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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Trail Creek in Taylor River Watershed, Colorado 2024-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Trail Creek. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format TR-X-Y, where TR refers to Trail Creek, X is the treatment block identifier, and Y is the location identifier. Specifically, TR-ASCC1 is the control treatment block under the Adaptive Silviculture for Climate Change (ASCC) project, and TR-ASCC2 is the clear-cut treatment block. TR-ASCC-EHSn is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and TR-ASCC-ERTn (upslope n=1) are ecohydrology sites along the electrical resistivity tomography transects. The sample and location information can be found in metadata.csv, and the data from the soil sensors will be included in a future data version when the observation period becomes sufficiently long for data analysis. Sampling and Measurements Each sample falls into one of the two sampling methods – (1) intact cores or (2) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. The intact cores were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗
DOE OSTI2024

First Constraints on WIMP-Nucleon Effective Field Theory Couplings in an Extended Energy Region From LUX-ZEPLIN

Following the first science results of the LUX-ZEPLIN (LZ) experiment, a dual-phase xenon time projection chamber operating from the Sanford Underground Research Facility in Lead, South Dakota, USA, we report the initial limits on a model-independent non-relativistic effective field theory describing the complete set of possible interactions of a weakly interacting massive particle (WIMP) with a nucleon. These results utilize the same 5.5 t fiducial mass and 60 live days of exposure collected for the LZ spin-independent and spin-dependent analyses while extending the upper limit of the energy region of interest by a factor of 7.5 to 270~keV. No significant excess in this high energy region is observed. Using a profile-likelihood ratio analysis, we report 90% confidence level exclusion limits on the coupling of each individual non-relativistic WIMP-nucleon operators for both elastic and inelastic interactions in the isoscalar and isovector bases.

Source record↗
DOE OSTI2022

Organomercury Measurements from Sludge Batch 10 Simulant Studies

Researchers at the Savannah River National Laboratory have recently performed testing to evaluate the Sludge Batch 10 flowsheet using simulated sludge waste. In the course of this testing several samples were taken to determine the concentration of organomercury species resulting from sludge batch processing. These samples were submitted to the Savannah River National Laboratory Sensing and Metrology department quantitation using a mercury analyzer. The signal amplifier used to perform organomercury quantitation in the mercury analyzer experienced a malfunction in the course of analysis, leading to uncertainty of organomercury concentrations observed. Seventy-three organomercury samples from six project submissions to the Savannah River National Laboratory Sensing and Metrology department have been critically reviewed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Safeguards Considerations for Coated Particle Fuel Fabrication Facilities

This study aims to identify where existing fuel fabrication safeguards are limited in application to coated particle fuel fabrication facilities; perform a review of techniques that may be appropriate to address these limitations; and identify where further study is required. The purpose is to ensure the necessary technology and safeguards developments are established to facilitate safeguards-by-design for coated particle fuel fabrication facilities, analogous to the research and development (R&D) efforts in the advanced reactor space, including those requiring coated particle fuels and progress to higher technology readiness levels. Finally, this study will also help meet high priority objectives set forth by the IAEA in establishing safeguards R&D precedence and measurement/procedural standards at emerging fuel fabrication facilities. To achieve these objectives, the report is formatted to (1) distill relevant background information on fuel fabrication of oxide and coated particle fuels; (2) provide an overview of the fuel fabrication techniques for a reference oxide fuel fabrication facility and two selected TRISO fuel fabrication facilities; (3) develop facility models of safeguards approaches for the reference facility and the two TRISO facilities; and (4) identify any observed technology needs or gaps from this analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Nucleon form factors and the pion-nucleon sigma term

