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DOE OSTI2026

Leaf Wax Hydrogen Isotopes Reflect Storm Track Position Over Western North America

Proxy records of past climates have yielded powerful insights into regional hydroclimate dynamics. Novel insights may be gained by reconstructing spatiotemporal changes in precipitation isotopologues in past climate states that cannot be gleaned from individual site‐level studies. In this paper, we ask whether latitudinal gradients in the stable hydrogen isotopic composition of precipitation, as inferred from sedimentary leaf wax biomarkers, reflect aspects of large‐scale climate conditions in western North America (WNA). Modern coretop samples from offshore WNA show that leaf wax hydrogen isotopes broadly track the hydrogen isotopic composition of rainfall between 20 and 40N, but with an offset corresponding to a relatively constant “apparent fractionation” value. Poleward of 40N, the leaf wax signal may be complicated by fluvial transport of leaf waxes from the continental interior. Leaf wax‐inferred precipitation hydrogen isotopes show a shift to more negative values between 30 and 40N. We use modern observational data to show that this latitudinal range marks a major transition between the subtropical arid zone and the location of the midlatitude storm tracks over the northeast Pacific. Nudged water isotope‐enabled models capture the location of the arid to mesic climate transition with fidelity. This modern data set suggests that reconstructions of the latitudinal gradient of precipitation hydrogen isotopes can constrain the sensitivity of the storm tracks to shifts in climatic boundary conditions in past climate states. This approach can yield novel insights into past, present, and future hydroclimate variability in this arid region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

First 𝛽-Delayed Two-Neutron Spectroscopy of the 𝑟-Process Nucleus 134 In and Observation of the 𝑖 13/2 Single-Particle Neutron State in 133 Sn

This manuscript reports on the direct observation of a 𝛽-delayed two-neutron emission in a study of 134 In at the ISOLDE Decay Station using neutron spectroscopy. We also report on the first measurement in 𝛽 − decay of the long-sought 13/2 + excited state in 133 Sn, attributed to be the neutron single-particle 𝑖 13/2 orbital. The observation of sequential neutron emission is used to extract the relative population of the 𝑖 13/2 state, which was found to be much smaller than the predictions of the statistical model. The experiment was possible because of the innovative use of a neutron array with neutron discrimination and interaction tracking capabilities. This is the first study of the details of the two-neutron emission for a nucleus, which belongs to the 𝑟-process path. Understanding 𝛽-delayed two-neutron emission probabilities is essential to validate models used in astrophysical 𝑟-process nucleosynthesis calculations. Observing two-neutron emissions in 𝛽 − decay paves the way for new experiments to study energy and angular correlations for 𝛽-delayed multineutron emitters.

Beta decay↗

DOE OSTI2024

Selective Deposition and Fusion of AISI 316L: An Additive Manufacturing Process for Space Environments via Direct Ink Writing and Laser Processing

Unlocking the potential of additive manufacturing (AM) for space exploration hinges on overcoming key challenges, notably the ability to manufacture or repair parts on-site during exploration missions with consideration of quality, feedstock utilization, and challenges involved in microgravity environments. While there are multiple efforts to investigate the use of existing metal AM processes such as powder bed fusion (PBF), directed energy deposition (DED), and filament-based material extrusion, each process comes with a different set of challenges in space environments. Here, in this work, we introduce a new AM method that integrates the benefits of direct ink writing (DIW) to selectively deposit metallic pastes with laser-based processing to locally debind and subsequently melt and fuse metal powder, layer by layer, enabling the manufacturing of AISI 316L samples with densities exceeding 99.0%. The impact of process parameters on single-track dimensions, surface morphology, and porosity was characterized. The efficacy of laser debinding was assessed via secondary-ion mass spectrometry, permitting the carbon content to be estimated at 0.0152%, which is safely below the acceptable limit (0.03 wt%) for AISI 316L.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Numerical investigation of liquid wall ablation in inertial fusion energy chambers

