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At least 217 records · Page 12

Understanding Commercial Building Energy Use in the Tulsa to Wichita Falls I-44 Corridor: Building Stock Segmentation for Retrofit Planning

This report is part of the second phase of a publication series focusing on approximately 100 different local geographies, or "clusters." Each report provides characteristic features and energy data for commercial buildings in a specific area to help policy makers at the city, county, and state level better understand building energy use and emissions. This report breaks down the energy consumption and emissions of the building stock in the counties shown in Figure 2 by building type, building size, end use, energy consumption, emissions, and segment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding Commercial Building Energy Use in the Central Gulf Coast Area: Building Stock Segmentation for Retrofit Planning

This report is part of the second phase of a publication series focusing on approximately 100 different local geographies, or "clusters." Each report provides characteristic features and energy data for commercial buildings in a specific area to help policy makers at the city, county, and state level better understand building energy use and emissions. This report breaks down the energy consumption and emissions of the building stock in the counties shown in Figure 2 by building type, building size, end use, energy consumption, emissions, and segment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding Commercial Building Energy Use in the Greater Dallas-Fort Worth Area: Building Stock Segmentation for Retrofit Planning

This report is part of the second phase of a publication series focusing on approximately 100 different local geographies, or "clusters." Each report provides characteristic features and energy data for commercial buildings in a specific area to help policy makers at the city, county, and state level better understand building energy use and emissions. This report breaks down the energy consumption and emissions of the building stock in the counties shown in Figure 2 by building type, building size, end use, energy consumption, emissions, and segment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding Commercial Building Energy Use in the Huntsville-Florence Area: Building Stock Segmentation for Retrofit Planning

This report is part of the second phase of a publication series focusing on approximately 100 different local geographies, or "clusters." Each report provides characteristic features and energy data for commercial buildings in a specific area to help policy makers at the city, county, and state level better understand building energy use and emissions. This report breaks down the energy consumption and emissions of the building stock in the counties shown in Figure 2 by building type, building size, end use, energy consumption, emissions, and segment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding Commercial Building Energy Use in the Duluth-Grand Forks-Fargo Area: Building Stock Segmentation for Retrofit Planning

This report is part of the second phase of a publication series focusing on approximately 100 different local geographies, or "clusters." Each report provides characteristic features and energy data for commercial buildings in a specific area to help policy makers at the city, county, and state level better understand building energy use and emissions. This report breaks down the energy consumption and emissions of the building stock in the counties shown in Figure 2 by building type, building size, end use, energy consumption, emissions, and segment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding Commercial Building Energy Use in the Omaha-Lincoln Area: Building Stock Segmentation for Retrofit Planning

This report is part of the second phase of a publication series focusing on approximately 100 different local geographies, or "clusters." Each report provides characteristic features and energy data for commercial buildings in a specific area to help policy makers at the city, county, and state level better understand building energy use and emissions. This report breaks down the energy consumption and emissions of the building stock in the counties shown in Figure 2 by building type, building size, end use, energy consumption, emissions, and segment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

The mission of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is to improve the understanding and representation of cloud and aerosol processes and their interaction with the Earth's surface in Earth system models (ESMs) by providing comprehensive field observations and supporting advanced data analytics. The ARM Cloud and Precipitation Measurements and Science Group (CPMSG) was chartered in March 2019 to help improve the performance and scientific impact of ARM measurements of clouds and precipitation. The group aims to identify and address gaps in measurement capabilities, maximize the scientific impact of ARM data, and effectively serve the scientific community. To achieve these goals, the group includes experts in cloud and precipitation science, as well as representatives from ARM infrastructure, including instrument mentors, engineers, data quality officers, and data product translators. Prior to CPMSG, early discussions on cloud and precipitation measurements primarily focused on improving radar systems, but have since evolved to include a broader scope involving radiometers and other instruments. Since its formation, the CPMSG has gathered feedback using science traceability matrices. CPMSG aims to keep these as living documents to show the measurement needs, scientific drivers, roadblocks, maturity of measurements and retrievals, and pathways to model improvements. The group meets quarterly to discuss and prioritize measurement and operational improvements.

54 ENVIRONMENTAL SCIENCES↗

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

The mission of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is to improve the understanding and representation of cloud and aerosol processes and their interaction with the Earth's surface in Earth system models (ESMs) by providing comprehensive field observations and supporting advanced data analytics. The ARM Cloud and Precipitation Measurements and Science Group (CPMSG) was chartered in March 2019 to help improve the performance and scientific impact of ARM measurements of clouds and precipitation. The group aims to identify and address gaps in measurement capabilities, maximize the scientific impact of ARM data, and effectively serve the scientific community. To achieve these goals, the group includes experts in cloud and precipitation science, as well as representatives from ARM infrastructure, including instrument mentors, engineers, data quality officers, and data product translators. Prior to CPMSG, early discussions on cloud and precipitation measurements primarily focused on improving radar systems, but have since evolved to include a broader scope involving radiometers and other instruments. Since its formation, the CPMSG has gathered feedback using science traceability matrices. CPMSG aims to keep these as living documents to show the measurement needs, scientific drivers, roadblocks, maturity of measurements and retrievals, and pathways to model improvements. The group meets quarterly to discuss and prioritize measurement and operational improvements.

