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DOE OSTI2021

Semi-automated Design of Artificial Intelligence Earth Systems Models

Prediction and observation of water cycles at various scales involve not only patterns isolated in space and time, but also modeling of complex spatio-temporal relationships across multiple domains. For instance, evapotranspiration (ET) and leaf area indexes (LAI) are two parameters that are needed to accurately model and understand land-atmosphere processes. Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFTs), which fail to capture fine-scale variations because of changes in vegetation type across the globe. Similarly LAI estimates have typically been derived from vegetation indices at global scales or estimated locally using physical models, both of which suffer from a range of uncertainties that impact model sensitivity. The new era of AI model development for Earth systems (ES) calls for data-driven methods that provide domain scientists with uncertainty-aware estimations of biophysical parameters such as ET and LAI in a generalizable, interpretable, and discoverable manner.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Usage of Observing System Simulation Experiments and Reinforcement Learning to Optimize Experimental Design and Operation

Various organizations regularly conduct field campaigns across the globe designed to probe and improve atmospheric process understanding. However, these campaigns are mostly designed ad-hoc, and rely on anecdotes and knowledge of what was successful in previous campaigns. Such ad-hoc experiment design results in sub-optimal instrument siting and operation strategies. Inadequate targeted data collection of extreme weather is a major limitation to Earth and Environmental Systems Science Division (EESSD)’s goals of data model integration (4.5.3), which limits the knowledge gained through the collected observations, holding back significant advances in predictability. While advances in instrument design are always chipping away at these limitations, we are not optimally utilizing the instrumentation we currently possess.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

LDRD 2022 Annual Report: Laboratory Directed Research and Development Program Activities

Each year, Brookhaven National Laboratory (BNL) is required to provide a report of its completed Laboratory Directed Research and Development Program (LDRD) projects to the Department of Energy (DOE) Office of Scientific and Technical Information in accordance with DOE Order 413.2C Chg1 (MinChg) dated August 2, 2018. This report provides a detailed look at the scientific and technical activities for each of the LDRD projects funded by BNL in FY 2022, in fulfillment of that requirement. In FY 2022, the BNL LDRD Program funded 70 projects, 30 of which were new starts, at a total cost of $17.2M. The investments that BNL makes in its LDRD program support the Laboratory’s strategic goals. BNL has identified seven scientific initiatives that define the Laboratory’s scientific future and that will enable it to realize its overall vision. This requires simultaneous excellence in all aspects of BNL’s work – from science and operations, to external partnerships with the local, state, and national communities, and beyond. This is enabled by safe, efficient, and secure operations; by an unwavering commitment to a diverse, equitable, and inclusive environment, including workforce development, both with staff and reaching out to the community; and by a strong focus on renewed infrastructure. The seven scientific initiatives are: 1) Nuclear Physics: uncover the structure of visible matter by constructing and operating the Electron-Ion Collider at BNL to maintain international leadership in nuclear physics for decades; 2) Clean Energy and Climate: support a net-zero U.S. economy through fundamental research in basic energy and climate sciences to revolutionize grid-scale storage, renewable integration, and the study of atmospheric processes with a new facility to improve climate predictability; 3) Quantum Information Science and Technology: discover new quantum materials to enhance quantum computers and develop an entanglement sharing quantum network as a prototype for the first quantum internet; 4) Discovery Science Driven by the Human-AI Facility Integration: revolutionize the operation of experiments across the sciences at user facilities and in core programs; 5) High Energy Physics: understand the origin of space and time with the ATLAS high luminosity upgrade at CERN and the future Long Baseline Neutrino Facility/Deep Underground Neutrino Experiment; 6) Isotope Production: accelerate and expand isotope production to ensure the security of the Nation’s supply; 7) Accelerator Science and Technology: harness the cross-cutting accelerator science expertise at BNL to develop new facilities, improve and expand its user facilities, and promote the use of accelerators in industry. The funded projects support BNL’s seven scientific initiatives and priority programs as well as new areas of research and competencies at the Laboratory that are consistent with the Laboratory’s vision and mission. In total, these LDRD investments supported 43 postdoctoral researchers in whole or in part and resulted in 138 publications and 7 awards. This Program Activities Report represents the future of BNL science; it is an impressive body of exploratory work that investigates many scientific and technical directions in support of the DOE and BNL missions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Entrainment and aerosol effects on marine boundary-layer clouds: An investigation using ACE-ENA data from HOLODEC, G1, Pico and ACTOS (Final Report on Project Activities)