This talk summarizes the progress made since Lattice 2021 in understanding and controlling the contributions of towers of multihadron excited states with mass gaps starting lower than of radial excitations, and in increasing our confidence in the extraction of ground state nucleon matrix elements. The most clear evidence for multihadron excited state contributions (ESC) is in axial/pseudoscalar form factors that are required to satisfy the PCAC relation between them. The talk examines the broader question--which and how many of the theoretically allowed positive parity states N(p)π(−p), N(0)π(0)π(0), N(p)π(0), N(0)π(p), … make significant contributions to a given matrix element? New data for the axial, electric and magnetic form factors are presented. They continue to show trends observed in Ref.[1]. The N2LO χPT analysis of the ESC to the pion-nucleon sigma term, σπN, has been extended to include the Δ as an explicit degree of freedom [2]. The conclusion reached in Ref.[3] that Nπ and Nππ states each contribute about 10 MeV to σπN, and the consistency between the lattice result with Nπ state included and the phenomenological estimate is not changed with this improvement.

Gupta, Rajan↗
DOE OSTI2023

Oncogenic Ras and ΔNp63α cooperate to recruit immunosuppressive polymorphonuclear myeloid-derived suppressor cells in a mouse model of squamous cancer pathogenesis

Introduction Amplification of human chromosome 3q26-29, which encodes oncoprotein ΔNp63 among other isoforms of the p63 family, is a feature common to squamous cell carcinomas (SCCs) of multiple tissue origins. Along with overexpression of ΔNp63, activation of the protooncogene, RAS , whether by overexpression or oncogenic mutation, is frequently observed in many cancers. In this study, analysis of transcriptome data from The Cancer Genome Atlas (TCGA) demonstrated that expression of TP63 mRNA , particularly ΔNp63 isoforms, and HRAS are significantly elevated in advanced squamous cell carcinomas of the head and neck (HNSCCs), suggesting pathological significance. However, how co-overexpressed ΔNp63 and HRAS affect the immunosuppressive tumor microenvironment (TME) is incompletely understood. Methods Here, we established and characterized an immune competent mouse model using primary keratinocytes with retroviral-mediated overexpression of ΔNp63α and constitutively activated HRAS (v-ras Ha G12R) to evaluate the role of these oncogenes in the immune TME. Results In this model, orthotopic grafting of wildtype syngeneic keratinocytes expressing both v-ras Ha and elevated levels of ΔNp63α consistently yield carcinomas in syngeneic hosts, while cells expressing v-ras Ha alone yield predominantly papillomas. We found that polymorphonuclear (PMN) myeloid cells, experimentally validated to be immunosuppressive and thus representing myeloid-derived suppressor cells (PMN-MDSCs), were significantly recruited into the TME of carcinomas arising early following orthotopic grafting of ΔNp63α/v-ras Ha -expressing keratinocytes. ΔNp63α/v-ras Ha -driven carcinomas expressed higher levels of chemokines implicated in recruitment of MDSCs compared to v-ras Ha -initiated tumors, providing a heretofore undescribed link between ΔNp63α/HRAS-driven carcinomas and the development of an immunosuppressive TME. Conclusion These results support the utilization of a genetic carcinogenesis model harboring specific genomic drivers of malignancy to study mechanisms underlying the development of local immunosuppression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Neutron Star Radii, Deformabilities, and Moments of Inertia from Experimental and Ab Initio Theory Constraints of the 208Pb Neutron Skin Thickness

Recent experimental and ab initio theory investigations of the 208Pb neutron skin thickness have the potential to inform the neutron star equation of state. In particular, the strong correlation between the 208Pb neutron skin thickness and the pressure of neutron matter at normal nuclear densities leads to modified predictions for the radii, tidal deformabilities, and moments of inertia of typical 1.4M⊙ neutron stars. In the present work, we study the relative impact of these recent analyses of the 208Pb neutron skin thickness on bulk properties of neutron stars within a Bayesian statistical analysis. Two models for the equation of state prior are employed in order to highlight the role of the highly uncertain high-density equation of state. From our combined Bayesian analysis of nuclear theory, nuclear experiment, and observational constraints on the dense matter equation of state, we find at the 90% credibility level R1.4=12.36−0.73+0.38 km for the radius of a 1.4M⊙ neutron star, R2.0=11.96−0.71+0.94 km for the radius of a 2.0M⊙ neutron star, Λ1.4=440−144+103 for the tidal deformability of a 1.4M⊙ neutron star, and I1.338=1.425−0.146+0.074×1045gcm2 for the moment of inertia of PSR J0737-3039A whose mass is 1.338M⊙.