This paper presents a novel approach for modeling liquid wall ablation in liquid wall-protected inertial fusion energy (IFE) chambers. These systems are promising candidates for the implementation of fusion technology, yet significant gaps remain in understanding the underlying physical processes and their implications for design. Following target ignition, a portion of the fusion energy is released as x-rays, which deposit their energy into an array of liquid jets, leading to partial vaporization. Accurately modeling this heat deposition and vaporization process remains challenging due to the complex geometries typical of (pre-conceptual) IFE chamber designs. Furthermore, the subsequent expansion of vaporized material into the chamber’s vacuum environment poses difficulties for conventional CFD methods based on continuum assumptions, which can lead to significant inaccuracies. To address some aspects of these challenges, this work introduces a ray-tracing-based methodology to map the spatial distribution of ablated material in liquid wall-protected systems. In addition, a vacuum-tracking scheme is developed to extend the applicability of an OpenFOAM-based solver to gas dynamics in rarefied environments. The proposed approach has been verified through numerical benchmarks and applied to a practical case involving the HYLIFE-II (High Yield Lithium Injection Fusion Energy) chamber. The methodology advances the modeling capabilities for liquid wall-protected IFE systems and provides valuable tools to support their design and optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Avian Activity Classification Using Recurrent Networks to Fuse Videos with Metadata on Imbalanced Datasets

Activity classification plays a crucial role in various real-life scenarios involving both humans and animals. There is an increasing need for precise activity classification focused on avian-solar interactions, as the usage of solar energy facilities, such as photovoltaic array power stations, has been observed to impact bird species richness, behavior, and activity. However, there has been no work to develop an automated system to monitor and classify these avian-solar interactions. All current methods rely on human observers, which is time and human resources costly and subject to errors related to searcher efficiency. With the recent success of Deep Learning models in activity classification problems, this paper develops a recurrent neural network-based model to automatically classify six avian activities around solar energy facilities. Our proposed model integrates critical feature engineering metadata with video frame data, enabling improved learning and more accurate activity classification. Furthermore, we address the challenge of data imbalance during training and demonstrate the efficacy of our model in detecting and classifying different activities within video tracks. Additionally, we analyze the saliency/backpropagation map of the trained proposed model and validate its decision-making rationale.

Avian activity classification; bidirectional LSTM;↗

DOE OSTI2025

Targeted Mobile Measurements to Isolate the Impacts of Aerosols and Meteorology on Deep Convection

One of the main goals of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign near Houston, TX was to improve understanding of meteorology and aerosol effects on deep convective storms. To help TRACER achieve its goals of disentangling aerosol-cloud interactions from meteorology, the Texas A&M University (TAMU) team deployed the new fully mobile Rapid Onsite Atmospheric Measurement Van (ROAM-V) carrying instruments to measure aerosol and atmospheric properties that was moved to multiple locations on a deployment day of isolated convection initiated by the sea breeze.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Implementation of compound refractive lenses for large field-of-view x-ray phase-contrast imaging during hypervelocity impact experiments

Synchrotron x-ray phase-contrast imaging (XPCI) offers time-resolved visualization of dynamic compression phenomena, but its intrinsically small field-of-view (FOV) limits the time that key features remain in frame. A novel approach to enlarge the FOV is achieved by positioning a two-dimensional parabolic compound refractive lens (CRL) upstream of the sample to deliberately defocus the white beam. Ray-tracing simulations and XPCI measurements show that this CRL configuration can expand the beam by ∼50% vertically and ∼15% horizontally based on the full width at half-maximum of the beam. Implementing the CRL, however, attenuates the photon flux and lowers signal-to-noise ratio (SNR). Task-based analysis using a calibration grid (30 μm dots) showed that both setups fail to consistently meet the Rose criterion (SNR ≥ 5) for features of this size in single-bunch imaging. Extrapolating the measured SNR Rose values suggests that the minimum consistently detectable feature lies closer to 30–40 μm for the standard XPCI setup and above 40 μm for CRL-XPCI. Despite this limitation, the CRL configuration nearly doubles the illuminated area, enabling simultaneous tracking of front and rear observations of boron carbide targets subjected to rod and sphere impacts at 1.0–2.6 km/s. Image tracking algorithms and photonic Doppler velocimetry were used to measure penetration and rear-surface velocity histories. Together, these measurements capture crack fronts, penetration, and material breakout, offering new benchmark data for validating high-strain-rate constitutive models of ceramic materials.