Marine boundary-layer clouds cover large regions of the globe and are known to strongly influence radiative balances. The microphysical properties and persistence of these clouds are tightly coupled with cloud-top entrainment and aerosol properties within both the boundary layer and the overlying free troposphere. This work addressed the microphysical response to entrainment and aerosol properties in marine stratocumulus clouds, using data from the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) project. Specifically, emphasis was placed on 1. extensive in situ measurements taken with the Atmospheric Radiation Measurement (ARM) G1 aircraft using the Holographic Detector for Clouds (Holodec) instrument; 2. airborne measurements obtained with the helicopter-borne Airborne Cloud Turbulence Observation System (ACTOS) operated by the Leibniz Institute for Tropospheric Research (TROPOS) during the first phase of ACE-ENA; and 3. above-boundary-layer, mountain-top measurements taken at the Pico Mountain Observatory (OMP) by the research group of the co-investigator and scientists from TROPOS during the first phase of ACE-ENA. The work is aligned with the topic “Warm Boundary-Layer Atmospheric Processes.” Key results include the following. Data from the Holographic Detector for Clouds (Holodec) were reprocessed, refined, and validated through a careful instrument intercomparison, resulting in a high-quality dataset available on the ARM archive for ACE-ENA. High-resolution ACTOS measurements of thermodynamics, microphysical, and turbulence properties were analyzed to explore the behavior of the entrainment velocity at cloud top. Analysis of the vertical variability of cloud droplet size distribution shape suggests that mixing is more inhomogeneous near cloud top, and more homogeneous deeper into the cloud. Analysis of aerosol measurements from OMP explored the mixing state and cloud condensation nucleus properties, as well as the implications for radiative forcing. Finally, a machine learning algorithm was developed for identifying characteristic cloud droplet size distributions, and was employed to explore microphysical regimes in stratocumulus clouds observed during ACE-ENA. The characteristic size distributions are narrow, and only when spatially averaged do they produce the broad “gamma” distributions typically assumed in models. This implies that precipitation development should account for variability and correlations in the distribution shape as well as the number concentration of cloud droplets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mechanisms of Pacific decadal variability in ESMs: the roles of stochastic forcing, feedbacks & external forcing

This project explored how and why climate patterns in the Pacific Ocean—specifically Pacific Decadal Variability (PDV)—change over time, and how well leading Earth System Models (ESMs) capture these changes under different climate scenarios. By analyzing large climate model datasets and running new simulations, the team investigated how ocean and atmosphere processes interact to shape PDV. The study tested a leading scientific hypothesis using both simplified and complex models, helping to uncover the key mechanisms that drive long-term climate swings in the Pacific. This work improves our ability to detect, predict, and understand how human-driven climate change may influence major ocean-climate patterns in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

ARM Aerial Instrument Workshop Report

The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program is to “support transformative science and scientific user facilities to achieve a predictive understanding of complex biological, earth, and environmental systems for energy and infrastructure security, independence, and prosperity.” (https://science.osti.gov/ber) Aligned with the BER central mission, the Earth and Environmental Systems Sciences Division (EESSD) plays a vital role in supporting the fundamental research to understand and predict Earth’s climate and environmental systems, and is also in a unique position to inform the development of sustainable solutions to the nation’s energy and environmental challenges. Specifically, EESSD manages two scientific user facilities: the Atmospheric Radiation Measurement (ARM) user facility and the Environmental Molecular Sciences Laboratory (EMSL). These facilities provide the broader scientific community with scientific expertise, technical capabilities, and unique data sets to facilitate science in areas of importance to DOE. As a multi-platform scientific user facility, ARM aims to fulfill the needs predominantly within the EESSD Atmospheric System Research (ASR) and the Earth and Environmental System Modeling (EESM) mission areas, and provide the critical measurements required to improve understanding of aerosol and cloud life cycles and their interactions, and their coupling with the Earth’s surface. Over the years, ARM has carried out piloted and unmanned aircraft campaigns under different organizational and operational paradigms (Schmid et al. 2014, 2016). Building on its success, the ARM Aerial Facility (AAF) continues to complement the ground-based observations with airborne in situ cloud, aerosol, and trace gas observations as well as measurements of atmospheric state and atmospheric radiation. During the past three years, ARM has managed field campaigns using unmanned aerial systems (UAS) and tethered balloon systems (TBS) at Oliktok Point in Alaska to improve understanding of atmospheric processes in the Arctic. In 2019, following a careful evaluation of scientific community needs, ARM acquired a Bombardier Challenger 850 regional jet to replace the vintage Grumman Gulfstream-159 turboprop aircraft previously used by AAF. With this new “laboratory in the sky”, AAF is evaluating its current and future aerial observation capabilities to continue satisfying the needs of the research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Parametric Optimization of Nanostructured Alumina Forming Austenitic Alloys

