Radiative Transfer Simulations Research Articles

A public grid of radiative transfer simulations for Lyman-alpha and metal lines in idealised galactic outflows

The vast majority of star-forming galaxies are surrounded by large reservoirs of gas ejected from the interstellar medium. Ultraviolet absorption and emission lines represent powerful diagnostics to constrain the cool phase of these outflows, through resonant transitions of hydrogen and metal ions. The interpretation of these observations is often remarkably difficult as it requires detailed modelling of the propagation of the continuum and emission lines in the gas. To this aim, we present a large public grid of $ 20,000$ simulated spectra that includes and five metal transitions associated with and which is accessible online. The spectra have been computed with the Monte Carlo radiative transfer code for $5,760$ idealised spherically symmetric configurations surrounding a central point source emission, and characterised by their column density, Doppler parameter, dust opacity, wind velocity, as well as various density and velocity gradients. Designed to predict and interpret and metal line profiles, our grid exhibits a wide diversity of resonant absorption and emission features, as well as fluorescent lines. We illustrate how it can help better constrain the wind properties by performing a joint modelling of observed and spectra. Using simulations and virial scaling relations, we also show that is expected to be a faithful tracer of the gas at $T 10^4-10^5$ K, even if the medium is highly ionised. While is found to probe the same range of temperatures as other metal lines merely trace cooler phases ($T 10^4$ K). As their gas opacity strongly depends on gas temperature, incident radiation field, metallicity and dust depletion, we caution that optically thin metal lines do not necessarily originate from low column densities and may not accurately probe Lyman continuum leakage.

Light Transfers Through a Koch Shape Cloud

AbstractModeling radiative transfer in a 3D cloudy atmosphere is critical to climate projections. A recently developed fast 3D radiation parameterization scheme gains some success in quantifying horizontal radiative transfer through cloud sides using cloud area fraction. Based on 3D Monte Carlo simulations of radiative transfer through an idealized single‐layer cloud with Koch‐shaped fractal geometry edges, here we show that radiative energy transport through cloud sides correlates more significantly with cloud area fraction than with cloud perimeter length. The results exemplify the importance of accounting for the horizontal radiative energy exchanges between cloud‐free and cloudy regions with cloud area fraction. Results from additional sensitivity simulations show that increased cloud vertical extent often enhances cloud‐side sunlight leak more significantly than cloud‐side sunlight interception. At low sun elevations, cloud‐side sunlight interception is enhanced more than cloud‐side sunlight leak does with the increase of cloud mass.

Benchmark simulations of radiative transfer in participating binary stochastic mixtures in two dimensions

We study radiative transfer in participating binary stochastic mixtures in two dimensions (2D) by developing an accurate and efficient simulation tool. For two different sets of physical parameters, 2D benchmark results are presented, and it is found that the influence of the stochastic mixture on radiative transfer is clearly parameter-dependent. Our results confirm that previous multidimensional results obtained in different studies are basically consistent, which is interpreted in terms of the relationship between the photon mean free path lp and the system size L. Nonlinear effects, including those due to scattering and radiation–material coupling, are also discussed. To further understand the particle size effect, we employ a dimensionless parameter lp/L, from which a critical particle size can be derived. On the basis of further 2D simulations, we find that an inhomogeneous mix is obtained for lp/L > 0.1. Furthermore, 2D material temperature distributions reveal that self-shielding and particle–particle shielding of radiation occur, and are enhanced when lp/L is increased. Our work is expected to provide benchmark results to verify proposed homogenized models and/or other codes for stochastic radiative transfer in realistic physical scenarios.

Anatomy of the uncertainty of satellite vicarious calibration using radiosondes: concepts and preliminary results for microwave radiometric observations

Calibration of satellite observations is crucial for ensuring the quality of retrieved products essential for meteorological and climate applications. Calibration is obtained and monitored through a cascade of stages, including postlaunch vicarious calibration/validation activities through comparison with independent reference measurements. Here, the vicarious calibration method using radiative transfer simulations based on reference radiosondes is considered in the framework of the calibration/validation activities for the Microwave Imager (MWI) and the Ice Cloud Imager (ICI) to be launched with the Second Generation of the EUMETSAT Polar System. This paper presents an overview of the uncertainty characterizing the vicarious calibration of MWI and ICI using radiosondes as performed within the EUMETSAT-funded VICIRS study. The uncertainty characterization is pursued following a metrological approach, providing a preliminary estimation of all the identified sources. The same approach is used to develop a rigorous method for estimating the number of comparison pairs (i.e., observations vs. simulations) needed to reach a certain level of accuracy in bias determination.

