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At least 451 records · Page 25

Surface Quantitative Precipitation Estimates (SQUIRE) of Snow Water Equivalent from the Surface Atmospheric Integrated Field Laboratory

The upper Colorado River basin is the primary source of water for 40 million people. With declining snowpack in the basin, forecasting hydrological budgets in the Southwest United States is more important than ever. However, due in part, to a lack of reliable observations of precipitation in complex terrain, hydrological models struggle to assess and forecast snowpack snow water equivalent (SWE) in the upper Colorado River basin (UCRB). Therefore, the need for more reliable SWE forecasts in the UCRB motivated the U.S. Department of Energy Atmospheric Radiation Measurement Facility’s Surface Atmospheric Integrated Field Laboratory (SAIL) that occurred from June 2021 to June 2023. During SAIL, the X-band precipitation radar from Colorado State University conducted volume scans sampling the precipitation properties over the UCRB. The ARM facility developed a gridded Surface Quantitative Precipitation Estimates (SQUIRE) product from the radar observations. To do this, various daily SWE estimates from radar using the radar reflectivity factor Z e and specific differential phase K dp were compared against ground-based precipitation gauges. SWE in precipitation calculated from Wolfe and Snider’s S–Z e estimator was in best agreement with the rain gauges for the days when SWE < 12 mm. For days with SWE > 12 mm, the WSR-88D Intermountain West relationship had the best agreement with the precipitation gauges. Airborne snow depth observations show that SQUIRE captures regions of orographic enhancement in the mountains to the west and northwest of the SAIL study area, indicating that the scientific community should focus on understanding and ultimately simulating orographic atmospheric precipitation processes to improve UCRB snowpack SWE assessment and forecasting.

Hydrology↗

A Moving-Wave Implementation in WRF to Study the Impact of Surface Water Waves on the Atmospheric Boundary Layer

Abstract While numerous modeling studies have focused on the interaction of ocean surface waves with the atmospheric boundary layer, most employ idealized waves that are either monochromatic or synthetically generated from a theoretical wave spectrum, and the atmospheric solvers are typically incompressible. To study wind–wave coupling in real-world scenarios, a model that can simulate both realistic meteorological and wave conditions is necessary. In this paper we describe the implementation of a moving bottom boundary condition into the Weather Research and Forecasting Model for large-eddy simulation applications. We first describe the moving bottom boundary conditions within WRF’s pressure-based vertical coordinate system. We then validate our code with idealized test cases that have analytical solutions, including flow over a monochromatic wave with and without viscosity. Finally, we present results from turbulent flows over a moving monochromatic wave with different wave ages, and demonstrate satisfactory agreement of the wave growth rate with results from the literature. We also compare atmospheric stress and wind parameters from two physically equivalent cases. The first specifies a wind moving in the same direction as a propagating wave, while the second involves a stationary wave with the wind adjusted such that the wind relative to the wave is the same as in the first case. Results indicate that the velocity and Reynolds stress profiles for the two cases match, further validating the moving bottom implementation.

17 WIND ENERGY↗

Characterizing warm atmospheric boundary layer over land by combining Raman and Doppler lidar measurements

PBL plays a critical role in the atmosphere by transferring heat, moisture, and momentum. The warm PBL has a distinct diurnal cycle including daytime convective mixing layer (ML) and nighttime residual layer developments. Thus, for PBL characterization and process study, simultaneous determinations of PBL height (PBLH) and ML height (MLH) are necessary. Here, new approaches are developed to provide reliable PBLH and MLH to characterize warm PBL evolution. The approaches use Raman lidar (RL) water vapor mixing ratio (WVMR) and Doppler lidar (DL) vertical velocity measurements at the Southern Great Plains (SGP) atmospheric observatory, which was established by the Atmospheric Radiation Measurement (ARM) user facility. Compared with widely used lidar aerosol measurements for PBLH, WVMR is a better trace for PBL vertical mixing. For PBLH, the approach classifies PBL water vapor structures into a few general patterns, then uses a slope method and dynamic threshold method to determine PBLH. For MLH, wavelet analysis is used to re-construct 2-D variance from DL vertical wind velocity measurements according to the turbulence eddy size to minimize the impacts of gravity wave and eddy size on variance calculations; then, a dynamic threshold method is used to determine MLH. Remotely-sensed PBLHs and MLHs are compared with radiosonde measurements based on the Richardson number method. Good agreements between them confirm that the proposed new algorithms are reliable for PBLH and MLH characterization. The algorithms are applied to warm seasons’ RL and ML measurements at the SGP site for five years to study warm season PBL structure and processes. The weekly composited diurnal evolutions of PBLHs and MLHs in warm climate were provided to illustrate diurnal and seasonal PBL evolutions. This reliable PBLH and MLH dataset will be valuable for PBL process study, model evolution, and PBL parameterization improvement.

