Observations and Radiative Transfer Simulations of the Carbon-rich AGB Star V Oph with VLTI/MATISSE*
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The development of radiative transfer simulators for radar and microwave signals, spanning a range of frequencies from 10 to 800 GHz, is paramount for enhancing weather forecasting accuracy, particularly for severe weather events. These tools facilitate the assimilation of microwave and radar observations into numerical weather prediction models, thereby improving accuracy of weather forecasts. Additionally, they directly simulate radar signals crucial for autonomous vehicle operation, with frequencies commonly used in radar systems such as 24, 74, 77, and 79 GHz. However, these frequencies are susceptible to weather phenomena like severe rain and snow, which can significantly impact vehicle safety and performance. These simulation tools, including radiative transfer simulators, serve a dual purpose. Firstly, they enhance forecasts for severe weather events, contributing to autonomous vehicle safety by providing early warnings and risk assessments. Secondly, they enable the direct simulation of radar signals in autonomous vehicle driving systems, allowing researchers and engineers to evaluate radar system performance under various weather conditions. In addition to the radar signal simulator, this abstract discusses the incorporation of advanced scattering properties developed using the discrete dipole approximation (DDA). The DDA technique enhances scattering calculations for frozen hydrometeors at microwave frequencies, thereby improving the accuracy of radar signal simulations and enabling more accurate assessments of radar system performance in adverse weather conditions. In summary, this abstract explores the development and utilization of comprehensive simulation tools, emphasizing their significance in simulating microwave and radar signals and improving weather forecasts. Special attention is given to the simulation of radar signals at critical frequencies for autonomous vehicle sensing and navigation, addressing challenges posed by severe weather phenomena and their effects on signal propagation and detection
The CPU allocation was primarily used for nucleosyn thesis calculations using LANL’s PRISM code, radiative transfer simulations using LANL’s SuperNu code, and parameter inference of the radiative transfer simulations. Below, I document all relevant publications where Inti tutional Computing (IC) resources were used in relation to this allocation and their scientific impacts.
A generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data has been developed. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must depend on the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (+/-55.4 deg and +/-55 deg from nadir for AVHRR and MODIS, respectively) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error by using results from systematic radiative transfer simulations over wide ranges of surface temperatures and emissivities, and atmospheric water vapor abundance and temperatures. Simulations indicated that as atmospheric column water vapor increases and viewing angle is larger than 45 deg it is necessary to optimize the split-window method by separating the ranges of the atmospheric column water vapor and lower boundary temperature, and the surface temperature into tractable sub-ranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range where the optimum coefficients of the split-window method are given. This new LST algorithm not only retrieves LST more accurately but also is less sensitive than viewing-angle independent LST algorithms to the uncertainty in the band emissivities of the land-surface in the split-window and to the instrument noise.
Satellite-based hyperspectral observations provide high information content for the Earth's atmospheric and surface properties; however, in order to analyze hyperspectral data efficiently, fast and accurate radiative transfer model is needed. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate radiative transfer in the cloudy atmosphere from far IR to visible and UV spectral regions quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. The computation speed is 3 to 4 orders of magnitude faster than the medium speed correlated-k option MODTRAN5 and LBLRTM. The PCRTM calculated radiance spectra agree with the Modtran and LBLRTM within 0.02%. We will demonstrate the application of the PCRTM forward model for atmospheric and surface property inversions and for climate observation studies.
A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TMþIGOM are considered as a benchmark because the IITM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TMþIGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 micrometers) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical thickness and effective diameter. In the MODIS infrared window bands centered at 8.5, 11, and 12 micrometers biases in the optical thickness and effective diameter are up to 12% and 10%, respectively. The CGOM-based simulation errors in ice cloud radiative forcing calculations are on the order of 10Wm(exp 2).
The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.
Stripped-envelope supernovae (SESNe) represent a significant fraction of core-collapse supernovae, arising from massive stars that have shed their hydrogen and, in some cases, helium envelopes. The origins and explosion mechanisms of SESNe remain a topic of active investigation. In this work, we employ radiative-transfer simulations to model the light curves and spectra of a set of explosions of single, solar-metallicity, massive Wolf–Rayet stars with ejecta masses ranging from 4 to 11 M ⊙ , which were computed from a turbulence-aided and neutrino-driven explosion mechanism. We analyze these synthetic observables to explore the impact of varying ejecta mass and helium content on observable features. We find that the light curve shape of these progenitors with high ejecta masses is consistent with observed SESNe with broad light curves but not the peak luminosities. The commonly used analytic formula based on rising bolometric light curves overestimates the ejecta mass of these high-initial-mass progenitor explosions by a factor of up to 2.6. In contrast, the calibrated method by Haynie et al., which relies on late-time decay tails, reduces uncertainties to an average of 20% within the calibrated ejecta mass range. Spectroscopically, the He I 1.083 μm line remains prominent even in models with as little as 0.02 M ⊙ of helium. However, the strength of the optical He I lines is not directly proportional to the helium mass but instead depends on a complex interplay of factors such as the 56 Ni distribution, composition, and radiation field. Thus, producing realistic helium features requires detailed radiative transfer simulations for each new hydrodynamic model.
