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DOE OSTI2023

Nanometer flat blazed x-ray gratings using ion beam figure correction

With the development of nanometer accuracy stitching interferometry, ion beam figuring (IBF) of x-ray mirrors can now be achieved with unprecedented performance. However, the process of producing x-ray diffraction gratings on these surfaces may degrade the figure quality due to process errors introduced during the ruling of the grating grooves. To address this challenge, we have investigated the post-production correction of gratings using IBF, where stitching interferometry is used to provide in-process feedback. A concern with ion beam correction in this case is that ions will induce enough surface mobility of atoms to cause smoothing of the grating structure and degradation of diffraction efficiency. In this study we found however that it is possible to achieve a nanometer-level planarity of the global grating surface with IBF, while preserving the grating structure. The preservation was so good, that we could not detect a change in the diffraction efficiency after ion beam correction. This is of major importance in achieving ultra-high spectral resolution, and the preservation of brightness for coherent x-ray beams.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Development of a triple-moment ice-phase cloud microphysics scheme and its application to the Single Column Atmosphere Model

Parameterization of cloud microphysics is critical for accurate simulation of weather and climate, in which the characteristics of cloud particle spectrum inevitably further affect climate simulation by changing the cloud evolution and cloud radiation effects. The popular currently used double-moment cloud microphysics schemes in numerical models can predict the intercept (N 0 ) and slope (λ) parameters of cloud particle spectrum but cannot predict the spectral shape parameter (μ), which hinders accurate description of cloud physical processes in climate models. Therefore, in the present study, we built upon the ideas of previously developed triple-moment cloud microphysics scheme, considered radar reflectivity factor as the third predictor in addition to number and mass concentration, and introduced its related prediction equation to the Single Column Atmosphere Model Version 5.3 (SCAM5.3). Moreover, the relevant microphysical process formulas in the model were revised, and a triple-moment ice-cloud microphysics scheme was constructed to predict the μ of ice particle spectrum. Based on this model, a 29-day case of the Atmospheric Radiation Measurement Program in the summer of 1997 (ARM97) was simulated, and the differences in cloud fraction and radiation simulations between the double- and triple-moment schemes were analysed. The μ of ice particle spectrum predicted by the triple-moment scheme mainly ranged from 0 to 4; the peak value was around 2, and at least 85% of the μ values were greater than the default 0. Therefore, the μ=0 setting in the double-moment scheme is unreasonable. Moreover, the developed triple-moment ice-cloud microphysics scheme yielded a narrower ice particle spectrum, which was closer to the observation results of previous studies, than the double-moment cloud microphysics scheme (e.g., height=233 hPa). Furthermore, compared with the double-moment scheme, the triple-moment scheme achieved closer simulations of the cloud fraction observations, particularly for ice clouds in the upper levels. Considering the close association between cloud fraction and radiation, the error with the triple-moment scheme was smaller than that with the double-moment scheme regardless of the shortwave (surface downward shortwave radiation, net downward shortwave radiation at the top of the atmosphere, and net shortwave radiation at the surface) or longwave (surface downward longwave radiation and net longwave radiation at the surface) flux density. Finally, the improvement mechanism of the triple-moment scheme on cloud fraction and radiation simulations was explored. The major reason is that the triple-moment scheme weakens the autoconversion of ice crystal to form snow and enhances the growth process of ice crystal deposition, thereby increasing the mass concentration of ice crystals and ice cloud fraction. Overall, the developed triple-moment ice-cloud microphysics scheme can help improve the simulation ability of models for cloud-climate feedback and other processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Real-Time High-Accuracy Digital Wireless Time, Frequency, and Phase Calibration for Coherent Distributed Antenna Arrays