Alumina-forming austenitic (AFA) alloys provide excellent oxidation resistance through the formation of a stable alumina scale, but their relatively high Ni content might limit application in core structural components because of helium generation and swelling under irradiation. Increasing the density of nanoscale features in the microstructure is a promising route to improve sink strength and mitigate these effects. Conventional oxide dispersion–strengthened (ODS) steels achieve this through mechanical alloying (MA), but the approach is costly and difficult to scale. In this milestone, additive manufacturing was applied as an alternative pathway to fabricate nanostructured AFA (NAFA) alloys with dual precipitation of oxides and nitrides enabled by reactive atmosphere processing. In FY25, two compositions, NAFA-1 (AFA-05) and NAFA-2, were produced and compared. Both alloys achieved densities above 99% of theoretical values, but NAFA-2 exhibited microcracking associated with Nb-rich intermetallic formation, indicating the need for further chemistry optimization. Nitrogen and oxygen uptake was confirmed on selected builds, demonstrating the intended dual-precipitate dispersion. Mechanical testing showed that AM-processed NAFA alloys exceed conventionally produced ODS steels in high-temperature tensile strength and fracture toughness. Preliminary Cu ion irradiation results further suggest improved resistance compared to wrought austenitic alloys. While the current alloys are promising for their compatibility in high-temperature air or liquid Pb environments, modifications to composition will be required for long-term operation in high-temperature impure sodium systems. Future work will focus on refining alloy chemistry to suppress laser powder bed fusion–induced cracking and scaling production to reactor-relevant dimensions using directed energy deposition as a pathway toward net-shape cladding fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2026

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↗
DOE OSTI2025

The Snow Albedo Evolution (SALVO) Campaign at the North Slope of Alaska Field Campaign Report

The springtime surface-albedo transition in the Alaskan Arctic, along with the forces that determine its duration and nature, was the focus of the Snow ALbedo eVOlution (SALVO) campaign. The SALVO team investigated the reasons and durations of the stages of spring melt, during which albedo values decrease from 0.8 to 0.1, signifying the year’s largest and most significant radiative energy change. SALVO II (2022, 2024) built on findings from the successful SALVO I (2019) melt season campaign and previous research on the melt transition period conducted by Grenfell and Perovich (2004). SALVO used the ARM NSA observatory, thus aligning with a core principle of the ARM Decadal Vision to “provide comprehensive and impactful field measurements to support scientific advancement of atmospheric process understanding.” SALVO fieldwork was conducted in the spring near the ARM NSA Central Facility in Utqiagvik, Alaska (Figure 1). Comprehensive data sets were collected in 2019, 2022, and 2024, which included spectral and broadband albedos, snow and meltwater depths, snow stratigraphy, snow grain size data, and aerial imagery. In April of each project year, before the snow began to melt, we established survey lines at three or four locations: inland tundra at NSA E12, coastal tundra at the NSA C1 site, Elson Lagoon, and offshore on the Chukchi Sea sea ice (2022 only). We set up a 200-meter-long line, marked every five meters, to enable repeated measurements of surface albedo and snow depth at each location. During most site visits, the SALVO II team dug at least one snow pit to assess the characteristics of the vertical snow layers, including the types and sizes of snow grains, snow density, and the distribution of liquid water. We evaluated the characteristics of flowing or pooled water at the bottom of the snowpack. Watching snow melt in the Arctic has been compared by some to being as exciting as watching paint dry, but it is far more exciting and dynamic than that. Initially, changes happen slowly while the snow cover remains above 80%, but then reductions in the albedo of the landscape, from about 0.8 to 0.4, combined with rising spring temperatures, begin to accelerate the melt. It happens so quickly that no matter how hard the field team works, they cannot keep up with documenting the changes. At first, liquid water is scarce—only a few wet layers of snow in the snowpack. But then, water becomes ubiquitous, transporting melt energy and creating an extremely heterogeneous albedo and melt landscape. At the end of each field season, the SALVO team is exhausted, relieved to see the snow gone, and joyful to play in the melt ponds on the sea ice under the midnight sun. Overall, the 2024 SALVO field campaign was a highlight, reflecting numerous lessons learned from 2019 and 2022. Daily measurements were taken more than 10 times at each site, resulting in a comprehensive time series of snow conditions and albedo. The team deployed using snowmachines and then on foot when snowmachine travel was no longer permitted on the melting tundra. Instrument mounts and packaging were optimized for quick deployment, regardless of the mode of transportation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Event Log / Raw Data

