Ensemble Of Numerical Simulations Research Articles

Water Mass Transport Changes through the Venice Lagoon Inlets from Projected Sea-Level Changes under a Climate Warming Scenario

In this study, an ensemble of numerical simulations with a state-of-the-art hydrodynamic model for coastal applications is used to characterize, for the first time, the expected mid-21st-century changes in circulation and associated sea-level height inside the Venice lagoon induced by projected Mediterranean sea level rise and atmospheric circulation changes over the Adriatic Sea under the RCP8.5 emission scenario. Our results show that water transports through the three inlets connecting the Venice lagoon to the open sea are expected to change significantly, with consequent significant persistent alterations of the circulation and sea-level height inside the lagoon. The projected water mass redistributions motivate further studies on the implications of climate change for the lagoon environment.

An Ensemble-Based Analysis of a Liminal Extreme Rainfall Event near Taiwan

This study analyzes an ensemble of numerical simulations of a heavy rainfall event east of Taiwan on 9 June 2020. Heavy rainfall was produced by quasi-stationary back-building mesoscale convective systems (MCS) associated with a mei-yu front. Global model forecast skill was poor in location and intensity of rainfall. The mesoscale ensemble showed liminal conditions between heavy rainfall or little to no rainfall. The two most accurate and two least accurate ensemble members are selected for analysis via validation against radar-estimated rainfall observations. All members feature moist soundings with low levels of free convection (LFC) and sufficient instability for deep convection. We find that stronger gradients in 100-m θe and θv in the most accurate members associated with a near-surface frontal boundary focus the lifting mechanism for deep, moist convection and enhanced rainfall. As the simulations progress, stronger southerly winds in the least accurate members advect drier mid-level air into the region of interest and shift the near-surface boundary further north and west. Analysis of the verification ensemble mean analysis reveals a strong near-surface frontal boundary similarly positioned as in the most accurate members and dry air aloft more similar to that in the least accurate members, suggesting that the positioning of the frontal boundary is more critical to accurately reproducing rainfall patterns and intensity in this case. The analyses suggest that subtle details in the simulation of frontal boundaries and mesoscale flow structures can lead to bifurcations in producing extreme or almost no rainfall. Implications for improved probabilistic forecasts of heavy rainfall events will be discussed.

Offshore Freshwater Pathways in the Northern Gulf of Mexico: Impacts of Modeling Choices

The Gulf of Mexico is a very productive and economically important system where riverine runoff acts as a linkage between the continental shelf and the open ocean, providing nutrients in addition to freshwater. This work investigates the three-dimensional transport and pathway structure of this river runoff offshore the continental shelf using ensembles of numerical simulations with different configurations regarding grid resolution (mesoscale resolving and submesoscale permitting) and river setup using suites of 5-months long integrations covering nearly 3 years. The riverine forcing is applied only at the surface over an area around the river mouth, a strategy often adopted in numerical studies, or as a meridional flux with a vertical extension. The simulated flow captures the southward offshore transport of river runoff driven by its interaction with the largest mesoscale circulations in the basin, the Loop Current and Loop Current eddies. This pathway is strong and well-document during summer but also active and relevant in winter, despite a less obvious surface signature. The most intense transport occurs primarily at the peripheries of the Loop Current and the detached eddies, and the freshwater is subducted as deep as 600 m around the mesoscale anticyclonic eddies. Submesoscale motions strengthen slightly the spread of freshwater plumes in summer but their contribution is negligible, if not negative, in winter. Differences in the freshwater distribution and transport volume among runs are small and generally less than 10% among ensembles, with overall slightly higher volume of freshwater transported off-shore and at depth in submesoscale permitting runs that include a velocity flux in their riverine input representation.

Suppression of Optical Rogue Waves by Dispersion Oscillating Fiber in the Mid-infrared Supercontinuum

We further numerically study the mid-infrared supercontinuum (SC) and the rare optical rogue wave (ORW) generated by femtosecond pulse pumping in chalcogenide fibers. Specifically, it is shown via ensembles of numerical simulations that the compression of the spectrum by dispersion oscillating fiber (DOF) effectively controls the generation of ORW. A comparison is made between uniform fiber (UF) and DOF, the spectral bandwidth is compressed from 5,800 nm of UF to 2,300 nm of DOF, and the ORW of high peak power is suppressed. In addition, the oscillation amplitude, oscillation period and initial phase of DOF dispersion are further changed. It has been proved that the suppression effect of ORW is the best when the oscillation amplitude is 300 ps2/km, the oscillation period is 0.5 cm and the initial phase is 0. We believe that our research results will provide some enlightenment for controlling the direction of ORW by changing the characteristics of optical fiber, improving the performance of SC.

