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77 records · Page 5

Parameterizations of Chromospheric Condensations in dG and dMe Model Flare Atmospheres

The origin of the near-ultraviolet and optical continuum radiation in flares is critical for understanding particle acceleration and impulsive heating in stellar atmospheres. Radiative-hydrodynamic (RHD) simulations in 1D have shown that high energy deposition rates from electron beams produce two flaring layers at T approximately 10 (exp 4) K that develop in the chromosphere: a cooling condensation (downflowing compression) and heated non-moving (stationary) flare layers just below the condensation. These atmospheres reproduce several observed phenomena in flare spectra, such as the red-wing asymmetry of the emission lines in solar flares and a small Balmer jump ratio in M dwarf flares. The high beam flux simulations are computationally expensive in 1D, and the (human) timescales for completing NLTE models with adaptive grids in 3D will likely be unwieldy for some time to come. We have developed a prescription for predicting the approximate evolved states, continuum optical depth, and emergent continuum flux spectra of RHD model flare atmospheres. These approximate prescriptions are based on an important atmospheric parameter: the column mass (m(sub ref)) at which hydrogen becomes nearly completely ionized at the depths that are approximately in steady state with the electron beam heating. Using this new modeling approach, we find that high energy flux density (>F11) electron beams are needed to reproduce the brightest observed continuum intensity in IRIS data of the 2014 March 29 X1 solar flare, and that variation in m(sub ref) from 0.001 to 0.02 g cm (exp -2) reproduces most of the observed range of the optical continuum flux ratios at the peak of M dwarf flares.

Kowalski, Adam F.↗

Interrogating Solar Flare Loop Models with IRIS Observations 2: Plasma Properties, Energy Transport, and Future Directions

During solar flares a tremendous amount of magnetic energy is released and transported through the Sun’s atmosphere and out into the heliosphere. Despite over a century of study, many unresolved questions surrounding solar flares are still present. Among those are how does the solar plasma respond to flare energy deposition, and what are the important physical processes that transport that energy from the release site in the corona through the transition region and chromosphere? Attacking these questions requires the concert of advanced numerical simulations and high spatial-, temporal-, and spectral-resolution observations. While flares are 3D phenomenon, simulating the NLTE flaring chromosphere in 3D and performing parameter studies of 3D models is largely outwith our current computational capabilities. We instead rely on state-of-the-art 1D field-aligned simulations to study the physical processes that govern flares. Over the last decade, data from the Interface Region Imaging Spectrograph (IRIS) have provided the crucial observations with which we can critically interrogate the predictions of those flare loop models. Here in Paper 2 of a two-part review of IRIS and flare loop models, I discuss how forward modelling flares can help us understand the observations from IRIS, and how IRIS can reveal where our models do well and where we are likely missing important processes, focussing in particular on the plasma properties, energy transport mechanisms, and future directions of flare modelling.

solar flares↗

Enabling the Assimilation of CrIS Shortwave Infrared Observations in Global NWP at NOAA. Part I: Background and Methods

Radiance observations from Earth-observing satellites have a significant positive impact on numerical weather prediction (NWP) forecasts, but some spectral regions are not fully exploited. Observations from hyperspectral infrared (IR) sounders in the longwave region (650-1100 cm -1 ), for instance, are routinely assimilated in many NWP models, but observations in the shortwave region (2155-2550 cm -1 ) are not. Each of these regions provides information on the temperature structure of the atmosphere, but the shortwave IR (SWIR) region is considered challenging to assimilate due to noise equivalent delta temperature (NEDT) that is highly variable depending on scene brightness temperature and to phenomena that are difficult to model, like non-Local Thermodynamic Equilibrium (NLTE) and solar reflectance. With recent advances in small-satellite technology, SWIR temperature sounders may provide an agile and cost-effective complement to the current constellation of IR sounders. Therefore, a better understanding of the use and impact of SWIR observations in data assimilation for NWP is warranted. In part one of this study, as presented here, the amount of unique information (as determined by Empirical Orthogonal Decomposition (EOD)) made available to a data assimilation system by Cross-track Infrared Sounder (CrIS) SWIR observations is reviewed, recent advancements to the Community Radiative Transfer Model (CRTM) for the simulation of CrIS shortwave radiances are tested, and enhancements to NOAA’s Global Data Assimilation System (GDAS) for the assimilation of CrIS SWIR observations are implemented and evaluated. Part two of this study, which seeks to assess the value of assimilating shortwave IR observations in global NWP, is also introduced.

Erin Jones↗

Understanding the deficiency in inertial confinement fusion hohlraum x-ray flux predictions using experiments at the National Ignition Facility

The predicted implosion performance of deuterium-tritium fuel capsules in indirect-drive inertial confinement fusion experiments relies on precise calculations of the x-ray drive in laser-heated cavities (hohlraums). This requires accurate, spectrally dependent simulations of laser to x-ray conversion efficiencies and x-ray absorption losses to the hohlraum wall. A set of National Ignition Facility experiments have identified a cause for the long-standing hohlraum “drive deficit” as the overprediction of gold emission at ~2.5 keV in nonlocal thermodynamic equilibrium coronal plasma regions within the hohlraum. Finally, reducing the emission and absorption opacity in this spectral region by ~20% brings simulations into agreement with measured x-ray fluxes and spectra.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transfer Learning of High-Fidelity Opacity Spectra in Autoencoders and Surrogate Models

Simulations of high energy density physics are expensive, largely in part for the need to produce nonlocal thermodynamic equilibrium opacities. High-fidelity spectra may reveal new physics in the simulations not seen with low-fidelity spectra, but the cost of these simulations also scales with the level of fidelity of the opacities being used. Neural networks are capable of reproducing these spectra, but neural networks need data to train them, which limits the level of fidelity of the training data. Here this article demonstrates that it is possible to reproduce high-fidelity spectra with median errors in the realm of 3%–4% using as few as 50 samples of high-fidelity Krypton data by performing transfer learning on a neural network trained on many times more low-fidelity data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