his work presents a fully-digital high-accuracy real-time calibration procedure for frequency and time alignment of open-loop wirelessly coordinated coherent distributed antenna array (CDA) modems, enabling radio frequency (RF) phase coherence of spatially separated commercial off-the-shelf (COTS) software-defined radios (SDRs) without cables or external references such as the global navigation satellite system (GNSS). Building on previous work using high-accuracy spectrally-sparse time of arrival (ToA) waveforms and a multistep ToA refinement process, a high-accuracy two-way time transfer (TWTT)-based time–frequency coordination approach is demonstrated. Due to the two-way nature of the high-accuracy TWTT approach, the time and frequency estimates are Doppler and multipath tolerant, so long as the channel is reciprocal over the synchronization epoch. This technique is experimentally verified using COTS SDRs in a lab environment in static and dynamic scenarios and with significant multipath scatterers. Time, frequency, and phase stability were evaluated by beamforming over coaxial cables to an oscilloscope which achieved time and phase precisions of ~60– 70 ps , with median coherent gains above 99% using optimized coordination parameters, and a beamforming frequency root-mean-square error (RMSE) of 3.73 ppb in a dynamic scenario. Finally, experiments were conducted to compare the performance of this technique with previous works using an analog continuous-wave two-tone (CWTT) frequency reference technique in both static and dynamic settings.

Clock synchronization↗

DOE OSTI2024

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part II: Enforcing the Lorenz Gauge Condition

In a previous paper Christlieb et al. (A particle-in-cell method for plasmas with a generalized momentum formulation, part I: Model formulation, 2024), we developed a new particle-in-cell (PIC) method for the relativistic Vlasov–Maxwell system in which the electromagnetic fields and the equations of motion for the particles were cast in terms of scalar and vector potentials through a Hamiltonian formulation. This new method evolved the potentials under the Lorenz gauge using integral equation methods. New methods to construct spatial derivatives of the potentials that converge at the same rates as the fields were also presented. The new particle method was compared against standard explicit discretizations, including the well-known FDTD-PIC method, for a range of applications involving sheaths and particle beams. Here, this paper extends this new class of methods by focusing on the enforcement the Lorenz gauge condition in both exact and approximate forms using co-located meshes. A time-consistency property of the proposed field solver for the vector potential form of Maxwell’s equations is established, which is shown to preserve the equivalence between the semi-discrete Lorenz gauge condition and the analogous semi-discrete continuity equation. Using this property, we present three methods to enforce a semi-discrete gauge condition. The first method introduces an update for the continuity equation that is consistent with the discretization of the Lorenz gauge condition. Both the finite difference and spectral implementations satisfy this discrete gauge condition to machine precision. The second approach we propose enforces a semi-discrete continuity equation using the boundary integral solution to the field equations. The potential benefit of this approach is that it eliminates spatial derivatives that appear on the particle data, namely the current density, which is often calculated by linear combinations of low-order spline basis functions. This method is ideally suited to boundary integral equation methods that invert multi-dimensional operators without dimensional splitting techniques and will be the subject of future work. The third approach introduces a gauge correcting method that makes direct use of the gauge condition to modify the scalar potential and uses local maps for both the charge and current densities. This results in a gauge error, as the maps do not enforce the continuity equation. The vector potential coming from the current density is taken to be exact, and using the Lorenz gauge, we compute a correction to the scalar potential that makes the two potentials satisfy the gauge condition. This method also enforces the gauge condition to machine precision. We demonstrate two of the proposed methods in the context of periodic domains. Problems defined on bounded domains, including those with complex geometric features remain an ongoing effort. However, this work shows that it is possible to design computationally efficient methods that can effectively enforce the Lorenz gauge condition in a non-staggered PIC formulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Angularly resolved spectral reconstruction of x rays via filter pack attenuation

We have designed a new filter pack array to measure angular variations in x-ray spectra during a single shot. The filter pack was composed of repeating identical columns of aluminum and copper filters of varying thicknesses. These columns were located at different positions to measure the spectrum at each corresponding angle. This array was utilized in an experiment to measure the energy evolution of betatron x rays in a laser wakefield accelerator by curving the wakefield with a transverse density gradient, streaking the x rays across the array in front of an x-ray charge-coupled device (CCD) camera. After subtracting the background and “flattening” the image to remove spatial nonuniformities, a critical energy was calculated for each position that produced the best agreement with the measured signal. There was a clear change in critical energy with angle, shedding light on the dynamics of the electrons that traveled through the accelerator. Furthermore, these angles correspond to distinct emission times, covering a timescale of tens of picoseconds. The filter pack was capable of recovering these angular details without the impact of errors introduced by shot-to-shot variability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Combining geometric-optical and spectral invariants theories for modeling canopy fluorescence anisotropy