Ceramic materials↗

DOE OSTI2025

Post-DTL Beam Delivery

Ensuring that the beam delivered from the upgraded Front-End (FE) meets the Key Performance Parameters (KPPs) at each user facility is critical to the success of the LANSCE Accelerator Modernization Project (LAMP). For a high-intensity, multi-user facility like LANSCE, compliance with beam loss and radiation thresholds is as important as the charge delivered to each target. While early LAMPF/LANSCE operations relied on iterative tuning to minimize losses from beam halo and tail particles, the new FE may introduce different beam distributions and loss modes—making predictive modeling essential. To manage this, the F2E (Front-End to End) effort is developing detailed particle-tracking models that reflect realistic beamline conditions, including halo formation and expected diagnostic readings. These "snapshot" simulations aim to benchmark live machine performance at a given moment. This will help quantify how beam quality from the new FE will propagate downstream through the facility. Only by validating these models can we confidently assess and mitigate the potential impacts of the LAMP FE on beam delivery. Post-DTL, the beam splits to serve five major user facilities. Historically, low-energy beam transport has been modeled using TRACE, and higher-energy sections with TRANSPORT. These have now been unified into MAD-X format and validated with codes such as Elegant, pyOrbit, XSuite, Impact-Z, and HPSim. The primary focus now is on accurate modeling of full particle distributions (including beam halo) as they traverse the accelerator and beamlines to each experimental station. All models are at various stages of validation with empirical data.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Lightning and Radar Measures of Mixed-Phase Updraft Variability in Tracked Storms during the TRACER Field Campaign in Houston, Texas

Properties of 7488 thunderstorms are summarized for June–September 2022 during the Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign Houston, Texas, using polarimetric weather radar and VHF 3D Lightning Mapping Array data. Automated tracking of storms linked each instrument’s measurements to a data-defined, time-evolving storm footprint. Within each storm, the depth and magnitude of episodic columns of radar differential reflectivity and specific differential phase quantified the prevalence of updrafts that activated mixed-phase precipitation pathways. Lightning measurements further distinguished the degree of rimed precipitation formation: the fraction of tracks with lightning varied from day to day and cells with lightning had stronger polarimetric columns. Track-level correlation of the lightning flash rate with radar polarimetric measures had substantial spread, showing that lightning provides an additional signal of mixed-phase precipitation processes that can complement future studies of thermodynamic and aerosol controls on cloud microphysics in the Houston region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Siting bioenergy facilities in the United States: Measuring participation in decisions and distribution of effects

Scientists and stakeholders can inform the process of siting renewable energy facilities in ways that do not perpetuate socioeconomic disparities associated with fossil fuel industries or create new ones. Procedural justice indicators and distributional justice indicators that incorporate environmental, social, and economic objectives can be used to site energy facilities in ways that increase benefits and reduce negative impacts to disadvantaged and underserved populations. A generic list of potential energy justice indicators for siting bioenergy facilities was developed collaboratively between U.S. bioenergy researchers and diverse agriculture, energy, and energy and environmental justice stakeholders and experts. From this list smaller numbers of indicators can be selected or modified with communities for local siting of bioenergy facilities. Groups of indicators can be used to guide biorefinery or biopower siting and permitting decisions, e.g., to compare siting options, to draw early attention to key problems, or to track progress toward justice-related targets.

09 BIOMASS FUELS↗

DOE OSTI2026

Data From: "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater"

