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At least 847 records · Page 47

Modeling Wavelength Dependent Mid-infrared (5.5–25 μm) Optical Constants of Silicate Glasses: A Genetic Algorithm Approach

Wavelength-dependent mid-infrared (400–1,800 cm -1 ; 5.56–25 μm) optical constants (real and imaginary indices of refraction; n and k) are determined using reflectance spectra at a spectral sampling of 4 cm -1 for several silicate glasses of varying SiO 2 wt% which include (a) basaltic volcanic glass from Kilauea, Hawaii, (b) synthetic andesite, (c) two synthetic dacites, (d) obsidian volcanic glass from Mount Lassen, California, (e) synthetic rhyodacite, and (f) rhyolitic volcanic glass from Mexico. Because glasses are optically isotropic, no specific orientation was required for spectral measurements, and polished glass samples were measured at random orientations using micro-FTIR spectrometer. Lorentz-Lorenz dispersion theory and Fresnel reflectance model for high symmetry materials were used to model the optical constants by optimizing oscillator parameters in modeled spectra to match laboratory spectra. A genetic algorithm (GA) approach automatically finds the natural oscillators and their parameters for each spectrum, and then uses these parameters in a non-linear least squares optimization routine. The study compared spectral parameters such as Christiansen feature, reststrahlen bands (RBs), and the peaks centered around 860–1,100 (peak 1) and 400–480 cm -1 (peak 2) of n and k to their respective SiO 2 wt% of the glasses. CF, RBs, peak 1 of n and k, and peak 2 of n shift to higher wavenumbers with increased SiO 2 wt%, whereas peak 2 of k shifts to lower wavenumbers with increased SiO 2 wt%. Derived optical constants of these glasses will improve quantitative abundance mapping of volcanic materials on the surfaces of silicate targets in the Solar System.

58 GEOSCIENCES↗

Hybridized Exciton-Photon-Phonon States in a Transition Metal Dichalcogenide van der Waals Heterostructure Microcavity

Excitons in atomically thin transition-metal dichalcogenides (TMDs) have been established as an attractive platform to explore polaritonic physics, owing to their enormous binding energies and giant oscillator strength. Basic spectral features of exciton polaritons in TMD microcavities, thus far, were conventionally explained via two-coupled-oscillator models. This ignores, however, the impact of phonons on the polariton energy structure. Here we establish and quantify the threefold coupling between excitons, cavity photons, and phonons. For this purpose, we employ energy-momentum-resolved photoluminescence and spatially resolved coherent two-dimensional spectroscopy to investigate the spectral properties of a high-quality-factor microcavity with an embedded WSe 2 van der Waals heterostructure at room temperature. Our approach reveals a rich multibranch structure which thus far has not been captured in previous experiments. Simulation of the data reveals hybridized exciton-photon-phonon states, providing new physical insight into the exciton polariton system based on layered TMDs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Exploring Changes in Quasar Spectral Energy Distributions across C IV Parameter Space

We examine the UV/X-ray properties of 1378 quasars in order to link empirical correlations to theoretical models of the physical mechanisms dominating quasars as a function of mass and accretion rate. The clarity of these correlations is improved when (1) using C IV broad emission line equivalent width (EQW) and blueshift (relative to systemic) values calculated from high signal-to-noise ratio reconstructions of optical/UV spectra and (2) removing quasars expected to be absorbed based on their UV/X-ray spectral slopes. In addition to using the traditional C IV parameter space measures of C IV EQW and blueshift, we define a "C IV ∥ distance" along a best-fit polynomial curve that incorporates information from both C IV parameters. We find that the C IV ∥ distance is linearly correlated with both the optical-to-X-ray slope, α ox , and broad-line He II EQW, which are known spectral energy distribution indicators, but does not require X-ray or high spectral resolution UV observations to compute. The C IV ∥ distance may be a better indicator of the mass-weighted accretion rate, parameterized by L/L Edd , than the C iv EQW or blueshift alone, as those relationships are known to break down at the extrema. Conversely, there is only a weak correlation with the X-ray energy index (Γ), an alternate L/L Edd indicator. We find no X-ray or optical trends in the direction perpendicular to the C IV distance that could be used to reveal differences in accretion disk, wind, or corona structure that could be widening the C IV EQW–blueshift distribution. A different parameter (such as metallicity) not traced by these data must come into play.

79 ASTRONOMY AND ASTROPHYSICS↗

Hyper Spectral Anomaly Detection

Anomaly detection is a common machine learning (ML) task with growing importance in the fields of imaging, quality assurance, and multiple security related disciplines. Anomaly detection is more difficult than traditional machine learning methods due to the inherent unlabeled nature of the datasets. Existing anomaly detection architectures commonly face challenges with explainability, retaining information related to the relational structure of the data, and false positive rates. Hyperspectral Imaging Anomaly Detection (HSI) is a statistical model that employs vertex and edge weighted graphs to preserve the data’s relationships on different topographical scales. The model is able to generalize from anomaly detection in 2D images to novel datasets related to cyber-security. Furthermore, the use of multi-spectral and other filtering methods results in fewer false positives and increases the explainability of model predictions. When applying HSI to cyber-security datasets, we are able to successfully detect malicious activity with a relatively high degree of accuracy.

