreme Value distributions, where the location and scale factor of the distribution increases markedly with coupling strength, indicating the crucial role of coupling interactions in the generation of extreme events. These results indicate how occurrences of extremely large predator populations can emerge in coupled population dynamics, and in a more general context they suggest a generic class of deterministic nonlinear systems that can naturally exhibit extreme events

Statistical Phase Transitions and Extreme Events in Shallow Water Waves with an Abrupt Depth Change

Predicting extreme events in complex nonlinear systems is an extremely challenging and important area in climate science. Important examples include extreme events near coastal continental shelves for shallow and deep water waves. Recent laboratory experiments reveal a remarkable transition from near Gaussian to highly skewed anomalous statistics with extreme events by measuring the surface water wave displacements in shallow water across an abrupt depth change (ADC). A statistical dynamical model has been proposed and used to accurately predict the representative statistical transition using Gibbs invariant measures for the truncated KdV equation at low and high inverse temperatures representing flows before and after the ADC. In this paper, we use much lower dimensional truncated paradigm models to understand the statistical phase transition and the creation of extreme events. Especially, a two-mode interacting model with exact integrable dynamics is adopted to characterize the core transition mechanism as the model parameter varies. The choice of the radically truncated two-mode model is motivated by the self-similar solution structures with reducing numbers of truncated modes. A clear separation of distinct dynamics in the phase space is discovered for the Gibbs ensembles sampled from different inverse temperatures. Direct numerical tests with various model truncation sizes are presented to illustrate the statistical transition in parameter regimes. The analysis here can also provide a theoretical guideline for a wider variety of models concerning the generation of extreme events and anomalous statistics.

Asymptotics for the long-time evolution of kurtosis of narrow-band ocean waves

In this paper we highlight that extreme events such as freak waves are a transient phenomenon in keeping with the old fisherman tale that these extreme events seem to appear out of nowhere. Janssen (J. Phys. Oceanogr., vol. 33, 2003, pp. 863–884) obtained an evolution equation for the ensemble average of the excess kurtosis, which is a measure for the deviation from normality and an indicator for nonlinear focusing resulting in extreme events. In the limit of a narrow-band wave train, whose dynamics is governed by the two-dimensional nonlinear Schrödinger (NLS) equation, the excess kurtosis is under certain conditions seen to grow to a maximum after which it decays to zero for large times. This follows from a numerical solution of the problem and also from an analytical solution presented by Fedele (J. Fluid Mech., vol. 782, 2015, pp. 25–36). The analytical solution is not explicit because it involves an integral from initial time to actual time. We therefore study a number of properties of the integral expression in order to better understand some interesting features of the time-dependent excess kurtosis and the generation of extreme events.

Extreme optical fluctuations in lumped Raman fibre amplifiers

A numerical study on the generation of extreme events in lumped Raman fibre amplifiers is performed. The evolution of continuous or pulsed signals is analysed using cross-correlations, spectra and probability density functions. For pulsed signals, the phase evolution is also explored. Both signal and Stokes cascaded waves are considered.

MV-WG: a new multi-variable weather generator

This paper presents a new stochastic multi-variable weather generator (MV-WG) and compares its performance with LARS-WG version 4.0. Daily data of 109 meteorological stations from a North American database were used in a twofold comparison of the two generators: (1) the capability of reproducing the mean and variance of annual, seasonal and monthly values, and (2) the capability of reproducing extreme weather events were compared. Both generators did very well on imitating the mean and the variance of the monthly values of the investigated variables, but both showed a more moderate performance as far as the generation of extreme events was concerned. The three-parameter Weibull function, which is first introduced in MV-WG, was found to be a powerful tool to describe not only the distribution of the daily precipitation amounts, but also the distribution of dry and wet spell lengths, as well.