This repository contains the data and code associated with the paper titled "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater," published in Nature Geoscience, 2026. This study seeks to answer how various ages of groundwater interact with mountainous streamflow in mountainous headwaters such as the East River. It includes various model-data processing scripts, primarily for ParFlow-CLM analysis of simulated water years 2015-2021, and two numerical warming experiments (+2.5 and +4.0 degrees C), including run scripts, forcing scripts, and post-processing, as well as comparison to observation datasets, detailed below. This data requires the use of R (.r, .rmd), Python (.py), Jupyter Notebook or Jupyter Lab (.ipynb), ParFLOW-CLM, EcoSLIM. Further information on the use of all file formats mentioned below (e.g. .tff. .nc) are provided within the associated scripts and directory where the files are located. Contents & Usage ASO/: Contains the bash and python scripts used to convert airborne snow observatory (ASO) data (ASO, 2023) in various data formats (georeferenced tiff file, NetCDF, UTM, and to latitude/longitude) then regrided to the ParFlow equivalent grid. Output data are in regrid_regll_data.zip and subsequently visualized and analyzed in plot_and_compare.py for Supplementary Figures A14 and A15. The wksht_ASO_comparison.xlsx spreadsheet is used to calculate the data for Supplementary Figure A16. EcoSLIM/: Contains the scripts and input files to run the EcoSLIM particle tracking simulations (/run_scripts) and the post-processing python script (/plot_scripts/eco_agedist_plots.ipynb). Jasechko et al./: Contains the jupyter notebook (Extract_Elevation.ipynb) to determine the outlet elevations of the 260 watersheds used in Jasechko et al. (2016), and the corresponding table, Table_S1_Watersheds_alt.csv. Used to create Supplementary Information Figure A2. PLM_Wells/: Contains the QA/QC-ed groundwater level time series of the PLM-1 and PLM-6 Monitoring Wells from Faybishenko et al. (2023), reformatted to water years used for Supplementary Figures A19 and and A20. ParFlow/: Contains the input files and run scripts to run ParFlow-CLM (/run_scripts), the python and tool command language (Tcl) scripts to create and distribute the ParFlow forcing simulation files (/forcing), and various scripts and intermediary files to analyze the model outputs (/post_process). SQUIRE/: Contains the processing scripts and intermediary files for the Surface QUantitatIve pRecipitation Estimation (SQUIRE) data (Grover, 2023) used to generate Supplementary Figure A18. USGS_Streamflow/: Contains the raw and gap-filled United States Geological Survey streamflow data (U.S. Geological Survey, 2026) used at the Almont station (site number 09112500). Gap-filling is performed in the R script with data from the Taylor station (site number 09110000). (/USGS_09112500_EAST_RIVER_AT_ALMONT_GAP_FILLED/code_almont_streamflow_gap_fill.Rmd). discharge/: Contains the gap-filled discharge data at the Watershed Function SFA East River pumphouse site (Newcomer et al., 2022) used to generate Supplementary Figure A13 and to compute hourly Nash-Sutcliffe model efficiency coefficients (NSE) in Table A4. snotel_and_flux_tower/: Contains the snow telemetry data (U.S. Department of Agriculture, 2024) from the Butte (site ID 380) and Schofield (site ID 737) stations, reformatted by water year, accessed with the snotelr R package. Used to create Supplementary Figure A17. Also contains the flux tower observational data (FluxTower_Pumphouse_ESS-DIVE.ET_only.h.txt) from Ryken et al. (2022) and sap flux transpiration data (MaxB_Transpiration_5Sites.daily_sums.h.txt) from Ryken (2021), used to create Supplementary Figures A22 and A23, respectively. Raw EcoSLIM model outputs are in excess of 24TB, and are stored on National Energy Research Scientific Computing Center (NERSC) and publicly available via the external link provided in the paper.

atmospheric warming↗

DOE OSTI2026

SPRUCE FT-ICR MS, Bulk Chemistry, and Mass Loss from Litter Decomposition Study in Experimental Plots, Marcell Experimental Forest, Minnesota, 2015-2017

This dataset contains molecular, bulk chemical, and mass loss measurements from a litter decomposition study at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. This site is in a Sphagnum spp. ombrotrophic bog forest. Litterbags were deployed into the peat in September 2015 across three warming levels (+0, +4.5, and +9°C) under ambient and elevated carbon dioxide (CO₂ - +500 ppm) and retrieved after roughly 0.5, 1, and 2 years of field incubation (2015-09-23 to 2017-08-02). Litterbags containing six peatland litter types: black spruce needles (Picea mariana - SPL), spruce fine roots (SPR), Sphagnum angustifolium (ANG), Sphagnum magellanicum (MAG), Labrador tea leaves (Rhododendron groenlandicum - LTL), and Labrador tea roots (LTR). Molecular composition of water-soluble organic matter extracts was characterized using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) at 9.4 Tesla, operated in negative ion mode with electrospray ionization, providing molecular formula assignments and compound-class distributions across the decomposition time series. Bulk chemical characterization included elemental analysis (percent carbon, nitrogen, and phosphorus) and Fourier Transform Infrared Spectroscopy (FTIR) to quantify functional group composition. Litter mass loss was tracked gravimetrically at each retrieval interval, expressed as percent mass remaining relative to initial dry mass for each litter type and treatment combination. These data are valuable for understanding how vegetation shifts driven by increased atmospheric CO2 and temperature in peatlands alter litter inputs and organic matter stabilization trajectories, with implications for projecting and modeling peatland carbon cycling. This dataset contains two data files in comma-separated value (.csv) format. Additional metadata are provided: two data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

decomposition↗

DOE OSTI2025

Directed energy deposition of functionally graded V-4Cr-4Ti to Fe-9Cr transition for fusion power systems