CARPool: fast, accurate computation of large-scale structure statistics by pairing costly and cheap cosmological simulations

ABSTRACT To exploit the power of next-generation large-scale structure surveys, ensembles of numerical simulations are necessary to give accurate theoretical predictions of the statistics of observables. High-fidelity simulations come at a towering computational cost. Therefore, approximate but fast simulations, surrogates, are widely used to gain speed at the price of introducing model error. We propose a general method that exploits the correlation between simulations and surrogates to compute fast, reduced-variance statistics of large-scale structure observables without model error at the cost of only a few simulations. We call this approach Convergence Acceleration by Regression and Pooling (CARPool). In numerical experiments with intentionally minimal tuning, we apply CARPool to a handful of gadget-iii N-body simulations paired with surrogates computed using COmoving Lagrangian Acceleration. We find ∼100-fold variance reduction even in the non-linear regime, up to $k_\mathrm{max} \approx 1.2\, h {\rm Mpc^{-1}}$ for the matter power spectrum. CARPool realizes similar improvements for the matter bispectrum. In the nearly linear regime CARPool attains far larger sample variance reductions. By comparing to the 15 000 simulations from the Quijote suite, we verify that the CARPool estimates are unbiased, as guaranteed by construction, even though the surrogate misses the simulation truth by up to $60{{\ \rm per\ cent}}$ at high k. Furthermore, even with a fully configuration-space statistic like the non-linear matter density probability density function, CARPool achieves unbiased variance reduction factors of up to ∼10, without any further tuning. Conversely, CARPool can be used to remove model error from ensembles of fast surrogates by combining them with a few high-accuracy simulations.

Dynamics of optical rogue wave generation in dispersion oscillating fibers.

We present an in-depth investigation of optical rogue waves (ORWs) during picosecond supercontinuum generations in photonic crystal fibers with periodic landscapes of group velocity dispersion and nonlinearity, namely dispersion oscillating fibers (DOFs). Specifically, it is shown via ensembles of numerical simulations that during supercontinuum generations, the rogue nature of extreme and rare events formed in uniform fibers can be effectively manipulated in DOFs. This is also verified by comparing single evolution dynamics in different dispersion longitudinal profiles. For investigating the influence of slow dynamics of ORW generation in DOFs, we increase the propagating distance and find out MI gain is still the major factor that influences the generation of ORWs. In addition, analytical results associated with simulations indicate the rogue manipulations in DOFs are attributed to the adjustable modulation-instability-gain due to periodic dispersion variation along fiber length. Finally, unlike MI in uniform fiber, MI gain side lobes result from quasi-phase-matching (QPM) relation in DOFs provide additional degree of freedom to control generations of ORWs. We believe our results will provide not only a novel insight of understanding ORW dynamics in presence of dispersion modulations, but also a new way of harnessing rogue waves in oceanology.

A Modeling Strategy for the Investigation of the Effect of Mesoscale SST Variability on Atmospheric Dynamics

AbstractAn efficient modeling strategy is proposed for the investigation of the effect of the sea surface temperature (SST) mesoscale variability on atmospheric dynamics. Two ensembles of numerical simulations are generated with a high‐resolution atmospheric global circulation model coupled to a slab ocean model. The two ensembles differ only in the treatment of the SST data used for the specification of the SST initial conditions and the estimation of the oceanic heat transport: one of the ensembles is generated by retaining, while the other by filtering, the mesoscale SST variability. The effect of mesoscale SST variability is assessed by comparing the two ensembles. The strategy is illustrated by simulation experiments with the Community Earth System Model, with a focus on the processes of the NH midlatitudes. The results suggest that ocean mesoscale variability has a significant effect on the jet streams, large‐scale flow, and midlatitude storm tracks.

Impact of climate change and seasonal trends on the fate of Arctic oil spills

We investigated the effects of a warmer climate, and seasonal trends, on the fate of oil spilled in the Arctic. Three well blowout scenarios, two shipping accidents and a pipeline rupture were considered. We used ensembles of numerical simulations, using the OSCAR oil spill model, with environmental data for the periods 2009–2012 and 2050–2053 (representing a warmer future) as inputs to the model. Future atmospheric forcing was based on the IPCC’s A1B scenario, with the ocean data generated by the hydrodynamic model SINMOD. We found differences in “typical” outcome of a spill in a warmer future compared to the present, mainly due to a longer season of open water. We have demonstrated that ice cover is extremely important for predicting the fate of an Arctic oil spill, and find that oil spills in a warming climate will in some cases result in greater areal coverage and shoreline exposure.

