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DOE OSTI2025

Synoptic Weather Regime Classifications for December, January and February, from 2000 to 2025

The synoptic weather regime classification has become a highly demanded product for the ARM site in recent years. This type of regime classification has shown applications in various studies and topics, including aerosol-cloud interactions, land-atmosphere interactions, and cloud radiative effects. The VAP employs an unsupervised machine learning method, Self-organizing map (SOM), to classify weather regimes for each day of the AMF campaigns and fixed sites, using ERA5 data. This idea is mainly based on our published study for TRACER in Wang et al. (2022, JGR-A).

{node_som_ml,synop_wea_reg}↗

DOE OSTI2025

Synoptic Weather Regime Classifications for September, October and November, from 2000 to 2025

node_som_ml↗

DOE OSTI2025

Organic Acid Aerosol Measurements from the Mount Airy Site for CoURAGE

This study investigates the prevalence and distribution of organic acid aerosols in a rural environment using filter-based measurements collected in Mount Airy, Maryland, during the CoURAGE campaign from March 19th through June 12th 2025. PM2.5 filters quantify a range of organic acids commonly associated with secondary organic aerosol formation and atmospheric oxidation processes. Each filter was collected using a 15 LPM sampler and was extracted in ultrapure Millipore water (>18 MΩ), allowing water-soluble organic acids to be extracted into solution for analysis. The extracts were then examined using a Waters Acquity I-Class PLUS liquid chromatography system coupled to a Bruker Maxis-II ultra-high-resolution Q-TOF mass spectrometer with electrospray ionization, providing high-sensitivity detection and separation of target compounds. Concentrations of several key organic acids were quantified, including acetic, propionic, pyruvic, butyric, oxalic, isovaleric, valeric, malonic, maleic, succinic, glutaric, malic, adipic, and citric acids. These findings contribute to ongoing efforts to understand regional aerosol composition and their impacts on aerosol-cloud interactions.

Acetic acid↗

DOE OSTI2025

Sources and Composition of Organic Aerosols in the Central Arctic during Spring and Summer

Organic aerosols (OA) are a major component of Arctic aerosol mass and influence the region’s radiation budget, yet their sources and physicochemical properties remain largely unknown. We investigate OA sources and climate-relevant characteristics over the central Arctic Ocean in spring and summer, by applying positive matrix factorization to aerosol mass spectrometry data from two ship-based expeditions (2018 and 2020), complemented by total and interstitial aerosol measurements during fog periods. Six distinct OA factors were identified: haze-related OA, Arctic oxygenated OA, two mixed-OA types resembling biomass burning and primary marine OA linked to warm-air intrusions, marine OA, and hydrocarbon-related OA. Seasonal transitions strongly shaped OA composition. Following polar sunrise, highly oxygenated OA, likely formed secondarily from photo-oxidized volatile organic compounds, became dominant. After the polar vortex collapsed in May, episodic spikes in marine OA from the marginal ice zone appeared, alongside a reduced influence from Eurasian anthropogenic sources. These transitions influenced OA oxidation state and related properties including volatility, acidity, and hygroscopicity, highlighting the role of the Arctic spring atmosphere as an active photochemical reactor. Overall, OA was highly oxidized, with particles activated in fog during summer showing even greater oxidation, suggesting that central Arctic OA can be highly cloud active.

Arctic haze↗

DOE OSTI2025

Variability of Eastern North Atlantic Summertime Marine Boundary Layer Clouds and Aerosols Across Different Synoptic Regimes Identified With Multiple Conditions