The WFIP3 event log is a curated record spanning 578 days of meteorological phenomena and field observations that complements the campaign’s high-frequency measurements. The log combines manually documented daily weather discussions with automatically derived indicators of key atmospheric processes, providing standardized, publicly available context to support model evaluation, forecast verification, and case-study selection for offshore boundary-layer research.

17 WIND ENERGY↗
DOE OSTI2023

A seamless approach for evaluating climate models across spatial scales

In regions of the world where topography varies significantly with distance, most global climate models (GCMs) have spatial resolutions that are too coarse to accurately simulate key meteorological variables that are influenced by topography, such as clouds, precipitation, and surface temperatures. One approach to tackle this challenge is to run climate models of sufficiently high resolution in those topographically complex regions such as the North American Regionally Refined Model (NARRM) subset of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 (E3SM v2). Although high-resolution simulations are expected to provide unprecedented details of atmospheric processes, running models at such high resolutions remains computationally expensive compared to lower-resolution models such as the E3SM Low Resolution (LR). Moreover, because regionally refined and high-resolution GCMs are relatively new, there are a limited number of observational datasets and frameworks available for evaluating climate models with regionally varying spatial resolutions. As such, we developed a new framework to quantify the added value of high spatial resolution in simulating precipitation over the contiguous United States (CONUS). To determine its viability, we applied the framework to two model simulations and an observational dataset. We first remapped all the data into Hierarchical Equal-Area Iso-Latitude Pixelization (HEALPix) pixels. HEALPix offers several mathematical properties that enable seamless evaluation of climate models across different spatial resolutions including its equal-area and partitioning properties. The remapped HEALPix-based data are used to show how the spatial variability of both observed and simulated precipitation changes with resolution increases. This study provides valuable insights into the requirements for achieving accurate simulations of precipitation patterns over the CONUS. It highlights the importance of allocating sufficient computational resources to run climate models at higher temporal and spatial resolutions to capture spatial patterns effectively. Furthermore, the study demonstrates the effectiveness of the HEALPix framework in evaluating precipitation simulations across different spatial resolutions. This framework offers a viable approach for comparing observed and simulated data when dealing with datasets of varying spatial resolutions. By employing this framework, researchers can extend its usage to other climate variables, datasets, and disciplines that require comparing datasets with different spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Long-term real-time chemical characterization of submicron aerosols at Montsec (southern Pyrenees, 1570 m a.s.l.)