97 - MATHEMATICS AND COMPUTING↗

Traces of electron-phonon coupling in one-dimensional cuprates

Abstract The appearance of certain spectral features in one-dimensional (1D) cuprate materials has been attributed to a strong, extended attractive coupling between electrons. Here, using time-dependent density matrix renormalization group methods on a Hubbard-extended Holstein model, we show that extended electron-phonon ( e–ph ) coupling presents an obvious choice to produce such an attractive interaction that reproduces the observed spectral features and doping dependence seen in angle-resolved photoemission experiments: diminished 3 k F spectral weight, prominent spectral intensity of a holon-folding branch, and the correct holon band width. While extended e–ph coupling does not qualitatively alter the ground state of the 1D system compared to the Hubbard model, it quantitatively enhances the long-range superconducting correlations and suppresses spin correlations. Such an extended e–ph interaction may be an important missing ingredient in describing the physics of the structurally similar two-dimensional high-temperature superconducting layered cuprates, which may tip the balance between intertwined orders in favor of uniform d -wave superconductivity.

36 MATERIALS SCIENCE↗

SDSS-IV MaStar: theoretical atmospheric parameters for the MaNGA stellar library

ABSTRACT We calculate the fundamental stellar parameters effective temperature, surface gravity, and iron abundance – Teff, log g, [Fe/H] – for the final release of the Mapping Nearby Galaxies at APO (MaNGA) Stellar Library (MaStar), containing 59 266 per-visit-spectra for 24 290 unique stars at intermediate resolution (R ∼ 1800) and high S/N (median = 96). We fit theoretical spectra from model atmospheres by both MARCS and BOSZ-ATLAS9 to the observed MaStar spectra, using the full spectral fitting code pPXF. We further employ a Bayesian approach, using a Markov Chain Monte Carlo (MCMC) technique to map the parameter space and obtain uncertainties. Originally in this paper, we cross match MaStar observations with Gaia photometry, which enable us to set reliable priors and identify outliers according to stellar evolution. In parallel to the parameter determination, we calculate corresponding stellar population models to test the reliability of the parameters for each stellar evolutionary phase. We further assess our procedure by determining parameters for standard stars such as the Sun and Vega and by comparing our parameters with those determined in the literature from high-resolution spectroscopy (APOGEE and SEGUE) and from lower resolution matching template (LAMOST). The comparisons, considering the different methodologies and S/N of the literature surveys, are favourable in all cases. Our final parameter catalogue for MaStar cover the following ranges: 2592 ≤ Teff ≤ 32 983 K; −0.7 ≤ log g ≤ 5.4 dex; −2.9 ≤ [Fe/H] ≤ 1.0 dex and will be available with the last SDSS-IV Data Release, in 2021 December.

79 ASTRONOMY AND ASTROPHYSICS↗

Factors That Influence Variability in Stress-Drop Measurements Using Spectral Decomposition and Spectral-Ratio Methods for the 2019 Ridgecrest Earthquake Sequence

Stress drop is a fundamental parameter related to earthquake source physics, but is hard to measure accurately. To better understand how different factors influence stress-drop measurements, we compare two different methods using the Ridgecrest stress-drop validation data set: spectral decomposition (SD) and spectral ratio (SR), each with different processing options. Here, we also examine the influence of spectral complexity on source parameter measurement. Applying the SD method, we find that frequency bandwidth and time-window length could influence spectral magnitude calibration, while depth-dependent attenuation is important to correctly map stress-drop variations. For the SR method, we find that the selected source model has limited influence on the measurements; however, the Boatwright model tends to produce smaller standard deviation and larger magnitude dependence than the Brune model. Variance reduction threshold, frequency bandwidth, and time-window length, if chosen within an appropriate parameter range, have limited influence on source parameter measurement. For both methods, wave type, attenuation correction, and spectral complexity strongly influence the result. The scale factor that quantifies the magnitude dependence of stress drop show large variations with different processing options, and earthquakes with complex source spectra deviating from the Brune-type source models tend to have larger scale factor than earthquakes without complexity. Based on these detailed comparisons, we make a few specific suggestions for data processing workflows that could help future studies of source parameters and interpretations.