Lim, Yeunhwan↗
DOE OSTI2021

Ice-nucleating particles in precipitation samples from the Texas Panhandle

Ice-nucleating particles (INPs) influence the formation of ice crystals in clouds and many types of precipitation. This study reports unique properties of INPs collected from 42 precipitation samples in the Texas Panhandle region from June 2018 to July 2019. We used a cold stage instrument called the West Texas Cryogenic Refrigerator Applied to Freezing Test system to estimate INP concentrations per unit volume of air (nINP) through immersion freezing in our precipitation samples with our detection capability of >0.006 INP L -1 . A disdrometer was used for two purposes: (1) to characterize the ground-level precipitation type and (2) to measure the precipitation intensity as well as size of precipitating particles at the ground level during each precipitation event. While no clear seasonal variations of n INP values were apparent, the analysis of yearlong ground-level precipitation observation as well as INPs in the precipitation samples showed some INP variations, e.g., the highest and lowest n INP values at -25°C both in the summer for hail-involved severe thunderstorm samples (3.0 to 1130 INP L -1 ), followed by the second lowest at the same temperature from one of our snow samples collected during the winter (3.2 INP L -1 ). Furthermore, we conducted bacteria community analyses using a subset of our precipitation samples to examine the presence of known biological INPs. In parallel, we also performed metagenomics characterization of the bacterial microbiome in suspended ambient dust samples collected at commercial open-lot livestock facilities (cattle feedyards hereafter) in the Texas Panhandle (i.e., the northernmost counties of Texas, also known as “West Texas”) to ascertain whether local cattle feedyards can act as a source of bioaerosol particles and/or INPs found in the precipitation samples. Some key bacterial phyla present in cattle feedyard samples appeared in precipitation samples. However, no known ice nucleation active species were detected in our samples. Overall, our results showed that cumulative n INP in our precipitation samples below -20°C could be high in the samples collected while observing > 10 mm h -1 precipitation with notably large hydrometeor sizes and an implication of cattle feedyard bacteria inclusion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

On the very high energy confinement observed in super H-mode DIII-D experiments

Analysis of recent super H-mode experiments on DIII-D shows that high rotation, not high pedestal, plays the essential role in achieving very high confinement H98y2 > 1.5. Very high confinement is reached early on in the H-mode phase of these discharges, when the pedestal is still very low, but after the toroidal rotation has already built-up to very high levels in the core. As the discharge evolves, the rotation drops, and so does the energy confinement, despite a sustained very high pressure pedestal. During this evolution, the confinement quality is linearly correlated with the core toroidal rotation, which varies according to different levels of injected neutral beam torque per particle. Core transport modeling shows that the contribution from rotation in the E×B shear is responsible for confinement quality significantly in excess of standard H-mode (H98y2 ∼ 1).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A novel measurement of initial-state gluon radiation in hadron collisions using Drell-Yan events

A study of initial-state gluon radiation (ISR) in hadron collisions is presented using Drell-Yan (DY) events produced in proton-antiproton collisions by the Tevatron collider at a center-of-mass energy of 1.96 TeV. This paper adopts a novel approach which uses the mean value of the Z/$\gamma^*$ transverse momentum $ $ in DY events as a powerful observable to characterize the effect of ISR. In a data sample corresponding to an integrated luminosity of 9.4 fb$^{-1}$ collected with the CDF Run II detector, $ $ is measured as a function of the Z/$\gamma^*$ invariant mass. It is found that these two observables have a dependence, $ = -8 + 2.2 \ln m_{DY}^2$ [GeV/c], where $m_{DY}$ is the value of the Z/$\gamma^*$ mass measured in units of GeV/$c^2$. This linear dependence is observed for the first time in this analysis. It may be exploited to model the effect of ISR and constrain its impact in other processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life