54 ENVIRONMENTAL SCIENCES↗

ARM FY2026 Radar Plan

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility maintains a suite of advanced atmospheric radar systems that serve as critical tools in ARM’s mission to provide continuous, high-quality observations for advancing the understanding and modeling of atmospheric processes. These radar systems enable detailed characterization of clouds, precipitation, and dynamic structures in the atmosphere, supporting a broad range of scientific applications. The number of deployed systems exceeds what current staffing levels can fully support for continuous 24/7/365 operation. As such, it is essential to have a clearly defined and community-informed plan that prioritizes radar operations and communicates ARM’s strategy for sustaining and evolving these observational assets. This FY2026 Radar Plan outlines ARM’s approach to managing its radar portfolio—balancing scientific impact, operational feasibility, and long-term sustainability. It reflects ARM’s continued commitment to delivering calibrated, well-documented radar data products that enable process-level studies and support the development and evaluation of weather and climate models. Through this plan, ARM aims to ensure transparency in decision-making, alignment with user needs, and support for innovative science across the facility’s fixed and mobile observatories. Given uncertainties around the Fiscal Year (FY) 2026 budget, this plan was developed to assume business as usual and will be updated as budgets and plans may change. It should be noted that, given the limited timeframe involved, this plan will be more succinct than previous plans.

47 OTHER INSTRUMENTATION↗

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

ARM Trajectories Data Set Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s ARM Trajectories Data Set (ARMTRAJ) Value-Added Product (VAP) provides trajectory data sets initialized at ARM deployment coordinates and configured using ARM data sets. The six trajectory data sets support aerosol, cloud, planetary boundary layer, and related research (aerosol-cloud interactions, etc.), as well as studies using ARM Aerial Facility (AAF) and tethered balloon system (TBS) measurements. Trajectory calculations use the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model informed by the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis (ERA5) data set at its highest spatial resolution (~31 km). HYSPLIT also runs at multiple initial starting locations surrounding ARM deployments (in latitude/longitude and/or vertical coordinates), facilitating an ensemble for each sample in the data sets. The ensemble mean and variability reported in ARMTRAJ improve the fidelity and provide uncertainty estimates of trajectory coordinates, thermodynamic properties, and other output fields.

54 ENVIRONMENTAL SCIENCES↗

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

The mission of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is to improve the understanding and representation of cloud and aerosol processes and their interaction with the Earth's surface in Earth system models (ESMs) by providing comprehensive field observations and supporting advanced data analytics. The ARM Cloud and Precipitation Measurements and Science Group (CPMSG) was chartered in March 2019 to help improve the performance and scientific impact of ARM measurements of clouds and precipitation. The group aims to identify and address gaps in measurement capabilities, maximize the scientific impact of ARM data, and effectively serve the scientific community. To achieve these goals, the group includes experts in cloud and precipitation science, as well as representatives from ARM infrastructure, including instrument mentors, engineers, data quality officers, and data product translators. Prior to CPMSG, early discussions on cloud and precipitation measurements primarily focused on improving radar systems, but have since evolved to include a broader scope involving radiometers and other instruments. Since its formation, the CPMSG has gathered feedback using science traceability matrices. CPMSG aims to keep these as living documents to show the measurement needs, scientific drivers, roadblocks, maturity of measurements and retrievals, and pathways to model improvements. The group meets quarterly to discuss and prioritize measurement and operational improvements.

54 ENVIRONMENTAL SCIENCES↗

TRACER Radar b1 Data Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed the first ARM Mobile Facility (AMF1) to Houston, Texas for the Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign. The TRACER campaign was conducted from October 1, 2021 to September 30, 2022, with an intensive operational period (IOP) from June 1 to September 30, 2022. To investigate the life cycles of convective cells in the polluted and humid urban environment of Houston, ARM deployed cloud and precipitation radars, including the C-band Scanning ARM Precipitation Radar (CSAPR2), the X/Ka-band Scanning ARM Cloud Radar (SACR), and the Ka-band ARM Zenith cloud Radar (KAZR), as shown in Figure 1. This report presents an analysis of radar data quality, hardware calibrations, and radar data corrections.