54 ENVIRONMENTAL SCIENCES↗

Optical modeling of a radioisotope atmospheric chamber

Abstract Volatile radioisotopes represent a substantial health risk when released into the environment. To better understand the environmental fate of radioisotopes, the authors constructed a cylindrical steel-walled chamber to simulate the atmospheric processing of volatile radioactive gases. Optical modeling was performed for the properties of simulated sunlight in the chamber to better characterize atmospheric reaction studies. Optical simulations were performed using two wall materials (steel and thin-film silica) and validated against experimental measurements. This optical analysis methodology can be used to improve the fidelity of atmospheric models by accounting for optical inhomogeneities enabling a firmer grasp of radioisotopes’ environmental fate. Graphical abstract

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

gdess: A framework for evaluating simulated atmospheric CO 2 in Earth System Models

Atmospheric carbon dioxide (CO 2 ) plays a key role in the global carbon cycle and global warming. Climate-carbon feedbacks are often studied and estimated using Earth System Models (ESMs), which couple together multiple model components—including the atmosphere, ocean, terrestrial biosphere, and cryosphere—to jointly simulate mass and energy exchanges within and between these components. Despite tremendous advances, model intercomparisons and benchmarking are aspects of ESMs that warrant further improvement (Fer et al., 2021; Smith et al., 2014). Such benchmarking is critical because comparing the value of state variables in these simulations against observed values provides evidence for appropriately refining model components; moreover, researchers can learn much about Earth system dynamics in the process (Randall et al., 2019). We introduce `gdess` (a.k.a., Greenhouse gas Diagnostics for Earth System Simulations), which parses observational datasets and ESM simulation output, combines them to be in a consistent structure, computes statistical metrics, and generates diagnostic visualizations. In its current incarnation, `gdess` facilitates evaluating a model's ability to reproduce observed temporal and spatial variations of atmospheric CO 2 . The diagnostics implemented modularly in `gdess` support more rapid assessment and improvement of model-simulated global CO 2 sources and sinks associated with land and ocean ecosystem processes. We intend for this set of automated diagnostics to form an extensible, open source framework for future comparisons of simulated and observed concentrations of various greenhouse gases across Earth system models.

97 MATHEMATICS AND COMPUTING↗

Compensation Between Poleward Energy Transports in the Ocean and Atmosphere

The goal of our project is to investigate the degree of compensation in poleward energy transports by the atmosphere and ocean and its dependence on the time scale, latitude and background climate primarily based on a large suite of the Community Earth System Model version 1 (CESM1) simulations to test the Bjerknes compensation hypothesis. Our particular emphases are to understand: (1) robustness of the degree of the compensation across the various simulations with differing parameterizations and initial conditions, (2) the competing role of atmosphere-ocean couplings through the momentum flux and buoyancy flux in enabling or deterring the compensation, and (3) the role of compensation in the leading modes of variability in the atmosphere and ocean.

58 GEOSCIENCES↗

COMBLE-Isotopic Links to Atmospheric Water’s Sources (ISLAS) Snow Sampling 2020 Field Campaign Report

Within the European Research Council (ERC)-funded project entitled Isotopic Links to Atmospheric Water’s Sources (ISLAS), researchers from the University of Bergen, Norway, used the stable isotope composition of atmospheric water vapor and precipitation to obtain information about the sources and transport processes of water vapor within arctic weather systems. In particular, during cold-air outbreak conditions, evaporation and precipitation occur in close proximity within the study area. With evaporation studied at a single location (Ny-Ålesund), ISLAS researchers wanted to be able to sample the resulting precipitation at several downstream locations. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) site was one of those locations, included in an entire network of precipitation sampling stations reaching from Ny-Ålesund, where water vapor isotope measurements are conducted near the surface, to Longyearbyen, Tromsø, Andenes, Ålesund, and Bergen. Daily precipitation samples, enhanced by more frequent sampling during intense operational periods (IOPs), were conducted during four weeks from 20 February to 20 March 2020. The contribution from the ARM mobile facility (AMF) observatory, deployed at ANX (Andenes, Norway) during COMBLE, was valuable to understand the spatial coherence of water isotope signals from arctic and extratropical weather systems.