The spectral invariants theory ( p -theory) has received much attention in the field of quantitative remote sensing over the past few decades and has been adopted for modeling of canopy solar-induced chlorophyll fluorescence (SIF). However, the spectral invariant properties (SIP) in simple analytical formulae have not been applied for modeling canopy fluorescence anisotropy primarily because they are parameterized in terms of leaf total scattering, which precludes the differentiation between forward and backward leaf SIF emissions. In this study, we have developed the canopy-SIP SIF model by combining geometric-optical (GO) theory to account for asymmetric leaf SIF forward and backward emissions at the first-order scattering and by modeling multiple scattering based on the p-theory, thus avoiding the dependence on radiative transfer models. The applicability of the model simulations especially over 3D heterogeneous canopies was improved by incorporating canopy structure through multi-angular clumping index, and by modeling single scattering from the four components of the scene in view according to the GO approach. The results show good consistency with both the state-of-the-art SIF models and multi-angular field SIF observations over grass and chickpea canopies. Further, the coefficient of determination (R²) between the simulated SIF and field measurements was 0.75 (red) and 0.74 (far-red) for chickpea, and 0.65 (both red and far-red) for grass. The average relative error was approximately 3% for 1D homogeneous scenes when comparing the canopy-SIP SIF model simulations to the SCOPE model simulations, and around 4% for the 3D heterogeneous scene when comparing to the LESS model simulations. The results indicate that the proposed approach for separating asymmetric leaf SIF emissions is a robust way to keep a balance between satisfactory simulation accuracy and efficiency. Model simulations suggest that neglecting the leaf SIF asymmetry can lead to an underestimation of canopy red SIF by 6.3% to 42.6% for various leaf biochemical and canopy structural parameters. This study presents a simple but efficient analytical approach for canopy fluorescence modeling, with potential for large-scale canopy fluorescence simulations.

3D heterogeneous structure↗

DOE OSTI2023

Temperature dependence of magnetic anisotropy and magnetoelasticity from classical spin-lattice calculations

Here we present a classical molecular-spin dynamics (MSD) methodology that enables accurate computations of the temperature dependence of the magnetocrystalline anisotropy as well as magnetoelastic properties of magnetic materials. The nonmagnetic interactions are accounted for by a spectral neighbor analysis potential (SNAP) machine-learned interatomic potential, whereas the magnetoelastic contributions are accounted for using a combination of an extended Heisenberg Hamiltonian and a Néel pair interaction model, representing both the exchange interaction and spin-orbit-coupling effects, respectively. All magnetoelastic potential components are parameterized using a combination of first-principles and experimental data. Our framework is applied to the α phase of iron. Initial testing of our MSD model is done using a 0 K parametrization of the Néel interaction model. After this, we examine how individual Néel parameters impact the $B$ 1 and $B$ 2 magnetostrictive coefficients using a moment-independent δ sensitivity analysis. The results from this study are then used to initialize a genetic algorithm optimization which explores the Néel parameter phase space and tries to minimize the error in the B 1 and B 2 magnetostrictive coefficients in the range of 0–1200 K. Our results show that while both the 0 K and genetic algorithm optimized parametrization provide good experimental agreement for $B$ 1 and $B$ 2 , only the genetic algorithm optimized results can capture the second peak in the $B$ 1 magnetostrictive coefficient which occurs near approximately 800 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

DESI DR1 Ly α 1D power spectrum: Validation of estimators

The Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) is the largest sample to date for small-scale Lyα forest cosmology, accessed through its one-dimensional power spectrum (P 1D ). The Lyα forest P 1D is extracted from quasar spectra that are highly inhomogeneous (both in wavelength and between quasars) in noise properties due to intrinsic properties of the quasar, atmospheric and astrophysical contamination, and also sensitive to low-level details of the spectral extraction pipeline. We employ two estimators in DR1 analysis to measure P 1D : the optimal estimator and the fast Fourier transform (FFT) estimator. To ensure robustness of our DR1 measurements, we validate these two power spectrum and covariance matrix estimation methodologies against the challenging aspects of the data. First, using a set of 20 synthetic 1D realizations of DR1, we derive the masking bias corrections needed for the FFT estimator and the continuum fitting bias needed for both estimators. We demonstrate that both estimators, including their covariances, are unbiased with these corrections using the Kolmogorov-Smirnov test. Second, we substantially extend our previous suite of CCD image simulations to include 675,000 quasars, allowing us to accurately quantify the pipeline's performance. This set of simulations reveals biases at the highest k values, corresponding to a resolution error of a few percent. We base the resolution systematics error budget of DR1 P 1D on these values, but do not derive corrections from them since the simulation fidelity is insufficient for precise corrections.