58 GEOSCIENCES↗

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗

Sustainability Trait Modeling of Field-Grown Switchgrass ( Panicum virgatum ) Using UAV-Based Imagery

Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this study, we used UAV-based remote sensing for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. Using vegetation indices calculated from a UAV-based multispectral camera, statistical models were developed for rust disease caused by Puccinia novopanici, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potentials for multiple traits associated with sustainable production of switchgrass, and one statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait. Also, for the first time, lignin content was estimated in switchgrass shoots via UAV-based multispectral image analysis and statistical analysis. The UAV-based models were verified by ground-truthing via correlation analysis between the traits measured manually on the ground-based with UAV-based data. The normalized difference red edge (NDRE) vegetation index outperformed the normalized difference vegetation index (NDVI) for rust disease and nitrogen content, while NDVI performed better than NDRE for chlorophyll and lignin content. Overall, linear models were sufficient for rust disease and chlorophyll analysis, but for nitrogen and lignin contents, nonlinear models achieved better results. As the first comprehensive study to model switchgrass sustainability traits from UAV-based remote sensing, these results suggest that this methodology can be utilized for switchgrass high-throughput phenotyping in the field.

60 APPLIED LIFE SCIENCES↗

Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94 compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

Single pion production and pion propagation in A chilles

We extend the applicability of A chilles (A CHIcagoLand Lepton Event Simulator) by incorporating the single pion production mechanism in a fully exclusive fashion. The electroweak interaction vertex is modeled by combining the state-of-the-art dynamical coupled-channels approach with realistic hole spectral functions, which account for correlations in both the initial target state and the residual spectator system. Final-state interactions are treated using a semiclassical intranuclear cascade that leverages nuclear configurations to determine the correlated spatial distribution of protons and neutrons. The meson-baryon scattering amplitudes used in the cascade are computed within the dynamical coupled-channels framework, consistent with the electroweak vertex. To model pion absorption, we employ the optical potential approach of Oset and Salcedo [Nucl. Phys. A484, 557 (1988).]. As an alternative approach, we explicitly model the production and propagation of resonances which mediate pion-nucleon scattering and pion absorption. We validate our approach against pion-nucleon and pion-nucleus scattering data, and present comparisons with electron- and neutrino-nucleus measurements from e⁢4⁢𝜈, T2K, MINER⁢𝜈⁢A, and MicroBooNE.

Isaacson, Joshua [Michigan State Univ., East Lansi↗

Quantifying Temperature Dependence of Pu(IV) Absorbance Spectra for Advanced Online Monitoring of Nuclear Processes

This article presents a systematic study of Pu(IV) absorbance spectral features as a function of temperature to develop an understanding of this parameter’s effect on chemometric models that can be used as online monitoring tools to support nuclear processing. The descriptive and predictive models that provide real-time feedback of these processes are usually constructed with data collected in conditions typical of a laboratory environment, which can differ drastically from a processing environment. To assess the impact of temperature on Pu(IV) absorbance spectra, 11 samples of Pu(IV) were synthesized with varying HNO 3 concentrations ranging from 0.6 to 9.5 M and heated between 15 and 45 °C. Ultraviolet (UV)–visible (vis)–near-infrared (NIR) absorption spectra collected at different HNO 3 concentrations and temperatures revealed that features associated with Pu(IV) are sensitive to temperature at all HNO 3 concentrations and that changes in features depend on HNO 3 concentration. The contributions of temperature and HNO 3 concentration to variation in Pu(IV) spectral features were evaluated using the principal component analysis of spectra that were baseline-corrected with an asymmetric least-squares method. Furthermore, predictive modeling for HNO 3 concentration with partial least-squares regression of UV–vis–NIR spectra highlighted the importance of accounting for temperature in the calibration set to optimize model performance. This methodology constitutes a new, systematic approach to account for the effect of temperature on the absorption spectra of metal ions and is useful for process monitoring applications in many industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Majorana modes with side features in magnet-superconductor hybrid systems

Magnet-superconductor hybrid (MSH) systems represent promising platforms to host Majorana zero modes (MZMs), the elemental building blocks for fault-tolerant quantum computers. Theoretical description of such MSH structures is mostly based on simplified models, not accounting for the complexity of real materials. Here, based on density functional theory, we derive a superconducting 80-band model to study an MSH system consisting of a magnetic manganese chain on the s wave superconductor niobium. For a wide range of values of the superconducting order parameter, the system is a topological superconductor, with MZMs exhibiting non-universal spatial patterns and a drastic accumulation of spectral weight on both sides along the magnetic chain. These side feature states can be explained by an effective model which is guided by the ab initio results. Performing scanning tunneling spectroscopy experiments on the same system, we observe a spatial structure in the low-energy local density of states that is consistent with the theoretical findings. Our results open a first-principle approach to the discovery of topological superconductors.