54 ENVIRONMENTAL SCIENCES↗

Understanding Mechanistic Controls of Heterotrophic CO 2 and CH 4 Fluxes in a Peatland with Deep Soil Warming and Atmospheric CO 2 Enrichment

This project was funded from August 1, 2016 – July 31, 2019 with a no-cost extension until July 31, 2020 (and built upon the PI-team’s previous work supported by DE-SC0008092 (June 2012 – September 2016)). Our project focused on the Spruce and Peatland Responses Under Changing Environments (SPRUCE: https://mnspruce.ornl.gov/) experiment taking place in the S1 Bog in the Marcell Experimental Forest in northern Minnesota, USA. The SPRUCE project is a unique whole-ecosystem experiment where a bog peatland is subjected to warming and atmospheric carbon dioxide (CO 2 ) enrichment. Deep peat heating of the soil profile (to a depth of at least 2 m) began in June of 2014 and was followed by whole-ecosystem warming in August of 2015. Warming treatments included +0 °C, +2.25 °C, +4.5 °C, +6.75 °C, and +9 °C above ambient temperatures, with 2 experimental chambers for each warming treatment. Half of these chambers received ambient atmospheric CO 2 concentrations, and starting in June of 2016, the other half received elevated atmospheric CO 2 concentrations (~ +500 ppm(v) above ambient). Our primary goal with this project was to explore the mechanistic controls of anaerobic carbon cycling – especially the dynamics of the potent greenhouse gas methane (CH 4 ) – within the SPRUCE experiment.

54 ENVIRONMENTAL SCIENCES↗

Step Catalysis to Synthesize Fossil-Free Ammonia at Atmospheric Pressure (Final Technical Report)

Affordable fossil-free ammonia synthesis will enable high-yield sustainable crop production for a growing world population while preserving the planet and making the best use of water and land. Simple technology amenable to intermittent operation using renewable energy will be made available through step catalysis activating dinitrogen at atmospheric pressure by nitride formation. Project objectives: (1) At the single particle level, quantify and analyze N2 activation by doped or alloyed manganese macroscopic- and nano particles at atmospheric pressure, (2) Quantify and analyze ammonia synthesis from doped or alloyed metal nitride particles when contacting them with hydrogen at atmospheric pressure, and (3) Integrate experimental data and atomic-level computational models to predict the behavior of metal alloys in nitrogen activation and subsequent ammonia synthesis.

10 SYNTHETIC FUELS↗

Enhanced Atmospheric Research at the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) (Final Report)

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was an international scientific expedition into the central Arctic sea ice to study the changing atmosphere-ice-ocean system and its key physical, chemical, and biological processes in a way that will support improved understanding and modeling of Arctic climate. The US Department of Energy’s Atmospheric Research Measurement (ARM) Program operated its second ARM Mobile Facility (AMF2) as a major contribution to the expedition, and the Atmospheric System Research (ASR) program supported this project to maximize the success of DOE’s involvement in MOSAiC. This project has enabled the successful collection of data through support of field operations plans, in-field operational implementation, oversight of real-time data quality, and representing DOE’s interests within the broader international MOSAiC endeavor. The project has promoted scientific research by facilitating and leading a number of efforts to develop value-added products that will support research, including products related to aerosol properties, trace gases, cloud properties, snowfall, the surface energy budget, and a merged product designed for model assessment. These products and related analyses have also contributed to numerous scientific publications on related themes as well as direct model evaluation. Lastly, the project has engaged in a great deal of communication and outreach activities that help to publicize and promote both MOSAiC and DOE’s specific contribution to a broad audience that includes the scientific community, program management, policy makers, and the general public.