Final Moments. II. Observational Properties and Physical Modeling of Circumstellar-material-interacting Type II Supernovae

We present ultraviolet/optical/near-infrared observations and modeling of Type II supernovae (SNe II) whose early time (δ t < 2 days) spectra show transient, narrow emission lines from shock ionization of confined (r < 1015 cm) circumstellar material (CSM). The observed electron-scattering broadened line profiles (i.e., IIn-like) of H i, He i/ii, C iv, and N iii/iv/v from the CSM persist on a characteristic timescale (t IIn) that marks a transition to a lower-density CSM and the emergence of Doppler-broadened features from the fast-moving SN ejecta. Our sample, the largest to date, consists of 39 SNe with early time IIn-like features in addition to 35 “comparison” SNe with no evidence of early time IIn-like features, all with ultraviolet observations. The total sample includes 50 unpublished objects with a total of 474 previously unpublished spectra and 50 multiband light curves, collected primarily through the Young Supernova Experiment and Global Supernova Project collaborations. For all sample objects, we find a significant correlation between peak ultraviolet brightness and both t IIn and the rise time, as well as evidence for enhanced peak luminosities in SNe II with IIn-like features. We quantify mass-loss rates and CSM density for the sample through the matching of peak multiband absolute magnitudes, rise times, t IIn, and optical SN spectra with a grid of radiation hydrodynamics and non-local thermodynamic equilibrium radiative-transfer simulations. For our grid of models, all with the same underlying explosion, there is a trend between the duration of the electron-scattering broadened line profiles and inferred mass-loss rate: tIIn≈3.8[Ṁ/ (0.01 M ⊙ yr−1)] days.

Kilonova light-curve interpolation with neural networks

Kilonovae are the electromagnetic transients created by the radioactive decay of freshly synthesized elements in the environment surrounding a neutron star merger. To study the fundamental physics in these complex environments, kilonova modeling requires, in part, the use of radiative transfer simulations. The microphysics involved in these simulations results in high computational cost, prompting the use of emulators for parameter inference applications. Utilizing a training set of 22 248 high-fidelity simulations (composed of 412 unique ejecta parameter combinations evaluated at 54 viewing angles), we use a neural network to efficiently train on existing radiative transfer simulations and predict light curves for new parameters in a fast and computationally efficient manner. Our neural network can generate millions of new light curves in under a minute. We discuss our emulator's degree of off-sample reliability and parameter inference of the AT2017gfo observational data. Finally, we discuss tension introduced by multiband inference in the parameter inference results, particularly with regard to the neural network's recovery of viewing angle. Published by the American Physical Society 2024

Unfiltering of the EarthCARE Broadband Radiometer (BBR) observations: the BM-RAD product

Abstract. The methodology to determine the unfiltered solar and thermal radiances from the measured EarthCARE Broadband Radiometer (BBR) shortwave (SW) and total-wave (TW) filtered radiances is presented. Within the EarthCARE ground processing, the correction for the effect of the BBR spectral responses, the unfiltering, is performed by the so-called BM-RAD processor which produces the level-2 BM-RAD product. The BM-RAD product refers to unfiltered broadband radiances that are derived from the BBR and the Multi-Spectral Imager (MSI) instruments on board the forthcoming EarthCARE satellite. The method is based on theoretical regressions between filtered and unfiltered radiances, as is done for the Clouds and the Earth's Radiant Energy System (CERES) and the Geostationary Earth Radiation Budget (GERB) instruments. The regressions are derived from a large geophysical database of spectral radiance curves simulated using radiative transfer models. Based on the radiative transfer computations, the unfiltering error, i.e., the error introduced by the small spectral variations of the BBR instrument response, is expected to remain well below 0.5 % in the shortwave (SW) and 0.1 % in the longwave (LW), at 1 standard deviation. These excellent performances are permitted by the very simple optics used in the BBR instrument: a telescope with a single paraboloid mirror. End-to-end verification of the unfiltering algorithm has been performed by running the BM-RAD processor on modelled level-1 BBR radiances obtained for three EarthCARE orbits simulated by an integrated forecasting and data assimilation system. The resulting unfiltered radiances are eventually compared to the solar and thermal radiances derived by radiative transfer simulations over the three EarthCARE orbits. In addition, this end-to-end verification has provided further evidence on the high accuracy of the unfiltered radiance process, with accuracies better than 0.5 % for SW and better than 0.1 % for LW.