Abstract This study estimates the meteorological covariations of aerosol and marine boundary layer (MBL) cloud properties in the eastern North Atlantic (ENA) region, characterized by diverse synoptic conditions. Using a deep‐learning‐based clustering model with mid‐level and surface daily meteorological data, we identify seven distinct synoptic regimes during the summer from 2016 to 2021. Our analysis, incorporating reanalysis data and satellite retrievals, shows that surface aerosols and MBL clouds exhibit clear regime‐dependent characteristics, whereas lower tropospheric aerosols do not. This discrepancy likely arises from synoptic regimes determined by daily large‐scale conditions, which may overlook air mass histories that predominantly dictate lower tropospheric aerosol conditions. Focusing on three regimes dominated by northerly winds, we analyze the Atmospheric Radiation Measurement Program (ARM) ENA observations on Graciosa Island in the Azores. In the subtropical anticyclone regime, fewer cumulus clouds and more single‐layer stratocumulus clouds with light drizzle are observed, along with the highest cloud droplet number concentration (Nd), surface cloud condensation nuclei (CCN) and surface aerosol levels. The post‐trough regime features more broken or multi‐layer stratocumulus clouds with slightly higher surface rain rate, and lower Nd and surface CCN levels. The weak trough regime is characterized by the deepest MBL clouds, primarily cumulus and broken stratocumulus clouds, with the strongest surface rain rate and the lowest Nd, surface CCN and surface aerosol levels, indicating strong wet scavenging. These findings highlight the importance of considering the covariation of cloud and aerosol properties driven by large‐scale regimes when assessing aerosol indirect effects using observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Impact of Turbulence Representation on the Relationship Between Cloud Feedback and Aerosol‐Cloud Interaction in an E3SMv2 Perturbed Parameter Ensemble

Recent studies reveal an anti‐correlation between global cloud feedback (CF) and effective radiative forcing due to aerosol‐cloud interaction (ERFaci) in Earth system models, but the physical mechanisms underlying it remain uncertain. Here we investigate how different turbulence representations contribute to this relationship over the global ocean using an ensemble of Energy Exascale Earth System Model version 2 simulations with perturbed turbulence parameters. The anti‐correlation appears only in the tropical ascent regime. In the Northern Hemisphere midlatitude and high latitude regimes, there is no significant correlation, and in the tropical marine low cloud and Southern Ocean regimes, the correlation is positive. These opposite correlations are primarily driven by opposing CF responses to perturbed parameters. We find that the mean‐state turbulent mixing strength affects both CF and ERFaci, enabling strong correlations in certain regimes. This study highlights the complex linkages between CF and ERFaci through turbulent processes across diverse cloud regimes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

The Amazon River‐Breeze Circulation Limits Detection of Aerosol‐Cloud Interactions in Warm Clouds

Increased aerosol concentrations can brighten low-level clouds and extend their lifetimes, but aerosol–cloud interactions (ACI) remain highly uncertain and difficult to quantify. We show that part of this uncertainty is caused by topographical influences on clouds, that is, those arising from land–water contrasts. This is demonstrated using satellite retrievals in regions with extensive river networks, such as the Amazon Basin. 15 years of MODerate resolution Imaging Spectroradiometer (MODIS) satellite data show cloud formation over the Amazon River basin is suppressed by 26% with warm low clouds above the river exhibiting a 22% smaller droplet effective radius and 18% higher droplet concentration ($N_d$) compared to adjacent land clouds. Thus, clouds above the river may appear polluted but are actually influenced by river-breeze circulations driven by the thermal contrast between the river and the surrounding land. These responses are robust in both wet and dry seasons, and tests using an improved MODIS retrieval product show cloud differences are unlikely due to retrieval artifacts. In situ measurements from the Green Ocean Amazon Experiment (GoAmazon) confirm that $N_d$ is elevated above rivers and are also higher when carbon monoxide concentrations are elevated near the large city of Manaus. Lagrangian airmass tracking over Manaus shows that regional-scale river-breeze circulations impact $N_d$ as much as the urban aerosol plume, complicating ACI attribution and highlighting the need to isolate land-surface effects to assess ACI in continental regions.

Aerosol-Cloud Interactions↗

DOE OSTI2025

Aerosol Influences on Cloud Water: Insights From ARM EPCAPE Observations With Explainable Machine Learning

This study employs an explainable machine learning (ML) framework (XGBoost-SHapley Additive exPlanations analysis) to investigate controlling factors on cloud liquid water path (LWP) using EPCAPE observations near the California coast. Aerosols are found to be the dominant factor explaining LWP variability, surpassing meteorological factors (MFs). By isolating aerosol effects from meteorological influences, the ML reveals a negative linear relationship between LWP and cloud droplet number concentration (Nd) in log space, likely driven by entrainment drying via evaporation-entrainment feedback. This aligns with the negative regime of the inverted-V relationship reported in previous studies, while no positive LWP responses are found due to a limited number of precipitating cases in EPCAPE. Furthermore, the sensitivity of LWP to Nd shows a non-linear dependence on MFs like moisture contrast between surface and free troposphere and lower-tropospheric stability. This occurs due to the interplay between the MFs' direct effects on entrainment drying and indirect effects through LWP adjustments.