54 ENVIRONMENTAL SCIENCES↗

The ARM Precipitation Best Estimate (PrecipBE) Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s Precipitation Best-Estimate (PrecipBE) Value-Added Product integrates multiple precipitation datastreams, accounting for data quality and instrument limitations, to deliver comprehensive per-precipitation event properties alongside ancillary ARM data set data. PrecipBE bundles all valid surface rainfall samples into artificial intelligence (AI)-ready tabular and time-series formats, reporting bundle means and uncertainty ranges. This per-event structure provides an insightful and easy-to-use resource for researchers analyzing precipitation characteristics.

54 ENVIRONMENTAL SCIENCES↗

ARM FY2025 Radar Plan

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is dedicated to delivering high-quality radar data that significantly advance our understanding of cloud and precipitation processes, improving climate models. With radars operating across diverse frequencies, scanning modes, and global climate conditions, extensive staffing is essential for effective management. Due to current staffing constraints, achieving the expected level of operational excellence requires a more strategic approach. To address this challenge, ARM has developed an operational radar plan for the upcoming Fiscal Year 2025 (FY25) based on budget and staffing considerations. This report summarizes the Fiscal Year 2024 (FY24) ARM radar-related activities and outlines the strategic plan for FY25. It presents a comprehensive radar plan that includes detailed activities, priorities, and a projected timeline aligned with the ARM radar roadmap. Key tasks, detailed in Table 1, cover various radar operational stages and coordinated efforts among ARM teams.

54 ENVIRONMENTAL SCIENCES↗

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud lifecycle in the Amazon rainforest

Atmospheric nanoparticles can significantly influence Earth’s climate if they grow to sizes large enough to nucleate cloud droplets. While the contribution of extremely low volatility vapors to nanoparticle growth has been discussed extensively, the role of semivolatile organics has been largely overlooked. Here we examine the growth and impacts of air pollution nanoparticles from an isolated metropolis amidst the Amazon rainforest. Although extremely low volatility organics are necessary for the initial growth of nanoparticles, model analysis suggests that dynamic gas-particle partitioning of semivolatile oxidation products of anthropogenic and natural hydrocarbons is predominantly responsible for the observed rapid growth to 50 nm. Furthermore, cloud-resolving simulations demonstrate that the grown particles appreciably modify shallow cloud droplet size distribution, suppress precipitation, and enhance the transition to deep clouds. With condensable semivolatile organics typically formed in greater proportion, similar nanoparticle growth and impacts on clouds could likely occur in heavily urbanized forested regions globally.

Zaveri, Rahul A↗

DATASET: Rapid growth of anthropogenic organic nanoparticles greatly alters cloud lifecycle in the Amazon rainforest

Atmospheric nanoparticles can significantly influence Earth’s climate if they grow to sizes large enough to nucleate cloud droplets. While the contribution of extremely low volatility vapors to nanoparticle growth has been discussed extensively, the role of semivolatile organics has been largely overlooked. Here we examine the growth and impacts of air pollution nanoparticles from an isolated metropolis amidst the Amazon rainforest. Although extremely low volatility organics are necessary for the initial growth of nanoparticles, model analysis suggests that dynamic gas-particle partitioning of semivolatile oxidation products of anthropogenic and natural hydrocarbons is predominantly responsible for the observed rapid growth to 50 nm. Furthermore, cloud-resolving simulations demonstrate that the grown particles appreciably modify shallow cloud droplet size distribution, suppress precipitation, and enhance the transition to deep clouds. With condensable semivolatile organics typically formed in greater proportion, similar nanoparticle growth and impacts on clouds could likely occur in heavily urbanized forested regions globally.

Zaveri, Rahul A↗

Polar Aerosol Vertical Structures and Characteristics Observed with a High Spectral Resolution Lidar at the ARM NSA Observatory

Aerosol vertical distributions impact both the direct and indirect radiative effects of aerosols. High Spectra Resolution Lidar (HSRL) separates between atmospheric molecular signals and aerosol particle signals and therefore can provide reliable measurements of aerosol properties. Six years of HSRL measurements between 2014 and 2019 from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) atmospheric observatory at Utqiaqvik are used to statistically analyze Arctic aerosol vertical distributions. The annual cycle of aerosol vertical distributions in terms of aerosol particulate backscatter coefficient ($β_p$), lidar scattering ratio (SR), and aerosol particulate depolarization ratio ($δ_p$) profiles at the wavelength of 532 nm shows that Arctic Haze events are prevalent in later winter and spring at the NSA site. Mineral dust is frequently presented in strong aerosol layers in the spring, fall, and winter seasons. Over the summer season, the NSA site has large aerosol loadings that are dominated by small spherical aerosol particles.

54 ENVIRONMENTAL SCIENCES↗