54 ENVIRONMENTAL SCIENCES↗

Observing Atmospheric Refraction with Stellar Occultation: Case Study with data from Tyvak-0172

Understanding the upper atmosphere is vital to successful hypersonic flight. Perturbations in temperature and density due to phenomena such as gravity waves and turbulence strongly affect the performance of a hypersonic vehicle (Roy and Blottner, 2006). Observing upper atmospheric conditions from the ground is difficult due to the interference of clouds, so most observations are gathered with weather balloons. However, balloons can only travel up to about 35 km from the Earth surface. Therefore, we turn to remote sensing for atmospheric conditions above 35 km.

58 GEOSCIENCES↗

Applying Corrective Machine Learning in the E3SM Atmosphere Model in C++ (EAMxx)

The Simplified Cloud-Resolving E3SM Atmosphere Model (SCREAM) is the newest addition to the family of Earth System Models capable of explicitly resolving convective systems. SCREAM is a kilometer-scale configuration of the advanced E3SM Atmosphere Model (EAMxx), designed for heterogeneous systems. While the enhanced accuracy of kilometer-scale modeling offers significant benefits, it comes with a substantial computational cost, limiting feasible simulation durations to only a few years, even on the fastest supercomputers. Machine learning presents an opportunity for scientists to achieve the high accuracy of storm-resolving models at a significantly reduced cost. Building on the previous success of applying corrective machine learning (ML) to the FV3 model, this study explores the effects of implementing corrective ML in EAMxx-SCREAM. We also address the computational challenges of integrating the corrective ML, which is written in Python, with the C++/Kokkos EAMxx driver, as well as the potential pitfalls of generalizing an approach that was effective with one atmosphere model to another.

54 ENVIRONMENTAL SCIENCES↗

Characterization and application of a high-resolution microfluidic device in atmospheric ice nucleation research and integrated science teaching

Ambient ice-nucleating particles (INPs) represent an important subset of aerosol particles that facilitate heterogeneous formation of ice crystals in the atmosphere, which can impact Earth system and energy. In this work, we developed an affordable high-resolution platform to replicate atmospheric immersion freezing through the unique capabilities of microfluidics to measure INP concentration of known ice nucleation active materials, as well as high-latitude soil samples. The new instrument produced comparable and extended freezing efficiency data for a multitude of samples over the temperature range of -5 to -35 °C as compared to an existing freezing assay within known uncertainties. Moreover, the new assay was integrated into science teaching at a primarily undergraduate and Hispanic-serving institute, contributing to fostering a deeper understanding of ice nucleation processes among college students, instilling their enthusiasm for science, and addressing the critical need for a well-informed citizenry. Student research assistants were involved in both research and pedagogical development processes. Three students from our team visited the Pacific Northwest National Laboratory to help characterize physicochemical properties of our test samples and to test modeling of atmospheric ice nucleation using a box model as well as a global climate model (E3SM) for the regional-scale conditions over the North Slope of Alaska (NSA) and Southern Great Plains (SGP). We also assessed student learning experience via hands-on training, research processes, and development of educational materials. On pre- and post-participation surveys and in exit interviews, students reported personal growth as advancements in breadth of experience, research-related skill sets, and regarding their educational and career goals. They also affirmed that the methods enacted incorporated the NASA Minority University Research and Education Program (MUREP) STEM Engagement Best Practices.

58 GEOSCIENCES↗

New Particle Formation and Growth in the Houston Atmosphere During TRACER (Final Report)

From 2020-2025, researchers from UC Irvine, UC Riverside, and Colorado State University collaborated on a Department of Energy-funded project to understand how airborne particles form and grow in urban atmospheres, conducting an intensive field campaign in Houston, Texas during summer 2022. Using advanced instruments to measure gas-phase chemicals, particle composition, and a specialized chamber to study particle growth, the team discovered that sulfur-containing compounds from industrial and power plant emissions are the dominant driver of new particle formation in Houston, with particles typically forming locally in the city and growing as air moves away in the urban plume. The research revealed an important methodological insight: measurements from fixed ground stations can be misleading when interpreting how particles actually evolve as air masses move, which has significant implications for how scientists worldwide interpret atmospheric observations. These findings improve understanding of urban air quality and help reduce uncertainties in climate models, since these particles play critical roles in cloud formation and Earth's radiation balance, while also providing detailed information about ultrafine particle composition relevant to public health. The project trained three doctoral students, developed enhanced computer models for urban particle formation, and made all data publicly available through the DOE Atmospheric Radiation Measurement data archive for use by the broader scientific community.