Real-time measurements of inorganic (sulfate, nitrate, ammonium, chloride and black carbon (BC)) and organic submicron aerosols (particles with an aerodynamic diameter of less than 1 μm) from a continental background site (Montsec, MSC, 1570 m a.s.l.) in the western Mediterranean Basin (WMB) were conducted for 10 months (July 2011–April 2012). An aerosol chemical speciation monitor (ACSM) was co-located with other online and offline PM 1 measurements. Analyses of the hourly, diurnal, and seasonal variations are presented here, for the first time, for this region. Seasonal trends in PM 1 components are attributed to variations in evolution of the planetary boundary layer (PBL) height, air mass origin, and meteorological conditions. In summer, the higher temperature and solar radiation increases convection, enhancing the growth of the PBL and the transport of anthropogenic pollutants towards high altitude sites. Furthermore, the regional recirculation of air masses over the WMB creates a continuous increase in the background concentrations of PM 1 components and causes the formation of reservoir layers at relatively high altitudes. The combination of all these atmospheric processes results in a high variability of PM 1 components, with poorly defined daily patterns, except for the organic aerosols (OA). OA was mostly composed (up to 90%) of oxygenated organic aerosol (OOA), split in two types: semivolatile (SV-OOA) and low-volatility (LV-OOA), the rest being hydrocarbon-like OA (HOA). The marked diurnal cycles of OA components regardless of the air mass origin indicates that they are not only associated with anthropogenic and long-range-transported secondary OA (SOA) but also with recently produced biogenic SOA. Very different conditions drive the aerosol phenomenology in winter at MSC. The thermal inversions and the lower vertical development of the PBL leave MSC in the free troposphere most of the day, being affected by PBL air masses only after midday, when the mountain breezes transport emissions from the adjacent valleys and plains to the top of the mountain. This results in clear diurnal patterns of both organic and inorganic concentrations. OA was also mainly composed (71%) of OOA, with contributions from HOA (5%) and biomass burning OA (BBOA; 24%). Moreover, in winter sporadic long-range transport from mainland Europe is observed. The results obtained in the present study highlight the importance of SOA formation processes at a remote site such as MSC, especially in summer. Furthermore, additional research is needed to characterize the sources and processes of SOA formation at remote sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Aerosol optical hygroscopicity measurements during the 2010 CARES campaign

Measurements of the effect of water uptake on particulate light extinction or scattering made at two locations during the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) study around Sacramento, CA are reported. The observed influence of water uptake, characterized through the dimensionless optical hygroscopicity parameter γ, is compared with calculations constrained by observed particle size distributions and size-dependent particle composition. A closure assessment has been carried out that allowed for determination of the average hygroscopic growth factors (GFs) at 85% relative humidity and the dimensionless hygroscopicity parameter κ for oxygenated organic aerosol (OA) and for supermicron particles (defined here as particles with aerodynamic diameters between 1 and 2.5 microns), yielding κ = 0.1–0.15 and 0.9–1.0, respectively. The derived range of oxygenated OA κ values are in line with previous observations. The relatively large values for supermicron particles is consistent with substantial contributions of sea-salt-containing particles in this size range. Analysis of time-dependent variations in the supermicron particle hygroscopicity suggest that atmospheric processing, specifically chloride displacement by nitrate and the accumulation of secondary organics on supermicron particles, can lead to substantial depression of the observed GF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Ubiquitous influence of wildfire emissions and secondary organic aerosol on summertime atmospheric aerosol in the forested Great Lakes region

Long-range aerosol transport affects locations hundreds of kilometers from the point of emission, leading to distant particle sources influencing rural environments that have few major local sources. Source apportionment was conducted using real-time aerosol chemistry measurements made in July 2014 at the forested University of Michigan Biological Station near Pellston, Michigan, a site representative of the remote forested Great Lakes region. Size-resolved chemical composition of individual 0.5–2.0 µm particles was measured using an aerosol time-of-flight mass spectrometer (ATOFMS), and non-refractory aerosol mass less than 1 µm (PM 1 ) was measured with a high-resolution aerosol mass spectrometer (HR-AMS). The field site was influenced by air masses transporting Canadian wildfire emissions and urban pollution from Milwaukee and Chicago. During wildfire-influenced periods, 0.5–2.0 µm particles were primarily aged biomass burning particles (88 % by number). These particles were heavily coated with secondary organic aerosol (SOA) formed during transport, with organics (average O∕C ratio of 0.8) contributing 89 % of the PM 1 mass. During urban-influenced periods, organic carbon, elemental carbon–organic carbon, and aged biomass burning particles were identified, with inorganic secondary species (ammonium, sulfate, and nitrate) contributing 41 % of the PM 1 mass, indicative of atmospheric processing. With current models underpredicting organic carbon in this region and biomass burning being the largest combustion contributor to SOA by mass, these results highlight the importance for regional chemical transport models to accurately predict the impact of long-range transported particles on air quality in the upper Midwest, United States, particularly considering increasing intensity and frequency of Canadian wildfires.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Secondary sulfate is internally mixed with sea spray aerosol and organic aerosol in the winter Arctic

