Ensemble Numerical Simulations Research Articles

Ensemble Numerical Simulations of Realistic SEP Events and the Inspiration for Space Weather Awareness

The solar energetic particle (SEP) event is a kind of hazardous space weather phenomena, so its quantitative forecast is of great importance from the aspect of space environmental situation awareness. We present here a set of SEP forecast tools, which consists of three components : (1) a simple polytropic solar wind model to estimate the background solar wind conditions at the inner boundary of 0.1 AU (about 20 R ⊙); (2) an ice-cream-cone model to estimate the erupted coronal mass ejection (CME) parameters; and (3) the improved Particle Acceleration and Transport in the Heliosphere (iPATH) model to calculate particle fluxes and energy spectra. By utilizing the above models, we have simulated six realistic SEP events from 2010 August 14 to 2014 September 10, and compared the simulated results to the Geostationary Operational Environmental Satellites (GOES) spacecraft observations. The results show that the simulated fluxes of >10 MeV particles agree with the observations while the simulated fluxes of >100 MeV particles are higher than the observed data. One of the possible reasons is that we have adopted a simple method in the model to calculate the injection rate of energetic particles. Furthermore, we have conducted the ensemble numerical simulations over these events and investigated the effects of different background solar wind conditions at the inner boundary on SEP events. The results imply that the initial CME density plays an important role in determining the power spectrum, while the effect of varying background solar wind temperature is not significant. Naturally, we have examined the influence of CME initial density on the numerical prediction results for virtual SEP cases with different CME ejection speeds. The result shows that the effect of initial CME density variation is inversely associated with CME speed.

A self-organizing forecast of day-ahead wind speed: Selective ensemble strategy based on numerical weather predictions

Accurate wind predictions are required in modern wind power generations, for which numerical weather predictions are generally used. This study focuses on short-term wind speed forecast based on ensemble numerical simulations. As for typical ensemble methods, all the single members are intuitively included, while an interesting idea is that the ensemble performance could be improved if the low-performing members are recognized and removed. With this conception, a selective ensemble system is developed in this study, which is a new method of ensemble numerical simulations especially for day-ahead wind speed predictions at local wind farms. The developed method is constructed by ensemble atmospheric simulations of weather research and forecasting models, a sample clustering process using Gaussian mixture model, an automatic modeling mechanism using group method of data handling network, and a multi-objective Cuckoo search optimization. The results obtained led to the following original conclusions: (i) the proposed method automatically excludes some low-performing members, signifying that ensembles with selected members could generate better forecasts than those with a combination of all members; (ii) by partitioning wind series into wave-like segments and applying sample clustering, model’s performance can be further improved.

Ferromagnetism-induced phase separation in a two-dimensional spin fluid.

We study the liquid-gas phase separation observed in a system of repulsive particles dressed with ferromagnetically aligning spins, a so-called "spin fluid." Microcanonical ensemble numerical simulations of finite-size systems reveal that magnetization sets in and induces a liquid-gas phase separation between a disordered gas and a ferromagnetic dense phase at low enough energies and large enough densities. The dynamics after a quench into the coexistence region show that the order parameter associated with the liquid-vapor phase separation follows an algebraic law with an unusual exponent, as it is forced to synchronize with the growth of the magnetization: this suggests that for finite size systems the magnetization sets in along a Curie line, which is also the gas-side spinodal line, and that the coexistence region ends at a tricritical point. This picture is confirmed at the mean-field level with different approximation schemes, namely, a Bethe lattice resolution and a virial expansion complemented by the introduction of a self-consistent Weiss-like molecular field. However, a detailed finite-size scaling analysis shows that in two dimensions the ferromagnetic phase escapes the Berezinskii-Kosterlitz-Thouless scenario and that the long-range order is not destroyed by the unbinding of topological defects. The Curie line thus becomes a magnetic crossover in the thermodynamic limit. Finally, the effects of the magnetic interaction range and those of the interaction softness are characterized within a mean-field semianalytical low-density approach.

What would happen to Superstorm Sandy under the influence of a substantially warmer Atlantic Ocean?