A Machine Learning Method to Retrieve Global Rainfall and Snowfall Rates From the Passive Microwave Observations of FY‐3E

AbstractPassive microwave radiometers onboard satellites rely on the received upwelling radiation to retrieve precipitation, which is a mixed signal from the surface, atmosphere and precipitation hydrometeors. Liquid precipitation droplets increase the upwelling radiation from the surface at lower frequencies, while ice particles cause a decrease in upwelling radiation at higher frequencies. The task of the retrieval algorithm is to identify the precipitation phase and to isolate the signal of precipitation from that of the surface. This study develops a machine learning method to retrieve rainfall and snowfall rates based on observations from the Microwave Hydrometer Sounder and Microwave Temperature Sounder onboard FY‐3E. Self‐organized mapping (SOM) is selected to classify the precipitation and underlying surface types, and an artificial neural network (ANN) is subsequently used to relate the brightness temperature to the precipitation rate for the clusters derived from the SOM. The half‐hour product of the Integrated Multi‐Satellite Retrieval for Global Precipitation Measurement (IMERG) is used to train the ANN. To address the issue that number of heavy precipitation samples are not enough for training, the simulation of radiative transfer for TOVS is used as a supplement to heavy rain samples. The SOM‐ANN algorithm outperforms the IMERG and Goddard profiling algorithm (GPROF) retrieval products in both rainfall and snowfall retrieval. Compared with the hourly observations at ∼4,400 stations during a 2‐year period, the root mean square errors of SOM‐ANN proposed here are 1.06 and 0.34 mm/hr for the rainfall and snowfall rates, which are better than those of IMERG (1.23 and 0.42 mm/hr) and GPROF (1.22 and 0.44 mm/hr).

Robustness of direct measurements of the mean free path of ionizing photons in the epoch of reionization

Abstract Measurements of the mean free path of Lyman-continuum photons in the intergalactic medium during the epoch of reionization can help constrain the nature of the sources as well as sinks of hydrogen-ionizing radiation. A recent approach to this measurement has been to utilize composite spectra of multiple quasars at z ∼ 6, and infer the mean free path after correcting the spectra for the presence of quasar proximity zones. This has revealed not only a steep drop in the mean free path from z = 5 to z = 6, but also potentially a mild tension with reionization simulations. We critically examine such direct measurements of the mean free path for biases due to quasar environment, incomplete reionization, and quasar proximity zones. Using cosmological radiative transfer simulations of reionization combined with one-dimensional radiative transfer calculations of quasar proximity zones, we find that the bias in the mean free path due to overdensities around quasars is minimal at z ∼ 6. Patchiness of reionization at this redshift also does not affect the measurements significantly. Fitting our model to the data results in a mean free path of $\lambda _{\mathrm{mfp}}=1.49^{+0.47}_{-0.52}$ pMpc at z = 6, which is consistent with the recent measurements in the literature, indicating robustness with respect to the modelling of quasar proximity zones. We also compare various ways in which the mean free path has been defined in simulations before the end of reionization. Overall, our finding is that recent measurements of the mean free path appear to be robust relative to several sources of potential bias.

Extending the use of normal hemispherical transmittance ([formula omitted]) measurements by modeling 3D multiple scattering radiative transfer

Spectrophotometers or optical benches using integrating spheres to measure normal-hemispherical transmittance TNH are widespread laboratory equipments. Although it is known that they cannot be used for ”highly turbid” samples, because multiple scattering may lead transmitted radiation to miss the entrance of the integrating sphere, very little is generally known about their exact validity range. Here we present a method to characterize the validity range of any such spectrophotometer and observe that most of them fail to measure TNH for scattering optical thickness above 0.25 (i.e. for TNH<0.9 in the case of non absorbing media with g=0). We also show how it is possible to continue using spectrophotometers even outside their TNH measurement validity range, without any calibration, thanks to a proper simulation of radiative transfer and geometrical optics. We make available the corresponding radiative transfer simulation tools as open access codes, that have been developed for a straightforward implementation on a wide range of experimental setups. The method is validated on three different spectrophotometers or optical benches using standardized latex microspheres, then its practical implementation is illustrated in the case of semi-conductor particles and photosynthetic microalgae. Errors in analysis arising from the misuse of such optical devices are discussed throughout the article.