Agent-based models (ABMs) in transportation modeling simulate activity and travel decisions at the disaggregate level of households and individuals. To do this, ABMs require detailed and realistic information on agents’ socioeconomic and demographic characteristics. Various synthetic population generators have been proposed to address this need. However, most of those currently in practice are cross-sectional in nature and do not account for the dynamics within households and individuals as they progress through life events over time. This is a major shortcoming, as literature has shown that transportation decisions are affected by the transition between and co-occurrence of life cycle events. While some demographic evolution simulators have been proposed to address this issue, they are developed using cross-sectional data and capture only a small set of life cycle events and their interdependence. Addressing these drawbacks, we propose a demographic microsimulator (DEMOS) that captures the “continuum of life” by considering a range of household- and individual-level life cycle events. DEMOS is developed using the Panel Survey of Income Dynamics, one of the world’s longest-running longitudinal surveys. The DEMOS submodels consider key life cycle events that are influenced by agents’ demographic variables. DEMOS is applied to evolve the population of the San Francisco Bay Area over a 9-year horizon. Results demonstrate how DEMOS generates life trajectories and how DEMOS outputs match the observed demographic trends. DEMOS is expected to enable longitudinal analysis in the context of ABMs and expand ABMs analyses relating to dynamic processes such as household-level vehicle transactions.

Demographic evolution↗
DOE OSTI2022

Search for the chiral magnetic effect with isobar collisions at $\sqrt{s_{NN}}$ = 200 GeV by the STAR Collaboration at the BNL Relativistic Heavy Ion Collider

The chiral magnetic effect (CME) is predicted to occur as a consequence of a local violation of P and CP symmetries of the strong interaction amidst a strong electro-magnetic field generated in relativistic heavy-ion collisions. Experimental manifestation of the CME involves a separation of positively and negatively charged hadrons along the direction of the magnetic field. Previous measurements of the CME-sensitive charge-separation observables remain inconclusive because of large background contributions. In order to better control the influence of signal and backgrounds, the STAR Collaboration performed a blind analysis of a large data sample of approximately 3.8 billion isobar collisions of $^{96}_{44}$Ru + $^{96}_{44}$Ru and $^{96}_{40}$Zr + $^{96}_{40}$Zr at $\sqrt{s_{NN}}$ = 200 GeV. Prior to the blind analysis, the CME signatures are predefined as a significant excess of the CME-sensitive observables in Ru + Ru collisions over those in Zr + Zr collisions, owing to a larger magnetic field in the former. Here, a precision down to 0.4% is achieved, as anticipated, in the relative magnitudes of the pertinent observables between the two isobar systems. Observed differences in the multiplicity and flow harmonics at the matching centrality indicate that the magnitude of the CME background is different between the two species. No CME signature that satisfies the predefined criteria has been observed in isobar collisions in this blind analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Characterizing the magnetic fields of nearby molecular clouds using submillimeter polarization observations

Of all the factors that influence star formation, magnetic fields are perhaps the least well understood. The goal of this paper is to characterize the 3D magnetic field properties of nearby molecular clouds through various methods of statistically analysing maps of polarized dust emission. Our study focuses on nine clouds, with data taken from the Planck Sky Survey as well as data from the Balloon-borne Large Aperture Submillimeter Telescope for Polarimetry observations of Vela C. We compare the distributions of polarization fraction (p), dispersion in polarization angles ($\mathcal {S}$), and hydrogen column density (N H ) for each of our targeted clouds. To broaden the scope of our analysis, we compare the distributions of our clouds’ polarization observables with measurements from synthetic polarization maps generated from numerical simulations. We also use the distribution of polarization fraction measurements to estimate the inclination angle of each cloud’s cloud-scale magnetic field. We obtain a range of inclination angles associated with our clouds, varying from 16° to 69°. We establish inverse correlations between p and both $\mathcal {S}$ and NH in almost every cloud, but we are unable to establish a statistically robust $\mathcal {S}$ versus NH trend. By comparing the results of these different statistical analysis techniques, we are able to propose a more comprehensive view of each cloud’s 3D magnetic field properties. These detailed cloud analyses will be useful in the continued studies of cloud-scale magnetic fields and the ways in which they affect star formation within these molecular clouds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Determination of proton PDF uncertainties with Markov chain Monte Carlo