AbstractBased on ensemble numerical simulations, we find that possible responses of Sandy‐like superstorms under the influence of a substantially warmer Atlantic Ocean bifurcate into two groups. In the first group, storms are similar to present‐day Sandy from genesis to extratropical transition, except they are much stronger, with peak Power Destructive Index (PDI) increased by 50–80%, heavy rain by 30–50%, and maximum storm size (MSS) approximately doubled. In the second group, storms amplify substantially over the interior of the Atlantic warm pool, with peak PDI increased by 100–160%, heavy rain by 70–180%, and MSS more than tripled compared to present‐day Superstorm Sandy. These storms when exiting the warm pool, recurve northeastward out to sea, subsequently interact with the developing midlatitude storm by mutual counterclockwise rotation around each other and eventually amplify into a severe Northeastern coastal storm, making landfall over the extreme northeastern regions from Maine to Nova Scotia.

Characteristics and Momentum Flux Spectrum of Convectively Forced Internal Gravity Waves in Ensemble Numerical Simulations

Abstract Characteristics of convectively forced gravity waves are investigated through ensemble numerical simulations for various ideal and real convective storms. For ideal storm cases, single-cell-, multicell-, and supercell-type storms are considered, and for real cases, convection events observed during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) and in Indonesia are used. For each storm case, wave perturbations and the momentum flux spectrum of convective gravity waves in a control simulation with nonlinearity and cloud microphysical processes are compared with those in quasi-linear dry simulations forced by either diabatic forcing or nonlinear forcing obtained from the control simulation. In any case, gravity waves in the control simulation cannot be represented well by wave perturbations induced by a single forcing. However, when both diabatic and nonlinear forcing terms are considered, the gravity waves and their momentum flux spectrum become comparable to those in the control simulation, because of cancellation between wave perturbations by two forcing terms. These results confirm that the two forcing mechanisms of convective gravity waves proposed by previous studies based on a single convective event can be applied generally to various types of convective storms. This suggests that nonlinear forcing, as well as diabatic forcing, should be considered appropriately in parameterizations of convectively forced gravity waves.

Modulational instability and non-Gaussian statistics in experimental random water-wave trains

We study random, long-crested surface gravity waves in the laboratory environment. Starting with wave spectra characterized by random phases we consider the development of the modulational instability and the consequent formation of large amplitude waves. We address both dynamical and statistical interpretations of the experimental data. While it is well known that the Stokes wave nonlinearity leads to non-Gaussian statistics, we also find that the presence of the modulational instability is responsible for the departure from a Gaussian behavior, indicating that, for particular parameters in the wave spectrum, coherent unstable modes are quite prevalent, leading to the occurrence of what might be called a “rogue sea.” Statistical results are also compared with ensemble numerical simulations of the Dysthe equation.

On the surface and atmospheric temperature changes following the 1991 Pinatubo volcanic eruption: A GCM study

Ensemble numerical simulations are performed using an atmospheric general circulation model to study the responses of the atmosphere to volcanic aerosol forcing and sea surface temperature (SST) forcing during the two years following the Pinatubo eruption. The simulated surface air temperature (SAT) anomalies, forced respectively and jointly by the Pinatubo aerosol and the observed SST anomalies, are compared to those derived from observations using a singular value decomposition (SVD) model. The simulated land SAT anomalies, forced only by the observed SST anomalies, match well in magnitude and time the leading mode of SAT anomalies from the SVD analysis, which represents the ENSO‐forced SAT variations. When forced by both the Pinatubo aerosol and the observed SST anomalies, the model captures the observed surface cooling over land in June–July–August and September–October–November 1992 but misses the surface warming over northern Eurasia in December–January–February (DJF) 1991–1992 and DJF 1992–1993. In the atmosphere the simulated temperature anomalies in the troposphere (stratosphere) forced by the Pinatubo aerosol are sensitive (insensitive) to the initial conditions and the type of prescribed SST. The signal of SST forcing is stronger in the troposphere and near the surface than in the stratosphere, while the signal of the Pinatubo aerosol forcing is strongest in the lower stratosphere. The simulated global‐mean stratospheric temperature anomalies induced by the Pinatubo aerosol are generally 1°C to 1.5°C larger than observed. Empirical data analyses and numerical model simulations showed that this discrepancy is explained in part by the influences of the quasi‐biennial oscillation and the observed ozone depletion, which the ensemble numerical simulations did not resolve.