Radiative transfer simulations of water-leaving radiance from the Skylight-Blocked Approach

Radiative transfer simulations of measurements performed with the Skylight-Blocked Approach (SBA) for water exhibiting diverse optical properties confirmed the non-negligible impact of the depth z0 of the radiometer shield in the determination of the water-leaving radiance Lw. In particular, results showed that the shield-shaded water volume lowers the measured Lw value by a few up to tens of percent as a function of the depth z0, water attenuation, and wavelength. The study also confirmed the potential applicability of an analytical correction scheme based on the sole water absorption and backscattering coefficients to support operational SBA measurements, still at the expense of decreased accuracy with increasing depth z0 and water turbidity.

Primary and secondary source of energy in the superluminous supernova 2018ibb

We examined a possible pair-instability origin for the superluminous supernova 2018ibb. As the base model, we used a non-rotating stellar model with an initial mass of 250 at about 1/15 solar metallicity. We considered three versions of the model as input for radiative transfer simulations done with the stella and artis codes: with 25 of 56Ni, with 34 of 56Ni, and a chemically mixed case with 34 of 56Ni. We present light curves and spectra in comparison to the observed data of SN\,2018ibb, and conclude that the pair-instability supernova model with 34 of 56Ni explains the broadband light curves reasonably well between $-100$ and 250 days around the peak. Our synthetic spectra have many similarities with the observed spectra. The luminosity excess in the light curves and the blue-flux excess in the spectra can be explained by an additional energy source, which may be an interaction of the supernova ejecta with circumstellar matter. We discuss possible mechanisms that could have caused the circumstellar matter to be ejected in the decades before the pair-instability explosion.

Holistic optical water type classification for ocean, coastal, and inland waters

AbstractWater constituents exhibit diverse optical properties across ocean, coastal, and inland waters, which alter their remote‐sensing reflectance obtained via satellites. Optical water type (OWT) classifications utilized in satellite data processing aim to mitigate optical complexity by identifying fitting ocean color algorithms tailored to each water type. This facilitates comprehension of biogeochemical cycles ranging from local to global scales. Previous OWT frameworks have focused narrowly on either oceanic or inland waters and have relied too heavily on specific data collections. We propose a novel holistic OWT framework applicable to all natural waters, based on state‐of‐the‐art bio‐geo‐optical modeling and radiative transfer simulations that encompass different phytoplankton groups. This framework employs a “knowledge‐driven” paradigm, combining domain knowledge and insights from previous studies to simulate the reflectance spectrum from water constituent concentrations and inherent optical properties. Our method extracts optical variables to represent the full spectrum of reflectance, consolidating both spectral shape and magnitude. We apply the framework utilizing diverse in situ, synthetic, and satellite data (Sentinel‐3 OLCI) and demonstrate its better classifiability than other frameworks. This framework lays the foundation for comprehensive global monitoring of natural waters.

The hydrodynamic response of small-scale structure to reionization drives large IGM temperature fluctuations that persist to z = 4