We present an analysis of parton distribution functions (PDFs) of the proton using Markov chain Monte Carlo (MCMC) methods. The MCMC approach naturally implements Bayes’ theorem and, thus, provides a means to directly sample the underlying probability distribution—in this case, the probability distribution of the PDF parameters. This allows for a straightforward propagation of the resulting uncertainties into any PDF-dependent observable, preserving their simple probabilistic interpretation. In our analysis we include a broad set of deep inelastic scattering data from HERA, BCDMS and NMC experiments along with the Drell-Yan, 𝑊 and 𝑍 boson data from LHC and Tevatron experiments, which combined with theoretical calculations at next-to-next-to-leading order in QCD allow for realistic determination of PDFs. The main focus of this analysis is to explore alternative methods for PDF uncertainty estimation that are more firmly grounded in statistical principles. We show that the flexibility of the Bayes framework, allowing one, e.g., to account for non-Gaussianity or inconsistencies of datasets, is crucial to extract realistic uncertainties when such assumptions are not fulfilled. We also demonstrate that MCMC allows one to determine the Δ⁢𝜒 2 value corresponding to a given confidence level in the sample, which can, in turn, be used as a statistically well-founded tolerance criterion used in the Hessian method, thus addressing one of its main long-standing drawbacks.

Risse, Peter Clemens [Universität Münster (Germany↗
DOE OSTI2025

Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones

Constraining cloud feedback in global climate models (GCMs) using observations is important for establishing accurate predictions of future climate. Uncertainty in shortwave cloud feedback (SW FB ) dominates uncertainty in total cloud feedback. Recent studies show a shift toward more positive extratropical SW FB in the latest generations of GCMs leading to the emergence of very high equilibrium climate sensitivity (ECS). In this study, we use precipitation efficiency and albedo susceptibility to constrain liquid water path (LWP) response to warming and SW FB in the Southern Ocean (SO; 50°–80°S). We analyze precipitation in extratropical cyclones (ECs) to learn about extratropical condensed water sink processes, combined with observations of clouds and moisture convergence, and use the analysis to better understand and constrain SW FB . We utilize a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model, version 6 (CAM6), to provide a constraint on SW FB based on observations from Clouds and the Earth’s Radiant Energy System (CERES) and Multisensor Advanced Climatology of LWP (MAC-LWP). We apply Gaussian process regression to emulate the model response to all parameters perturbed in the PPE. Confronting the emulator output with observations provides a new estimated response of Earth to global warming. Furthermore, our new estimates of SO LWP reduce the PPE range by 66%–72%, which results in a shortwave cloud radiative effect estimated range that is 27%–34% less than the PPE range. Observations suggest a more positive SO SW FB than the Community Earth System Model, version 2 (CESM2), and consequently do not reject the high climate sensitivity GCMs emerging from the Coupled Model Intercomparison Project phase 6 (CMIP6).