54 ENVIRONMENTAL SCIENCES↗

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗

Observed Atmospheric River Events

This dataset contains observed landfalling atmospheric river (AR) events over the Northeast Pacific and U.S. West Coast used to initialize and evaluate the Deep-AR synthetic atmospheric river framework. It includes 1,434 held-out events whose observed records begin 48 hours before diagnosed AR landfall and continue at 6-hour intervals over a 144-hour event window. Each HDF5 file provides high-resolution 0.25° gridded fields of integrated vapor transport components (qu, qv), 10 m wind components (u10, v10), and 6-hour accumulated precipitation. IVT components and precipitation are sourced from EDARA; 10 m winds are sourced from ERA5. The records share a common 200 × 480 grid over the Northeast Pacific and U.S. West Coast and include coordinate and datetime arrays. These events support atmospheric-river hazard analysis, evaluation of synthetic event generation, precipitation-extremes research, and regional stress testing.

17 WIND ENERGY↗

Special Issue: 10th Anniversary of Atmosphere: Climatology and Meteorology

During the last decade, the number of open access science journals has increased, and these have become an avenue for publishing quality science in a relatively fast and economical way. The Multidisciplinary Digital Publishing Institute (MDPI) journal Atmosphere published its first volume in 2010, and recently celebrated 10 years with the publication of this special commemorative issue. Atmosphere is a peer reviewed, open access journal described as cross disciplinary. Furthermore, the journal attracts authorship from across the globe. During the first few years, the regular issue of Atmosphere was a quarterly publication, but, by 2019, was issued each month. Furthermore, the journal publishes research articles and notes, communications, review articles, and case studies, as well as timely Special Issues.

54 ENVIRONMENTAL SCIENCES↗

EMS-Induced Mutagenesis of Clostridium carboxidivorans for Increased Atmospheric CO 2 Reduction Efficiency and Solvent Production

Clostridium carboxidivorans (P7) is one of the most important solvent-producing bacteria capable of fermenting syngas (CO, CO 2 , and H 2 ) to produce chemical commodities when grown as an autotroph. This study aimed to develop ethyl methanesulfonate (EMS)-induced P7 mutants that were capable of growing in the presence of CO 2 as a unique source of carbon with increased solvent formation and atmospheric CO 2 reduction to limit global warming. Phenotypic analysis including growth and end product characterization of the P7 wild type (WT) demonstrated that this strain grew better at 25 °C than 37 °C when CO 2 served as the only source of carbon. In the current study, 55 mutagenized P7-EMS mutants were developed by using 100 mM and 120 mM EMS. Interestingly, using a forward genetic approach, three out of the 55 P7-EMS mutants showed a significant increase in ethanol, butyrate, and butanol production. The three P7-EMS mutants presented on average a 4.68-fold increase in concentrations of ethanol when compared to the P7-WT. Butyric acid production from 3 P7-EMS mutants contained an average of a 3.85 fold increase over the levels observed in the P7-WT cultures under the same conditions (CO 2 only). In addition, one P7-EMS mutant presented butanol production (0.23 ± 0.02 g/L), which was absent from the P7-WT under CO 2 conditions. Most of the P7-EMS mutants showed stability of the obtained end product traits after three transfers. Most importantly, the amount of reduced atmospheric CO 2 increased up to 8.72 times (0.21 g/Abs) for ethanol production and up to 8.73 times higher (0.16 g/Abs) for butyrate than the levels contained in the P7-WT. Additionally, to produce butanol, the P7-EMSIII-J mutant presented 0.082 g/Abs of CO 2 reduction. This study demonstrated the feasibility and effectiveness of employing EMS mutagenesis in generating solvent-producing anaerobic bacteria mutants with improved and novel product formation and increased atmospheric CO 2 reduction efficiency.

59 BASIC BIOLOGICAL SCIENCES↗