In order to find the best observable diagnostics for the amount of internal extinction within spiral galaxies, we have constructed realistic models for disk galaxies with immersed dust layers. The radiative transfer including both scattering and absorption has been computed for a range of model galaxies in various orientations. Standard galaxy surface photometry techniques were then applied to the numerical data to illustrate how different observables such as total magnitude, color and luminosity distribution behave under given conditions of dust distribution. This work reveals a set of superior diagnostics for the dust in the disk. These include not only the integrated parameters, but also the apparent disk structural parameters, the amplitude of the asymmetry between the near and far sides of the galaxy as divided by the apparent major axis and their dependence on the orientation of the galaxy with respect to the observer. Combining the above diagnostics with our impressions of real galaxies, we arrive at the qualitative conclusion that galaxy disks are generally optically thin. Quantitative conclusions will appear in subsequent work.
The fluid dynamics of falling hydrometeors often results in preferential orientations that can affect both the intensity and polarization of electromagnetic radiation. In order to properly interpret remote sensing observations of ice and snow, such alignments should be considered when constructing databases of scattering particles; however, the inclusion of aligned particles increases the complexity of the scattering data. To demonstrate the use of scattering properties of preferentially-aligned particles, millimeter-wave brightness temperatures and radar observables, including reflectivity and linear depolarization ratio, are modeled using the Atmospheric Radiative Transfer Simulator (ARTS). The necessary scattering parameters for vector radiative transfer, particularly with respect to ARTS, are reviewed, and the exploitation of particle symmetries, as well as scattering reciprocity relationships, are detailed.
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The term “hotspot” refers to the sharp increase of reflectance occurring when incident (solar) and reflected (viewing) directions almost coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications. The RossThick-LiSparse-Reciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is widely used in radiative transfer simulations, and the hotspot model mostly used is from Maignan- Bréon but it typically requires large values of numerical quadrature and Fourier expansion terms in order to represent the hotspot accurately. To improve its use in atmospheric radiative transfer (RT) model simulations, in this paper we have developed a modified version based on the Maignan-Bréon’s hotspot BRDF model that converge much faster numerically, making it more practical for use in RT models that require Fourier expansion of BRDF to simulate the top-of-atmosphere (TOA) hotspot signatures. Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), we found that reasonable TOA hotspot accuracy can be obtained with just 23 Fourier terms for clear atmospheres, and 63 Fourier terms for atmospheres with aerosol scattering. One advantage of this modified model is that the new hotspot model agrees very well with the original RossThick model away the hotspot region, making it is very convenient to use in the condition with and without hotspot in applications. This model can calculate the amplitude of hot spot accurately, and has been added in the most recent version of VLIDORT. However, there are some difference of this modified model with the original model for scattering angle close the hot spot, and it may not be appropriate for those who need an exact representation of the hot spot angular signature close to hot spot.
A method is described for determining the water vapor content to within + or - 0.4 g/sq cm from remotely sensed radiances in three infrared channels, 11, 13, 18 microns. Using this method, it is possible to significantly improve the accuracy of sea surface temperature (SST) over what is obtainable with the two channel technique. A radiative computational scheme for the radiative transfer equation is used to study the manner in which the equivalent radiative temperature of the atmosphere changes as a function of wave number for different atmospheric conditions. Average climatological conditions are used to simulate the radiative response of the atmosphere. This radiative transfer simulation is used to compute brightness temperatures for radiosonde profiles obtained from oceanographic ships, which temperatures are in turn used to estimate the SST. Nimbus 4 IRIS spectral measurements corresponding to the profiles were used in the same way for purposes of comparison.