36 MATERIALS SCIENCE↗

Characteristics of the Diffuse Astrophysical Electron and Tau Neutrino Flux with Six Years of IceCube High Energy Cascade Data

In this work, we report on the first measurement of the astrophysical neutrino flux using particle showers (cascades) in IceCube data from 2010-2015. Assuming standard oscillations, the astrophysical neutrinos in this dedicated cascade sample are dominated (~90%) by electron and tau flavors. The flux, observed in the sensitive energy range from 16 TeV to 2.6 PeV, is consistent with a single power-law model as expected from Fermi-type acceleration of high energy particles at astrophysical sources. We find the flux spectral index to be γ=2.53±0.07 and a flux normalization for each neutrino flavor of $\phi$ astro =1.66$_{-0.27}^{+0.25}$ at E 0 =100 TeV, in agreement with IceCube's complementary muon neutrino results and with all-neutrino flavor fit results. In the measured energy range we reject spectral indices γ≤2.28 at ≥3σ significance level. Because of high neutrino energy resolution and low atmospheric neutrino backgrounds, this analysis provides the most detailed characterization of the neutrino flux at energies below ~100 TeV compared to previous IceCube results. Results from fits assuming more complex neutrino flux models suggest a flux softening at high energies and a flux hardening at low energies (p value ≥0.06). The sizable and smooth flux measured below ~100 TeV remains a puzzle. In order to not violate the isotropic diffuse gamma-ray background as measured by the Fermi Large Area Telescope, it suggests the existence of astrophysical neutrino sources characterized by dense environments which are opaque to gamma rays.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Measurement of the 2 ν β β Decay Rate and Spectral Shape of Mo 100 from the CUPID-Mo Experiment

Neutrinoless double beta decay (0νββ) is a yet unobserved nuclear process that would demonstrate Lepton number violation, a clear evidence of beyond standard model physics. The process two neutrino double beta decay (2νββ) is allowed by the standard model and has been measured in numerous experiments. In this Letter, we report a measurement of 2νββ decay half-life of 100 Mo to the ground state of 100 Ru of [7.07±0.02(stat)±0.11(syst)]×10 18 yr by the CUPID-Mo experiment. With a relative precision of ±1.6% this is the most precise measurement to date of a 2νββ decay rate in 100 Mo. In addition, we constrain higher-order corrections to the spectral shape, which provides complementary nuclear structure information. We report a novel measurement of the shape factor ξ 3,1 =0.45±0.03(stat)±0.05(syst) based on a constraint on the ratio of higher-order terms from theory, which can be reliably calculated. This is compared to theoretical predictions for different nuclear models. Finally, we also extract the first value for the effective axial vector coupling constant obtained from a spectral shape study of 2νββ decay.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

Abstract Aim Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m). Location Eastern USA. Time period 2017–2018. Taxa studied Trees. Methods With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics. Results Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity. Main conclusions We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.

54 ENVIRONMENTAL SCIENCES↗

SDSS-IV MaStar: [α/Fe] for the MaNGA Stellar Library from synthetic model spectra

ABSTRACT We calculate the α-enhancement ratio [α/Fe] for the Mapping Nearby Galaxies at APO (MaNGA) Stellar Library (MaStar) while also fitting for the fundamental atmospheric parameters effective temperature, surface gravity, and metallicity – Teff, log g, [Fe/H]. This approach builds upon a previous catalogue of stellar parameters, whereby only the fundamental atmospheric parameters are fit with solar-scaled models. Here, we use the same Markov Chain Monte Carlo method with the additional free parameter [α/Fe]. Using the full spectral fitting code pPXF, we are able to fit multiple lines sensitive to [α/Fe] for a more robust measurement. Quality flags based on the convergence of the sampler, errors in [α/Fe] and a cut in the χ2 of the model fit are used to clean the final catalogue, returning 17 214 spectra and values in the range of −0.25 < [α/Fe] < 0.48. Comparing our calculated [α/Fe] with literature values reveals a degeneracy in cool stars with log g ≥ ∼4; this comparison is then used to create an alternative and calibrated parameter set. We also plot the final catalogue in an [Fe/H] versus [α/Fe] diagram and recover the expected result of increasing [α/Fe] with decreasing [Fe/H] for Milky Way disc-halo stars. We apply our method to a subsample of spectra of uniform resolution and higher signal to noise that finds that our results are independent of this higher signal to noise. In the context of stellar population models, we are able to cover a parameter space for the creation of intermediate to old age models at solar-scaled [α/Fe], high [Fe/H] and enhanced [α/Fe], low [Fe/H].

79 ASTRONOMY AND ASTROPHYSICS↗

PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere

Forward models are a key tool to generate synthetic observations given knowledge of the atmospheric state. In this way, they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud-resolving models (CRMs). Herein, CRM profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for upward- and downward-looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing upwelling and downwelling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications and interfaces to many different formats of input and output, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh–Gans approximation (SSRGA) for both active and passive applications, which becomes especially important for the investigation of frozen hydrometeors.

54 ENVIRONMENTAL SCIENCES↗