Lyman alpha forest↗

DOE OSTI2020

An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring

Unmanned aerial system (UAS)-based remote sensing can provide high spatial- and temporal-resolution crop monitoring for precision management. Existing crop monitoring UAS primarily use conventional techniques such as multi-spectral broadband vegetation indices (VIs) to track canopy structure/biomass. Recently developed lightweight hyperspectral sensors can track crop physiology and performance via complementary signals such as solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) that can be derived from hyperspectral reflectance. However, few existing UAS can acquire high-quality SIF and hyperspectral reflectance. Here, we designed a novel UAS that simultaneously captures far-red SIF and hyperspectral reflectance, using a single bifurcated fiber and motorized arm to measure downwelling and upwelling irradiance. The UAS was tested over (1) a heterogeneous corn field with spatially varying crop yield potential and (2) a set of soybean and corn plots under differing nutrient treatments. Our UAS can maintain stability under low-to-moderate winds (2–3 m/s) with <0.4 m geolocation accuracy, <0.1 m altitude drift, and <1.5° error of the fiber optic from nadir position during scanning. Weekly seasonal campaigns reveal that SIF outperforms conventional VIs such as the normalized difference vegetation index (NDVI) for distinguishing plots with different crop yield potential, especially after canopy closure when NDVI tends to saturate. The UAS can capture the diurnal dynamics of SIF and PRI for both corn and soybean. At the seasonal scale, SIF acquired from the UAS correlates well with that from a fixed SIF tower system ( R 2 = 0.81), which measured the same target albeit with different footprints, demonstrating the capability of UAS in characterizing the seasonal progression of crop activity. In conclusion, our newly developed UAS provides high-quality SIF and hyperspectral reflectance, facilitating mechanistic understanding of the physiological control on photosynthesis dynamics. Our findings also imply that this UAS could enable extension of fixed tower-based systems to monitor multiple targets from diurnal to seasonal scales and improve monitoring of heterogeneous fields.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

All-sky aerosol direct radiative effects at the ARM SGP site

All-sky aerosol direct radiative effect (DRE) was estimated for the first time at the Atmospheric Radiation Measurement Southern Great Plains site using multi-year ground-based observations. The NASA Langley Fu-Liou radiation model was employed. Observed inputs for the radiation model include aerosol and cloud vertical extinction profile from Raman lidar; spectral aerosol optical depth, single-scattering albedo, and asymmetry factor from Aerosol Robotic Network; cloud water content profiles from radars; temperature and water vapor profiles from radiosondes; and surface shortwave spectral albedo from radiometers. A cloudy-sky radiative closure experiment was performed. The relative mean differences between modeled and observed surface downwelling shortwave total fluxes were 6% (7%) for transparent (opaque) cloudy-skies. The estimated annual mean all-sky aerosol DRE is -2.13±0.54W m -2 at the top of atmosphere (TOA) and -5.95±0.87 W m -2 at the surface, compared to -3.00±0.58 W m -2 AND -6.85±1.00 W m -2 , respectively, under clear-sky conditions. The seasonal cycle of all-sky aerosol DRE is similar to that of the clear-sky, except with secondary influences of the clouds: The cloud radiative effect is strongest (most negative) in the spring, which reduces the all-sky aerosol DRE. The relative uncertainties in all-sky aerosol DRE due to measurement errors are generally comparable to those in clear-sky conditions except for the aerosol single-scattering albedo. Finally, the TOA all-sky aerosol DRE relative uncertainty due to aerosol single-scattering albedo uncertainty is larger than that in clear-sky, leading to a larger total relative uncertainty. The measurement errors in cloud properties have small effects on the all-sky aerosol DRE.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Evaluating Retention Index Score Assumptions to Refine GC–MS Metabolite Identification