While solar eclipses are known to greatly diminish the visible radiation reaching the surface of the Earth, less is known about the magnitude of the impact. We explore both the observed and modeled levels of change in surface radiation during the eclipse of 2017. We deployed a pyranometer and Pandora spectrometer instrument to Casper, Wyoming, and Columbia, Missouri, to measure surface broadband shortwave (SW) flux and atmospheric properties during the 21 August 2017 solar eclipse event. We performed detailed radiative transfer simulations to understand the role of clouds in spectral and broadband solar radiation transfer in the Earth’s atmosphere for the normal (non-eclipse) spectrum and red-shift solar spectra for eclipse conditions. The theoretical calculations showed that the non-eclipse-to-eclipse surface flux ratio depends strongly on the obscuration of the solar disk and slightly on the cloud optical depth. These findings allowed us to estimate what the surface broadband SW flux would be for hypothetical non-eclipse conditions from observations during the eclipse and further to quantify the impact of the eclipse on the surface broadband SW radiation budget. We found that the eclipse caused local reductions of time-averaged surface flux of about 379 W m−2 (50 %) and 329Wm-2 (46 %) during the ∼3 h course of the eclipse at the Casper and Columbia sites, respectively. We estimated that the Moon’s shadow caused a reduction of approximately 7 %–8% in global average surface broadband SW radiation. The eclipse has a smaller impact on the absolute value of surface flux reduction for cloudy conditions than a clear atmosphere; the impact decreases with the increase in cloud optical depth. However, the relative time-averaged reduction of local surface SW flux during a solar eclipse is approximately 45 %, and it is not sensitive to cloud optical depth. The reduction of global average SW flux relative to climatology is proportional to the non-eclipse and eclipse flux difference in the penumbra area and depends on cloud optical depth in the Moon’s shadow and geolocation due to the change in solar zenith angle. We also discuss the influence of cloud inhomogeneity on the observed SW flux. Our results not only quantify the reduction of the surface solar radiation budget, but also advance the understanding of broadband SW radiative transfer under solar eclipse conditions.
Accurate information about aerosol vertical distribution is needed to reduce uncertainties in aerosol radiative forcing and its effect on atmospheric dynamics. The present study deals with synergistic analyses of aerosol vertical distribution and aerosol optical depth (AOD) with meteorological variables using multisatellite and ground-based remote sensors over Kanpur in central Indo-Gangetic Plain (IGP). Micro-Pulse Lidar Network-derived aerosol vertical extinction (sigma) profiles are analyzed to quantify the interannual and daytime variations during monsoon onset period (May-June) for 2009-2011. The mean aerosol profile is broadly categorized into two layers viz., a surface layer (SL) extending up to 1.5 km (where sigma decreased exponentially with height) and an elevated aerosol layer (EAL) extending between 1.5 and 5.5 km. The increase in total columnar aerosol loading is associated with relatively higher increase in contribution from EAL loading than that from SL. The mean contributions of EALs are about 60%, 51%, and 50% to total columnar AOD during 2009, 2010, and 2011, respectively. We observe distinct parabolic EALs during early morning and late evening but uniformly mixed EALs during midday. The interannual and daytime variations of EALs are mainly influenced by long-range transport and convective capacity of the local emissions, respectively. Radiative flux analysis shows that clear-sky incoming solar radiation at surface is reduced with increase in AOD, which indicates significant cooling at surface. Collocated analysis of atmospheric temperature and aerosol loading reveals that increase in AOD not only resulted in surface dimming but also reduced the temperature (approximately 2-3 C) of lower troposphere (below 3 km altitude). Radiative transfer simulations indicate that the reduction of incoming solar radiation at surface is mainly due to increased absorption by EALs (with increase in total AOD). The observed cooling in lower troposphere in high aerosol loading scenario could be understood as a dynamical feedback of EAL-induced stratification of lower troposphere. Further, the observed radiative effect of EALs increases the stability of the lower troposphere, which could modulate the large-scale atmospheric dynamics during monsoon onset period. These findings encourage follow-up studies on the implication of EALs to the Indian summer monsoon dynamics using numerical models.
Insufficient knowledge of the habit distribution and the degree of surface roughness of ice crystals within ice clouds is a source of uncertainty in the forward light scattering and radiative transfer simulations required in downstream applications involving these clouds. The widely used MODerate Resolution Imaging Spectroradiometer (MODIS) Collection 5 ice microphysical model assumes a mixture of various ice crystal shapes with smooth-facets except aggregates of columns for which a moderately rough condition is assumed. When compared with PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) polarized reflection data, simulations of polarized reflectance using smooth particles show a poor fit to the measurements, whereas very rough-faceted particles provide an improved fit to the polarized reflectance. In this study a new microphysical model based on a mixture of 9 different ice crystal habits with severely roughened facets is developed. Simulated polarized reflectance using the new ice habit distribution is calculated using a vector adding-doubling radiative transfer model, and the simulations closely agree with the polarized reflectance observed by PARASOL. The new general habit mixture is also tested using a spherical albedo differences analysis, and surface roughening is found to improve the consistency of multi-angular observations. It is suggested that an ice model incorporating an ensemble of different habits with severely roughened surfaces would potentially be an adequate choice for global ice cloud retrievals.