ABSTRACT The thermal history and structure of the intergalactic medium (IGM) at $z \ge 4$ is an important boundary condition for reionization, and a key input for studies using the Ly $\alpha$ forest to constrain the masses of alternative dark matter candidates. Most such inferences rely on simulations that lack the spatial resolution to fully resolve the hydrodynamic response of IGM filaments and minihaloes to H i reionization heating. In this letter, we use high-resolution hydrodynamic + radiative transfer simulations to study how these affect the IGM thermal structure. We find that the adiabatic heating and cooling driven by the expansion of initially cold gas filaments and minihaloes sources significant small-scale temperature fluctuations. These likely persist in much of the IGM until $z \le 4$. Capturing this effect requires resolving the clumping scale of cold, pre-ionized gas, demanding spatial resolutions of ${\le} 2$ $h^{-1}$kpc. Pre-heating of the IGM by X-rays can slightly reduce the effect. Our preliminary estimate of the effect on the Ly $\alpha$ forest finds that, at $\log (k /[{\rm km^{-1} s}]) = -1.0$, the Ly $\alpha$ forest flux power (at fixed mean flux) can increase ${\approx} 10~{{\ \rm per\ cent}}$ going from 8 and 2 $h^{-1}$kpc resolution at $z = 4{\!-\!}5$ for gas ionized at $z \ \lt\ 7$. These findings motivate more careful analyses of how the effects studied here affect the Ly $\alpha$ forest.

The first microwave and submillimetre closure study using particle models of oriented ice hydrometeors to simulate polarimetric measurements of ice clouds

Abstract. The first closure study involving passive microwave and submillimetre measurements of ice clouds with the consideration of oriented particles is presented, using a unique combination of polarised observations from the ISMAR spectral-like radiometer, two radars with frequencies of 35 and 95 GHz, and a variety of in situ instruments. Of particular interest to this study are the large V–H polarised brightness temperature differences measured from ISMAR above a thick frontal ice cloud. Previous studies combining radar and passive submillimetre measurements have not considered polarisation differences. Moreover, they have assumed particle habits a priori. We aim to test whether the large V–H measurements can be simulated successfully by using an atmospheric model consistent with in situ microphysics. An atmospheric model is constructed using information from the in situ measurements, such as the ice water content, the particle size distribution, and the mass and shape of particles, as well as background information obtained from dropsonde profiles. Columnar and dendritic aggregate particle models are generated specifically for this case, and their scattering properties are calculated using the independent monomer approximation under the assumption of horizontal orientation. The scattering properties are used to perform polarised radiative transfer simulations using ARTS to test whether we can successfully simulate the measured large V–H differences. Radar measurements are used to extrapolate the 1-D microphysical profile to derive a time series of particle size distributions which are used to simulate ISMAR brightness temperatures. These simulations are compared to the observations. It is found that particle models that are consistent with in situ microphysics observations are capable of reproducing the brightness temperature depression and polarisation signature measured from ISMAR at the dual-polarised channel of 243 GHz. However, it was required that a proportion of the particles were changed in order to increase the V–H polarised brightness temperature differences. Thus, we incorporated millimetre-sized dendritic crystals, as these particles were observed in the probe imagery. At the second dual-polarised channel of 664 GHz, the brightness temperature depressions were generally simulated at the correct locations; however, the simulated V–H was too large. This work shows that multi-frequency polarisation information could be used to infer realistic particle shapes, orientations, and representations of the split between single crystals and aggregates within the cloud.

Monte Carlo Method for Numerical Simulation of Solar Energy Radiation Transfer in Crystal Clouds

Monte Carlo Method for Numerical Simulation of Solar Energy Radiation Transfer in Crystal Clouds

On the impact of radiative transfer in fluorescence imaging of bacterial films and suspensions

Fluorescence imaging and spectroscopy are convenient, rapid, and simple methods to analyze chemical samples including biological materials such as bacterial biofilms and suspensions. In principle, these techniques could be used to diagnose or discriminate between infectious bacteria in infections of the skin or ocular surface (microbial keratitis, MK). However, the extension of these techniques to macroscopic turbid media that strongly absorb and scatter light is difficult. Radiative transfer effects obscure the relationship between microscopic scattering and absorption properties and macroscopically observable quantities such as fluorescence intensity, transmission, and reflection. A combination of experimental measurements of aqueous bacteria cell suspensions and Monte Carlo radiation transfer simulations are performed to better understand these effects. Several general observations, e.g., that fluorescence intensity is maximized in scattering-dominated media, are discussed in detail. It was found that wavelength-dependent radiative transfer effects are observable even at moderate optical densities (OD ∼ 1; well below the diffusion limit). Careful consideration of radiative transfer effects using physically rigorous models is needed to determine single-cell scattering and absorption properties and interpret quantitative fluorescence measurements accurately in most cases of interest. A detailed discussion of radiative transfer effects and analytical models is provided. In the context of surface infections and MK, it was found that radiative transfer effects may be negligible for the model bacteria E. coli in some cases. However, more accurate measurements of microbe optical properties are needed to confirm and extend this conclusion to other species. Overall this work demonstrates that quantitative fluorescence imaging and spectroscopy of bacterial films and suspensions is feasible, but requires detailed sample characterization and careful consideration of radiative transfer effects.