This study proposes a graded structure via additive manufacturing for divertor and first wall blanket applications in fusion reactors. Materials were selected based on thermodynamic calculations to operate from 1100 °C at the plasma-facing level to 550 °C at the structural steel level. Conventional joining methods often lead to failures due to discrete reaction layers with significant mechanical property differences. Using laser beam-directed energy deposition (LB-DED), this study demonstrates the fabrication of a VCrTi-Gr91 steel functionally graded component through a novel process parameter optimization framework. A systematic approach included powder characterization, single-track depositions, and construction of printability maps. Near full-density specimens of each interlayer were additively manufactured, and a transition from V-based alloys to reduced activation ferritic martensitic steels was achieved. Computational material selection of interlayer alloys and thermodynamic/diffusion kinetics simulations prevented most interface incompatibilities. A brittle intermetallic formed at one interface, causing cracking, which was not predicted by current thermodynamic models. Transition alloy design approach was updated with a more recent database and a mitigation strategy has been proposed to eliminate the formation of deleterious intermetallic phases. Ultimately, LB-DED has proven effective for producing multi-material graded systems for fusion applications, with the demonstrated process parameter optimization framework applicable to various materials.

Additive manufacturing↗

DOE OSTI2025

Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE)

Convective clouds play an important role in Earth’s climate system and are a known source of extreme weather. Gaps in our understanding of convective vertical motions, microphysics, and precipitation across a full range of aerosol and meteorological regimes continue to limit our ability to predict the occurrence and intensity of these cloud systems. To improve predictability, the National Science Foundation (NSF) sponsored a large field experiment entitled “Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE).” ESCAPE took place between 30 May and 30 September 2022 in the vicinity of Houston, Texas, because this area frequently experiences isolated deep convection that interacts with the region’s mesoscale circulations and its range of aerosol conditions. ESCAPE focused on collecting observations of isolated deep convection through innovative sampling and developing novel analysis techniques. This included the deployment of two research aircraft, the National Research Council of Canada Convair-580 and the Stratton Park Engineering Company Learjet, which combined conducted 24 research flights from 30 May to 17 June. On the ground, three mobile X-band radars and one mobile Doppler lidar truck equipped with soundings were deployed from 30 May to 28 June. From 1 August to 30 September 2022, a dual-polarization C-band radar was deployed and operated using a novel, multisensor agile adaptive sampling strategy to track the entire life cycle of isolated convective clouds. Analysis of the ESCAPE observations has already yielded preliminary findings on how aerosols and environmental conditions impact the convective life cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A new technique to retrieve aerosol vertical profiles using micropulse lidar and ground-based aerosol measurements

Accurately characterizing the vertical distribution of aerosols and their cloud-forming properties is crucial for understanding aerosol-cloud interactions and their impact on climate. This study presents a novel technique for retrieving vertical profiles of aerosols, cloud condensation nuclei (CCN), and ice nucleating particles (INP) by combining micropulse lidar, radiosonde, and ground-based aerosol measurements. Herein, the technique is applied to data collected by our team at Texas A&M University during the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) campaign. Ground-based aerosol size distribution and CCN counter data are used to estimate the value of the aerosol hygroscopicity parameter, κ. The derived κ, together with Mie scattering theory and the relative humidity profile from the radiosonde, is used to estimate aerosol size growth and the associated increase in backscatter at each altitude. We then correct the lidar backscatter to dry conditions to produce the dry aerosol backscatter coefficient profile. The dry aerosol backscatter coefficient profile is linearly scaled to collocated surface measurements of aerosols, CCN, and INP to produce corresponding vertical profiles. Combining lidar backscatter profiles with aerosol and cloud nucleation measurements leads to a more realistic representation of vertical distributions of aerosol properties. The method could be readily applied to lidar measurements in future field campaigns.