Abstract. Few measurements of aerosol chemical composition have been made during the winter–spring transition (following polar sunrise) to constrain Arctic aerosol–cloud–climate feedbacks. Herein, we report the first measurements of individual particle chemical composition near Utqiaġvik (Barrow), Alaska, in winter (seven sample days in January and February 2014). Individual particles were analyzed by computer-controlled scanning electron microscopy with energy dispersive X-ray spectroscopy (CCSEM-EDX, 24 847 particles), Raman microspectroscopy (300 particles), and scanning transmission X-ray microscopy with near-edge X-ray absorption fine structure spectroscopy (STXM-NEXAFS, 290 particles). Sea spray aerosol (SSA) was observed in all samples, with fresh and aged SSA comprising 99 %, by number, of 2.5–7.5 µm diameter particles, 65–95 % from 0.5–2.5 µm, and 50–60 % from 0.1–0.5 µm, indicating SSA is the dominant contributor to accumulation and coarse-mode aerosol during the winter. The aged SSA particles were characterized by reduced chlorine content with 94 %, by number, internally mixed with secondary sulfate (39 %, by number, internally mixed with both nitrate and sulfate), indicative of multiphase aging reactions during transport. There was a large number fraction (40 % of 1.0–4.0 µm diameter particles) of aged SSA during periods when particles were transported from near Prudhoe Bay, consistent with pollutant emissions from the oil fields participating in atmospheric processing of aerosol particles. Organic carbon and sulfate particles were observed in all samples and comprised 40–50 %, by number, of 0.1–0.4 µm diameter particles, indicative of Arctic haze influence. Soot was internally mixed with organic and sulfate components. All sulfate was mixed with organic carbon or SSA particles. Therefore, aerosol sources in the Alaskan Arctic and resulting aerosol chemical mixing states need to be considered when predicting aerosol climate effects, particularly cloud formation, in the winter Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic

To investigate the influence of sea ice openings like leads on wintertime Arctic clouds, the air mass transport is exploited as a heat and humidity feeding mechanism which can modify Arctic cloud properties. Cloud microphysical properties in the central Arctic are analysed as a function of sea ice conditions during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020. The Cloudnet classification algorithm is used to characterize the clouds based on remote sensing observations and the atmospheric thermodynamic state from the observatory on board the research vessel (RV) Polarstern. To link the sea ice conditions around the observational site with the cloud observations, the water vapour transport (WVT) being conveyed towards RV Polarstern has been utilized as a mechanism to associate upwind sea ice conditions with the measured cloud properties. This novel methodology is used to classify the observed clouds as coupled or decoupled to the WVT based on the location of the maximum vertical gradient of WVT height relative to the cloud-driven mixing layer. Only a conical sub-sector of sea ice concentration (SIC) and the lead fraction (LF) centred on the RV Polarstern location and extending up to 50 km in radius and with an azimuth angle governed by the time-dependent wind direction measured at the maximum WVT is related to the observed clouds. We found significant asymmetries for cases when the clouds are coupled or decoupled to the WVT and selected by LF regimes. Liquid water path of low-level clouds is found to increase as a function of LF, while the ice water path does so only for deep precipitating systems. Clouds coupled to WVT are found to generally have a lower cloud base and larger thickness than decoupled clouds. Thermodynamically, for coupled cases the cloud-top temperature is warmer and accompanied by a temperature inversion at the cloud top, whereas the decoupled cases are found to be closely compliant with the moist adiabatic temperature lapse rate. The ice water fraction within the cloud layer has been found to present a noticeable asymmetry when comparing coupled versus decoupled cases. This novel approach of coupling sea ice to cloud properties via the WVT mechanism unfolds a new tool to study Arctic surface–atmosphere processes. With this formulation, long-term observations can be analysed to enforce the statistical significance of the asymmetries. Furthermore, our results serve as an opportunity to better understand the dynamic linkage between clouds and sea ice and to evaluate its representation in numerical climate models for the Arctic system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