Расчеты сжатия сферической слоистой системы ударными волнами с учетом переноса тепла излучением в различных приближениях

Numerical modeling is one of the basic tools to investigate physical phenomena that occur in materials compressed by shock waves. A study of the behavior of shock waves using simplified models is helpful in the analysis of more complex systems, for instance, in the problems of inertial thermonuclear fusion on laser facilities. Mathematical simulation of the nonstationary radiative heat transfer in a spectral kinetic statement is rather complicated because the system of equations is nonlinear and large in size. Generally, the kinetic transport equation is solved in 7D phase space, which requires huge computational resources. The initial system is often approximated under certain assumptions but this immediately causes questions as to whether the simplified model is applicable to particular calculations. In this study, several economic radiative heat transfer models were implemented in a 2D hydrodynamic code. Based on these models, test calculations were performed to simulate the compression of a layered spherical system by shock waves, taking into account radiative heat transfer. When the shock wave reaches the center of the sphere, it is focused and reflected. In the neighborhood of the focal point of a converging wave, temperature gradients increase; therefore, thermal conduction and radiation become the main mechanisms of energy dissipation to be considered when taking into account heat transfer. Maximum densities and temperatures at the center of the sphere and their average values in its regions were calculated. In addition, the time when shock and heat waves cross the sphere center was determined, and their behavior before and after focusing at the sphere center was estimated. It is shown that solutions to such problems can be found much faster and with adequate accuracy when applying simplified models.

Anomalous trends in global ocean carbon concentrations following the 2022 eruptions of Hunga Tonga-Hunga Ha’apai

We report on observed trend anomalies in climate-relevant global ocean biogeochemical properties, as derived from satellite ocean color measurements, that show a substantial decline in phytoplankton carbon concentrations following eruptions of the submarine volcano Hunga Tonga-Hunga Ha’apai in January 2022. The anomalies are seen in remotely-sensed ocean color data sets from multiple satellite missions, but not in situ observations, thus suggesting that the observed anomalies are a result of ocean color retrieval errors rather than indicators of a major shift in phytoplankton carbon concentrations. The enhanced concentration of aerosols in the stratosphere following the eruptions results in a violation of some fundamental assumptions in the processing algorithms used to obtain marine biogeochemical properties from satellite radiometric observations, and it is demonstrated through radiative transfer simulations that this is the likely cause of the anomalous trends. We note that any future stratospheric aerosol disturbances, either natural or geoengineered, may lead to similar artifacts in satellite ocean color and other remote-sensing measurements of the marine environment, thus confounding our ability to track the impact of such events on ocean ecosystems.

Quantitative modelling of type Ia supernovae spectral time series: Constraining the explosion physics

Abstract Multiple explosion mechanisms have been proposed to explain type Ia supernovae (SNe Ia). Empirical modelling tools have also been developed that allow for fast, customised modelling of individual SNe and direct comparisons between observations and explosion model predictions. Such tools have provided useful insights, but the subjective nature with which empirical modelling is performed makes it difficult to obtain robust constraints on the explosion physics or expand studies to large populations of objects. Machine learning accelerated tools have therefore begun to gain traction. In this paper, we present riddler, a framework for automated fitting of SNe Ia spectral sequences up to shortly after maximum light. We train a series of neural networks on realistic ejecta profiles predicted by the W7 and N100 explosion models to emulate full radiative transfer simulations and apply nested sampling to determine the best-fitting model parameters for multiple spectra of a given SN simultaneously. We show that riddler is able to accurately recover the parameters of input spectra and use it to fit observations of two well-studied SNe Ia. We also investigate the impact of different weighting schemes when performing quantitative spectral fitting and show that best-fitting models and parameters are highly dependent on the assumed weighting schemes and priors. As spectroscopic samples of SNe Ia continue to grow, automated spectral fitting tools such as riddler will become increasingly important to maximise the physical constraints that can be gained in a quantitative and consistent manner.