Impact of wildfire-induced land cover modification on local meteorology: A sensitivity study of the 2003 wildfires in Portugal

Wildfires alter land cover creating changes in dynamic, vegetative, radiative, thermal and hydrological properties of the surface. However, how so drastic changes induced by wildfires and how the age of the burnt scar affect the small and meso-scale atmospheric boundary layer dynamics are largely unknown. These questions are relevant for process analysis, meteorological and air quality forecast but also for regional climate analysis. Such questions are addressed numerically in this study on the case of the Portugal wildfires in 2003 as a testbed. In order to study the effects of burnt scars, an ensemble of numerical simulations using the Weather Research and Forecasting modeling system (WRF) have been performed with different surface properties mimicking the surface state immediately after the fire, few days after the fire and few months after the fire. In order to investigate such issue in a seamless approach, the same modelling framework has been used with various horizontal resolutions of the model grid and land use, ranging from 3.5km, which can be considered as the typical resolution of state-of-the art regional numerical weather prediction models to 14km which is now the typical target resolution of regional climate models.The study shows that the combination of high surface heat fluxes over the burnt area, large differential heating with respect to the preserved surroundings and lower surface roughness produces very intense frontogenesis with vertical velocity reaching few meters per second. This powerful meso-scale circulation can pump more humid air from the surroundings not impacted by the wildfire and produce more cloudiness over the burnt area. The influence of soil temperature immediately after the wildfire ceases is mainly seen at night as the boundary-layer remains unstably stratified and lasts only few days. So the intensity of the induced meso-scale circulation decreases with time, even though it remains until full recovery of the vegetation. Finally all these effects are simulated whatever the land cover and model resolution and there are thus robust processes in both regional climate simulations and process studies or short-time forecast. However, the impact of burnt scars on the precipitation signal remains very uncertain, especially because low precipitation is at stake.

Upper thermospheric responses to forcing from above and below during 1–10 April 2010: Results from an ensemble of numerical simulations

AbstractIn this report we examine the spatial and temporal variability of the quiescent thermosphere leading up to and after the 5 April 2010 geomagnetic disturbance. We attribute the dominant driver of this variability to a combination of tides generated in situ and in the troposphere, stratosphere, and mesosphere. We identify nonmigrating tidal signatures attributable to the latter source that are ubiquitous, persistent, and significant at all thermospheric latitudes. Further, these perturbations underlie the upper atmospheric response to solar geomagnetic disturbances and are measurably altered, along with their migrating counterparts, during the storm. Our investigation is centered on a series of National Center for Atmospheric Research thermosphere‐ionosphere‐mesosphere‐electrodynamics general circulation model simulations during 1–10 April 2010, including an optimal simulation with lower boundary forcing based on Modern‐Era Retrospective Analysis for Research and Application reanalysis data and upper boundary forcing based on satellite and ground magnetometer measurements and the Assimilative Mapping of Ionospheric Electrodynamics procedure and three diagnostic simulations. The differences between the optimal and diagnostic simulations allow us to quantify thermospheric variability attributable to solar geomagnetic forcing and dynamical effects propagating into the thermosphere from below. We find that they can be comparable at high latitudes for some nonmigrating tidal components.

Contour Boxplots: A Method for Characterizing Uncertainty in Feature Sets from Simulation Ensembles

Ensembles of numerical simulations are used in a variety of applications, such as meteorology or computational solid mechanics, in order to quantify the uncertainty or possible error in a model or simulation. Deriving robust statistics and visualizing the variability of an ensemble is a challenging task and is usually accomplished through direct visualization of ensemble members or by providing aggregate representations such as an average or pointwise probabilities. In many cases, the interesting quantities in a simulation are not dense fields, but are sets of features that are often represented as thresholds on physical or derived quantities. In this paper, we introduce a generalization of boxplots, called contour boxplots, for visualization and exploration of ensembles of contours or level sets of functions. Conventional boxplots have been widely used as an exploratory or communicative tool for data analysis, and they typically show the median, mean, confidence intervals, and outliers of a population. The proposed contour boxplots are a generalization of functional boxplots, which build on the notion of data depth. Data depth approximates the extent to which a particular sample is centrally located within its density function. This produces a center-outward ordering that gives rise to the statistical quantities that are essential to boxplots. Here we present a generalization of functional data depth to contours and demonstrate methods for displaying the resulting boxplots for two-dimensional simulation data in weather forecasting and computational fluid dynamics.

Probability-weighted hazard maps for comparing different flood risk management strategies: a case study

The study proposes an original methodology for producing probability-weighted hazard maps based on an ensemble of numerical simulations. These maps enable one to compare different strategies for flood risk management. The methodology was applied over a 270-km2 flood-prone area close to the left levee system of a 28-km reach of the river Reno (Northern Central Italy). This reach is characterised by the presence of a weir that allows controlled flooding of a large flood-prone area during major events. The proposed probability-weighted hazard maps can be used to evaluate how a structural measure such as the mentioned weir alters the spatial variability of flood hazard in the study area. This article shows an application by constructing two different flood hazard maps: a first one which neglects the presence of the weir using a regular levee system instead, and a second one that reflects the actual geometry with the weir. Flood hazard maps were generated by combining the results of several inundation scenarios, simulated by coupling 1D- and 2D-hydrodynamic models.