As metabolomics grows into a high-throughput and high demand research field, current metrics for the identification of small molecules in gas chromatography–mass spectrometry (GC–MS) still require manual verification. Though steps have been taken to improve scoring metrics by combining spectral similarity (SS) and retention index (RI), the problem persists. A large body of literature has analyzed and refined SS scores, but few studies have explicitly studied improvements to RI scores. Here, in this study, we examined whether uninvestigated assumptions of the RI score are valid and propose ways to improve them. Query RIs were matched to library RI with a generous window of ±35 to avoid unintentional removal of valid compound identifications. Each match was manually verified as a true positive (TP), true negative, or unknown. Metabolites with at least 30 TP identifications were included in downstream analyses, resulting in a total of 87 metabolites from samples of varying complexity and type (e.g., amino acid mixtures, human urine, fungal species, and so on.). Our results showed that the RI score assumptions of normality, consistent variance across metabolites, and a mean error centered at 0 are often violated. We demonstrated through a cross-validation analysis that modifying these underlying assumptions according to empirical metabolite-specific distributions improved the TP and negative rankings. Further, we statistically determined the minimum number of samples required to estimate distributional parameters for scoring metrics. Overall, this work proposes a robust statistical pipeline to reduce the time bottleneck of metabolite identification by improving RI scores and thus minimize the effort to complete manual verification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Rapid Fabrication of High Frame Rate Multichannel FTIR Spectrometers

Spectrally resolved signals in the short- to mid-wave infrared (SWIR/MWIR) bands at high-temporal resolution are critical for many national security remote sensing missions. Currently available off the shelf technology can achieve either high temporal resolution or high spectral resolution, but rugged instruments that can achieve both simultaneously remain mostly in the realm of one-off R&D projects. This report documents efforts to demonstrate a new technique for designing and building high resolution, high framerate multichannel FTIR (MC-FTIR) spectrometers that operate in the SWIR/MWIR bands. The core optical element in a MC-FTIR spectrometer is an array of statically-tuned lamellar grating interferometers (LGI). In the original MC-FTIR work these arrays were fabricated using a synchrotron x-ray lithography method. We proposed to instead fabricate these LGI arrays using multiphoton lithography (MPL), a 3D printing technique that can fabricate meso-scale structures with sub-micron precision. Although we were able to fabricate LGI arrays of sufficient size using MPL, the realized optical surfaces had unsuitably high optical form errors, precluding their use in a fieldable instrument. Further advancement in MPL technology may eventually enable fabrication of interferometer-grade LGI arrays.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Preserving Superconvergence of Spectral Elements for Curved Domains

Spectral element methods (SEM), extensions of finite element methods (FEM), have emerged as significant techniques for solving partial differential equations in physics and engineering. SEM can potentially deliver superior accuracy due to the potential superconvergence in nodal solutions for well-shaped tensor-product elements. However, the accuracy of SEM often degrades in complex geometries due to geometric inaccuracies near curved boundaries and the loss of superconvergence with simplicial or non-tensor-product elements. To overcome the first issue, we propose using geometric refinement, which both refines the mesh near high-curvature regions and increases the degree of geometric basis functions. We show that when using mixed-element meshes with tensor-product elements in the interior of the domain, curvature-based geometric refinement near boundaries can improve the accuracy of the interior elements by reducing pollution errors and preserving the superconvergence in nodal solutions. To address the second issue, we introduce ApSEM, a post-processing technique using the adaptive extended stencil finite element method (AES-FEM) to recover the accuracy near the curved boundaries. The combination of curvature-based geometric refinement and accurate post-processing offers an effective and easier-to-implement alternative to methods reliant on exact geometries. We demonstrate our techniques by solving the convection-diffusion equation in 2D and 3D and show up to two orders of magnitude of improvement in the solution accuracy, even when the elements are poorly shaped near boundaries. We also show the efficiency of ApSEM as it can recover superconvergence in nodal solutions without drastically increasing the computational cost.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Efficient continuous Energy-Multigroup hybrid depletion scheme using the Shift Monte Carlo code. Part I: Energy condensation sensitivity analysis