Atmosphere↗
DOE OSTI2023

Analysis of Needlet Internal Linear Combination performance on B -mode data from sub-orbital experiments

The observation of primordial B modes in cosmic microwave background (CMB) polarisation data represents the main scientific goal of most of the future CMB experiments. This signal is predicted to be much lower than polarised Galactic emission (foregrounds) in any region of the sky, pointing to the need for effective component separation methods. Aims. Among all the techniques, the blind Needlet Internal Linear Combination (NILC) is of great relevance given our current limited knowledge of the B-mode foregrounds. In this work, we explore the possibility of employing NILC for the analysis of B modes reconstructed from partial-sky data, specifically addressing the complications that such an application yields such as E–B leakage, needlet filtering, and beam convolution. We consider two complementary simulated datasets of future experiments: the balloon-borne Short Wavelength Instrument for the Polarisation Explorer (SWIPE) of the Large Scale Polarisation Explorer, which targets the observation of both reionisation and recombination peaks of the primordial CMB B-mode angular power spectrum, and the ground-based Small Aperture Telescope of Simons Observatory, which, instead, is designed to observe only the recombination bump at ℓ ~ 80. We assessed the performance of the following two alternative techniques to correct for the CMB E–B leakage: the recycling technique and the Zhao-Baskaran method. We find that both techniques reduce the E–B leakage residuals at a negligible level given the sensitivity of the considered experiments, except for the recycling method in the SWIPE footprint at ℓ < 20. Thus, we implemented two extensions of the pipeline, the iterative B decomposition and the diffusive inpainting, which enabled us to recover the input CMB B-mode power for ℓ ≥ 5. For the considered experiments, we demonstrate that needlet filtering and beam convolution do not affect the CMB B-mode reconstruction. Finally, with an appropriate masking strategy, we find that NILC foregrounds subtraction allows one to achieve sensitivities on the tensor-to-scalar ratio in agreement with the targets of the considered CMB experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Understanding Interfacial Block Copolymer Structure and Dynamics

Here, block copolymer (BCP) structure and dynamics were studied using small-angle neutron scattering (SANS), neutron spin echo (NSE) spectroscopy, and molecular dynamics (MD) simulations to obtain a fundamental understanding of the impact of an interfacial block on chain dynamics. A glassy block acted as the interface, and the dynamics of a rubbery block was studied. The rubbery block was protonated near the interface in one sample and near the chain end in another sample to observe the interfacial effect on the rubbery polymer. Analysis of the structure and dynamics revealed that the interfacial rubbery block was confined in layered morphologies and exhibited much slower dynamics than the chain-end rubbery block that was dispersed in the rubbery matrix. The interfacial rubbery block showed weaker dynamical relaxation than that at the chain end, and it also had critically important length scale dependence. Dynamical slowing was only observed at length scales significantly larger than the characteristic segmental length, and the disparity between interfacial and chain-end dynamics increased with increasing length.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Constraints on Nonthermal Pressure at Galaxy Cluster Outskirts from a Joint SPT and XMM-Newton Analysis

We present joint South Pole Telescope and XMM-Newton observations of eight massive galaxy clusters (0.8–2 × 10$^{15}$ M$_{⊙}$) spanning a redshift range of 0.16–0.35. Employing a novel Sunyaev–Zel’dovich + X-ray fitting technique, we effectively constrain the thermodynamic properties of these clusters out to the virial radius. The resulting best-fit electron density, deprojected temperature, and deprojected pressure profiles are in good agreement with previous observations of massive clusters. For the majority of the cluster sample (five out of eight clusters), the entropy profiles exhibit a self-similar behavior near the virial radius. We further derive hydrostatic mass, gas mass, and gas fraction profiles for all clusters up to the virial radius. Comparing the enclosed gas fraction profiles with the universal gas fraction profile, we obtain nonthermal pressure fraction profiles for our cluster sample at >0.5R$_{500}$, demonstrating a steeper increase between R$_{500}$ and R$_{200}$ that is consistent with the hydrodynamical simulations. Our analysis yields nonthermal pressure fraction ranges of 8%–28% (median: 15% ± 11%) at R$_{500}$ and 21%–35% (median: 27% ± 12%) at R$_{200}$. Notably, weak-lensing mass measurements are available for only four clusters in our sample, and our recovered total cluster masses, after accounting for nonthermal pressure, are consistent with these measurements.

79 ASTRONOMY AND ASTROPHYSICS↗