Chen, Bo [Texas A & M Univ., College Station, TX (↗

DOE OSTI2026

Microstructure prediction for Ti-22Al-25Nb in laser powder bed fusion

This work presents a physics-informed framework for predicting solidification morphology and defect susceptibility in additively manufactured Ti–22Al–25Nb across a broad processing space. The framework integrates solidification microstructure selection (SMS) analysis with a single-track defect-based printability map to establish a unified methodology linking processing parameters to both interfacial morphology and manufacturability. Thermal gradients G and solidification rates R are first computed using the Thermo-Calc Additive Manufacturing (TC-AM) module, a finite-interface-dissipation (FID) phase-field (PF) model coupled with CALPHAD method is then employed to systematically distinguish planar and dendritic regimes as functions of $G$ and $R$. By superimposing the printability map onto the morphology projections, a comprehensive process–structure framework is obtained. Across most processing conditions, the predicted microstructure is predominantly dendritic, while planar growth emerges only under selected laser power $P$ and scan speed $v$ combinations. In addition to morphology classification, the framework quantifies the dendritic area fraction and introduces a width-based morphology descriptor to characterize the spatial extent of planar/dendritic regions within the melt pool. It provides mechanistic insight into the interplay between solidification physics and defect formation, offering practical guidance for parameter selection and microstructural control in Ti–22Al–25Nb additive manufacturing (AM).

36 MATERIALS SCIENCE↗

DOE OSTI2025

Extending TOUGH + HYDRATE with a parallel particle transport simulator: numerical investigation of sand production during gas production from hydrate deposits

A new parallel code for simulating particle transport in porous media is integrated with the TOUGH + HYDRATE simulator to investigate sand production associated with gas production from unconsolidated gas hydrate-bearing sediments (HBS). Here, the parallel coupled simulator is named THMPT and uses the integral finite difference method to describe the Darcian and non-Darcian flow of fluids and heat transport, the finite element method to describe the associated geomechanical changes, and the discrete element method to track the trajectory of individual sand particles within the HBS. The THMPT simulator is written in Fortran, incorporates multiple optimized algorithms, and can comprehensively address the coupled flow, thermal, chemical, geomechanical, and particle transport processes that characterize the system behaviors during gas production from HBS. The simulator can capture all processes involved in sand particle transport in porous media, including sand detachment, collision, clogging (i.e., bridging), and migration. A benchmark case study of sand production in the course of depressurization-induced gas production from a representative HBS reveals various distinct microscopic particle migration mechanisms and the adverse impact of sand particle detachment, transport, and clogging. The numerical investigation also examines the effect of bottomhole pressure on mitigating sand production. The simulation results indicate that sand clogging near the wellbore significantly reduces permeability, decreasing gas production by at least 50%. Lastly, the efficiency of gravel packing in mitigating sand production is numerically evaluated, revealing that the structure of the porous media appears to profoundly influence the macroscopic motion behavior of sand particles and sand clogging characteristics.

discrete element method↗

DOE OSTI2025

Variability in Ice Nucleating Particles Across Greater Houston Texas

The concentration and cloud-forming potential of a region's ice nucleating particle (INP) population have uncertain impacts on deep convective clouds. Specifically, ice nucleating particles (INPs) may affect various cloud properties related to the formation, lifetime, and precipitation of deep convective clouds. As part of the U.S. Department of Energy's TRacking Aerosol and Convection interaction ExpeRiment (TRACER) campaign, researchers from Texas A&M University deployed three Davis Rotating-drum Universal-size-cut Monitoring (DRUM) samplers throughout Greater Houston, Texas from June through September 2022. Ambient particles, collected at the surface with the DRUM samplers in four aerodynamic diameter size ranges (>3, 3–1.2, 1.2–0.34, and 0.34–0.15 μm), were analyzed in offline cold-stage ice nucleation experiments. The INP population in Greater Houston is complex, varying by site and day, but can be generalized by a weak to moderately efficient mode of INPs at −24°C and an efficient mode at −15°C. Analysis reveals that supermicron particles are largely responsible for ice nucleation warmer than −20°C across the region while submicron particles dominate at temperatures colder than −20°C. Additionally, significant spatial diversity in the INP population was observed, with differences in mean nucleation temperature between sites for nearly every size cut. Although INP concentrations were typically ∼0.08 L −1 at −20°C throughout the campaign, a notable region-wide increase in INP concentration for particles freezing at temperatures warmer than −20°C occurred from mid-August to mid-September. This comprehensive characterization of Greater Houston's INP population, including spatial, temporal, and particle size variations, can help constrain ice microphysics parameterizations in weather and climate models.

Thompson, Seth A. [Texas A & M Univ., College Stat↗