Monte Carlo (MC) codes coupled to depletion solvers are increasingly used to provide high fidelity fuel cycle modeling capabilities. Here, these coupled depletion-MC tools produce accurate results in general but can experience nonphysical spatial oscillations when time steps are large or when a system’s dominance ratio approaches unity. Two substepping techniques have been developed previously to remedy and dampen these spatial oscillations without needing to reduce step sizes. The first approach relied on higher-order techniques to account for spectral changes within steps (extrapolation and interpolation techniques). The second approach used the first order perturbation (FOP) theory to account for the change in the one-group spatial flux distribution within steps. This paper develops a hybrid depletion methodology which, in a way, combines how the flux is handled in both substepping techniques. Specifically, the multigroup (MG) MC Shift code is used to update the flux distribution within steps rather than a one-group FOP solver. A fully reflected pincell is investigated, which is not spatially dependent in the MG representation. Thus, the analysis in this paper is an initial demonstration of hybrid depletion. An upcoming companion paper will focus on how the hybrid depletion dampens spatial oscillations. The hybrid depletion approach is verified to be consistent with previous constant extrapolation depletion (CED) methods. This paper finds that the hybrid CED exhibits some error in the eigenvalue and one group constants within macro steps. To address this discrepancy, a simple interpolation scheme (CELI) is investigated. This work found that CELI sufficiently addresses the discrepancy in spectrum for macro steps up to 100 days. Overall, this work demonstrates that the hybrid depletion method can significantly reduce the number of high fidelity MC executions in a MC-coupled depletion with an acceptable eigenvalue error.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Evaluation and Optimization of Snow Albedo Scheme in Noah-MP Land Surface Model Using In Situ Spectral Observations in the Colorado Rockies

The Biosphere-Atmosphere Transfer Scheme (BATS) ground snow albedo algorithm is commonly used in land-surface models (LSM), weather forecasting and research applications. This study addresses key uncertainties in BATS simulated ground snow albedo within the Noah-MP LSM framework through evaluation and optimization of the Noah-MP BATS ground snow albedo formulation using 2-band (visible and near-infrared (NIR)) in situ albedo observations at Rocky Mountain field stations. The Noah-MP BATS ground snow albedo scheme is extremely sensitive to its input parameters. Namely, an ensemble generated by varying BATS input parameters within potentially plausible ranges provides an average daily range (maximum ensemble member minus minimum ensemble member) of ground snow albedo exceeding 0.45 in visible and NIR bands. Parameter optimization improves agreement between simulated and in situ observed ground snow albedo in visible, NIR and broadband spectrums. Importantly, optimized parameters result in reduced biases relative to observed fresh-snow albedo and better agreement with observed albedo decay. Our analysis across different sites supports that the optimized BATS ground snow albedo parameters are appropriate to transfer in space and time, at least within the region studied (the central-southern Rocky Mountains). The primary error source remaining after parameter optimization is that observed fresh-snow albedo is highly variable, particularly in the NIR spectrum, whereas BATS fresh-snow albedo is constant, an issue which requires further investigation. This study shows significant correlations between observed fresh-snow albedo and surface meteorological conditions (e.g., downward shortwave radiation and temperature) which can support future model development that attempts to include a time-varying formulation for fresh-snow albedo.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Synergistic Retrieval of Temperature and Humidity Profiles from Space-Based and Ground-Based Infrared Sounders Using an Optimal Estimation Method