Analytic model for the bispectrum of galaxies in redshift space

We develop an analytic theory for the redshift space bispectrum of dark matter, haloes, and galaxies. This is done within the context of the halo model of structure formation, as this allows for the self-consistent inclusion of linear and nonlinear redshift-space distortions and also for the nonlinearity of the halo bias. The model is applicable over a wide range of scales: on the largest scales the predictions reduce to those of the standard perturbation theory (PT); on smaller scales they are determined primarily by the nonlinear virial velocities of galaxies within haloes, and this gives rise to the $U$-shaped anisotropy in the reduced bispectrum---a finger print of the Finger-Of-God distortions. We then confront the predictions with measurements of the redshift-space bispectrum of dark matter from an ensemble of numerical simulations. On very large scales, $k=0.05h\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$, we find reasonably good agreement between our halo model, PT and the data, to within the errors. On smaller scales, $k=0.1h\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$, the measured bispectra differ from the PT at the level of $\ensuremath{\sim}10%--20%$, especially for colinear triangle configurations. The halo model predictions improve over PT, but are accurate to no better than 10%. On smaller scales $k=0.5--1.0h\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$, our model provides a significant improvement over PT, which breaks down. This implies that studies which use the lowest order PT to extract galaxy bias information are not robust on scales $k\ensuremath{\gtrsim}0.1h\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$. The analytic and simulation results also indicate that there is no observable scale for which the configuration dependence of the reduced bispectrum is constant---hierarchical models for the higher-order correlation functions in redshift space are unlikely to be useful. It is hoped that our model will facilitate extraction of information from large-scale structure surveys of the Universe, because different galaxy populations are naturally included into our description.

The transient emission of propagating gravity waves by a stably stratified shear layer

AbstractBy analysing the transient evolution of an initial perturbation, it is shown that a stably stratified shear layer emits gravity waves having well defined dynamical characteristics. For instance, the outgoing waves systematically have phase lines tilting against the shear, their vertical momentum flux has a sign opposite to that of the shear and their amplitude increases when the flow stability decreases. Those features are commonly observed in numerical simulations of gravity waves generated by convection. It is shown that they are related to the singular vectors of the system that have fast energy growth and fast energy decay within a finite time. In this work, the singular vectors are computed using a linear gravity‐wave model, its adjoint and an iterative Lanczos algorithm. For a given shear layer, characterized by a minimum Richardson number Ri and a depth d, these perturbations show that emission of gravity waves by a stratified shear layer essentially occurs for waves with horizontal wave number close to a critical value kc = √Ri/d. The importance of the singular vectors on the dynamics of more general initial conditions is also tested by making few ensembles of numerical simulations with stochastic initial conditions imposed inside the shear layer. The amplitude of the momentum fluxes of the outgoing waves as a function of Ri is also evaluated systematically. It gives a relationship between the efficiency of gravity‐wave emission and Ri that could be used in convective gravity‐wave parametrization schemes.

Biased power spectrum and bispectrum for an ensemble of three-dimensional scale-free numerical simulations

We examine the effect of a threshold bias on the power spectrum and the bispectrum in an ensemble of numerical simulations (Gaussian initial perturbations with power law spectra P(k) \sim k^n, n=+1, 0, -1, -2) and compare our results with theoretical predictions. Our simulations are evolved sufficiently that on the scale where we apply the threshold the rms fluctuation has developed significantly into the nonlinear regime. Thus, predictions based on perturbation theory do not necessarily apply. Nevertheless, we find our results for the power spectrum, biased power simply amplified by a numerical factor, follow predicted trends, far beyond the regime where perturbation theory is expected to be valid. We find that the biased bispectrum continues to follow the so-called hierarchical form, with reduced three-point amplitude Q \approx 1 in the strongly nonlinear regime, independent of initial spectrum. In the quasi-linear perturbative regime the three-point amplitude depends on configuration shape, a behavior that is found to give useful information about the amount of bias without information about the unbiased matter distribution.

The three-point function in an ensemble of numerical simulations

We evaluate the three-point function in Fourier space for an ensemble of two-dimensional numerical simulations with nine initial power spectra distinguished by spectral index and cutoff. To remove the main dependences on scale and time, we present results as the reduced amplitude Q in the hierarchical model. To lowest nonvanishing order in perturbation theory, Q is a constant, independent of length scale, of time, and of initial spectrum. Our results show that in the nonlinear regime of evolution, normalizing to Q does remove the main variations, but systematic dependences on spectral index and cutoff remain at late times that depend on properties of the initial spectrum. Models with initial power cut off on a scale that has been evolved far into the nonlinear regime are indistinguishable from models with no cutoff.