African smoke particles act as cloud condensation nuclei in the wintertime tropical North Atlantic boundary layer over Barbados

Abstract. The number concentration and properties of aerosol particles serving as cloud condensation nuclei (CCN) are important for understanding cloud properties, including in the tropical Atlantic marine boundary layer (MBL), where marine cumulus clouds reflect incoming solar radiation and obscure the low-albedo ocean surface. Studies linking aerosol source, composition, and water uptake properties in this region have been conducted primarily during the summertime dust transport season, despite the region receiving a variety of aerosol particle types throughout the year. In this study, we compare size-resolved aerosol chemical composition data to the hygroscopicity parameter κ derived from size-resolved CCN measurements made during the Elucidating the Role of Clouds–Circulation Coupling in Climate (EUREC4A) and Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) campaigns from January to February 2020. We observed unexpected periods of wintertime long-range transport of African smoke and dust to Barbados. During these periods, the accumulation-mode aerosol particle and CCN number concentrations as well as the proportions of dust and smoke particles increased, whereas the average κ slightly decreased (κ=0.46±0.10) from marine background conditions (κ=0.52±0.09) when the submicron particles were mostly composed of marine organics and sulfate. Size-resolved chemical analysis shows that smoke particles were the major contributor to the accumulation mode during long-range transport events, indicating that smoke is mainly responsible for the observed increase in CCN number concentrations. Earlier studies conducted at Barbados have mostly focused on the role of dust on CCN, but our results show that aerosol hygroscopicity and CCN number concentrations during wintertime long-range transport events over the tropical North Atlantic are also affected by African smoke. Our findings highlight the importance of African smoke for atmospheric processes and cloud formation over the Caribbean.

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

Weak influence of anthropogenic emissions on aerosol, cloud, and rain in the wet season of the Amazon rainforest

Anthropogenic emissions have been shown to affect new particle formation, aerosol concentrations, and clouds. Such effects vary with region, environmental conditions, and cloud types. In the wet season of Amazonia, anthropogenic emissions emitted from Manaus, Brazil, can significantly increase the cloud condensation nuclei (CCN) concentrations compared to the background of mainly natural aerosols. However, the regional response of cloud and rain to anthropogenic emissions in Amazonia remains very uncertain. Here, we aim to quantify how aerosol concentration, cloud, and rain respond to changes in anthropogenic emissions through parameterized new particle formation and primary aerosol emission in the Manaus region and to understand the underlying mechanisms. We ran the atmosphere-only configuration of the HadGEM3 climate model with a nested regional domain that covers most of the rainforest region (720 km by 1200 km with 3 km resolution) under scaled regional emissions. The 7 d simulations show that, in the areas that are affected by anthropogenic emissions, when aerosol and precursor gas emissions are doubled from the baseline emission inventories, aerosol number concentrations increase by 13 %. The nucleation rate that involves sulfuric acid and biogenic compounds generally increases with pollution levels. However, nucleation is suppressed very close to the pollution source, resulting in lower nucleation and soluble Aitken mode aerosol number concentrations. We also found that doubling the anthropogenic emission can increase the cloud droplet number concentrations ( N d ) by 9 %, but cloud water and rain mass mixing ratios do not change significantly. Even very strong reductions in aerosol number concentrations by a factor of 4, which is an unrealistic condition, cause only a 4 % increase in rain over the domain. If we assume our simulation has a fine enough grid resolution and an accurate representation of the relevant atmospheric processes, the simulated weak and non-linear response of cloud and rain properties to linearly scaled anthropogenic emissions suggests that the interactions among aerosol, cloud, and precipitation in the Amazonian convective environment are buffered by microphysical processes. It also implies that the convective environment is resilient to the changes in Nd that occur in response to localized anthropogenic aerosol perturbations.

Wang, Xuemei [University of Leeds (United Kingdom)↗