The atmospheric temperature and humidity profiles of the troposphere are generally measured by radiosondes and satellites, which are essential for analyzing and predicting weather. Nevertheless, the insufficient observation frequencies and low detection accuracy of the boundary layer restricts the description of atmospheric state changes by the temperature and humidity profiles. Therefore, this work focus on retrieving the temperature and humidity profiles using observations of the FengYun-4 (FY-4) Geostationary Interferometric Infrared Sounder (GIIRS) combined with ground-based infrared spectral observations from the Atmospheric Emitted Radiance Interferometer (AERI), which are more accurate than space-based individual retrieval results and have a wider effective retrieval range than ground-based individual retrieval results. Based on the synergistic observations, which are made by matching the space-based and ground-based data with those of different spatial and temporal resolutions, a synergistic retrieval process is proposed to obtain the temperature and humidity profiles at a high frequency under clear-sky conditions based on the optimal estimation method. In this research, using the line-by-line radiative transfer model (LBLRTM) as the forward model for observing simulations, a retrieval experiment was carried out in Qingdao, China, where an AERI is situated. Taking radiosonde data as a reference for comparing the retrieval results of the temperature and humidity profiles of the troposphere, the root-mean-square error (RMSE) of the synergistic retrieval algorithm below 400 hPa is within 2 K for temperature and within 12% for relative humidity. Compared with the GIIRS individual retrieval, the RMSE of temperature and relative humidity for the synergistic method is reduced by 0.13–1.5 K and 2.7–4.4% at 500 hPa, and 0.13–2.1 K and 2.5–7.2% at 900 hPa. Moreover, the forecast index (FI) calculated from the retrieval results shows reasonable consistency with the FIs calculated from the ERA5 reanalysis and from radiosonde data. The synergistic retrieval results have higher temporal resolution than space-based retrieval results and can reflect the changes in the atmospheric state more accurately. Overall, the results demonstrated the promising potential of the synergistic retrieval of temperature and humidity profiles at high accuracy and high temporal resolution under clear-sky conditions from FY-4/GIIRS and AERI.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Annotation of DOM metabolomes with an ultrahigh resolution mass spectrometry molecular formula library

Current approaches to analyzing metabolomic data often rely on matching MS/MS fragmentation data to sparse libraries or databases. This approach results in limited identification of features, often with less than 10% of the dataset being annotated. A complementary approach is to assign molecular formula to features based on accurate mass measurements, but the platforms commonly used for metabolomics do not have the needed accuracy or resolving power to do this robustly, particularly for larger molecules. Using our newly modified analysis tool, CoreMS, we generated a library of molecular formula from pooled samples analyzed with LC-21T FT-ICR MS. This library successfully annotated approximately 53.2% of features identified from the exometabolome of marine diatom Phaeodactylum tricornutum – a nearly ten-fold increase over the 5.9% annotation rate achieved using a conventional MS/MS library matching approach. Using this FT-ICR MS library approach, we were able to differentiate differences in the exometabolome of P. tricornutum in iron replete and iron limited conditions, with 668 metabolites being differentially expressed (p < 0.05, 2 x intensity difference) under these conditions. The traditional MS/MS fragmentation-based annotation approach only annotated 61 of these metabolites, while our novel pipeline annotated 450 metabolites and revealed 12 metabolites that were significantly more abundant under low iron conditions. Our results demonstrate the utility of ultrahigh resolution mass spectrometry for generating more comprehensive and confident molecular annotations.

21T-FTICR-MS, CoreMS↗

DOE OSTI2025

Extension of Complex Refractive Index Measurements to the Near-Infrared for Liquids: Methodology and Uncertainty Analysis

Optical identification of liquid droplets, aerosols, or thin films is important for many applications. While reference spectra are sometimes available for such measurements, they are not always applicable to the observed spectrum or the given sample morphology. Reference spectra for many forms can be modeled, however, if the n/k vectors (real and imaginary refractive indices) are available. In previous work we have reported protocols to determine the n/k vectors for dozens of liquids, primarily in the mid-infrared (MIR) spectral range from 7500 to 400 cm –1 . In this work we extend the spectral range into the near-infrared (NIR) region, demonstrating a method to measure and merge the data sets to create composite n/k data ranging from 10 000 to 400 cm –1 (1.0 to 25 µm) with absorbance fidelity spanning over four orders of magnitude, and vastly improved signal-to-noise in the NIR. The precision of the composite data is evaluated for three different liquids, focusing primarily on the steps for converting the raw absorbance spectra to k values. The variability in both MIR and NIR data as well as in the final n/k vectors is also investigated for several liquids. For typical liquids, the overall variability (reported as 2σ) in the final n and k-vectors is determined to be ∼0.4% and 3%, respectively. Finally, the derived n/k data are used to calculate absorbance spectra for aerosol droplets, showing marginal variability due to the typical measurement errors in the final n/k vectors.

47 OTHER INSTRUMENTATION↗