EPCAPE observations↗

DOE OSTI2026

Marine Aerosol to Refinery Emissions: Transport and Evolution of CCN in the Houston Metropolitan Area and Their Impact on Cloud Formation

The Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) campaign aimed to untangle the impacts of contrasting aerosol sources on cloud microphysical properties within deep convective cells using airborne observations with the National Research Council Canada (NRC) Convair CV‐580 research aircraft. Horizontal and vertical gradients of aerosol number size distributions, total aerosol concentrations and cloud condensation nuclei (CCN) spectra were measured in the lower troposphere to quantify the impact of different aerosol sources on aerosol‐cloud interactions. This study focuses on a research flight dedicated to characterizing the aerosol and CCN properties in the Houston Metropolitan region and identifies five main categories of aerosols based on characteristics of aerosol number size distributions, their CCN properties and meteorological conditions. These categories encompassed more than two orders of magnitude differences in aerosol and CCN concentrations, yet their hygroscopic properties remained similar. Aerosol number size distributions and effective hygroscopicity parameters are used to generate continuous CCN spectra to represent the major aerosol types. The different CCN spectra are then incorporated into a 1‐D aerosol‐cloud parcel model using a large range of updrafts selected in the range of those observed during the ESCAPE campaign to assess the impact of the major aerosol sources in Houston on deep convective cloud microphysical properties.

aerosol-cloud interactions↗

DOE OSTI2025

Causal machine learning uncovers conditions for convective intensification driven by organic and sulfate aerosols

Aerosols are often hypothesized to invigorate deep convective clouds (DCCs), but observational evidence remains limited and inconclusive. Clarifying this hypothesis is critical for regions vulnerable to thunderstorms and flooding, particularly highly polluted coastal cities. Leveraging a novel causal discovery–inference pipeline and high-resolution observations near Houston, TX, we identify multiple causal pathways among aerosols (mostly organic and sulfate), DCCs, and meteorological factors. However, a direct causal link from aerosols to DCCs is found to be uncommon, occurring in less than 35% of analyzed scenarios, and is characterized by strong conditionality and nonlinearity. When aerosol impacts on DCCs do occur, they can be substantial, enhancing DCC core heights by approximately 1.7 km, with 92% of this effect concentrated in warmer-phase cloud regions. Notably, the presence of sea breezes and the inclusion of all measured aerosol particles each enhance DCCs in over 95% of aerosol-sensitive cases.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

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

Difficulty in using observations to isolate the impacts of aerosols from meteorology on deep convection often stems from inability to resolve the spatiotemporal variations in the environment serving as the storm’s inflow region. During the DOE TRacking Aerosol Convection interactions ExpeRiment (TRACER) in June-September 2022, a Texas A&M University (TAMU) team conducted a mobile field campaign to characterize the meteorological and aerosol variability in airmasses that serve as inflow to convection across the ubiquitous mesoscale boundaries associated with the sea- and bay-breezes in the Houston, Texas, region. These boundaries propagate inland over the fixed DOE Atmospheric Radiation Measurement (ARM) sites. However, convection occurs on either or both the continental or maritime sides or along the boundary. The maritime and continental airmasses serving as convection inflow may be quite distinct, with different meteorological and aerosol characteristics that fixed-site measurements cannot simultaneously sample. Thus, a primary objective of TAMU TRACER was to provide mobile measurements similar to those at the fixed sites, but in the opposite airmass across these moving mesoscale boundaries. TAMU TRACER collected radiosonde, lidar, aerosol, cloud condensation nuclei (CCN), and ice nucleating particle (INP) measurements on 29 enhanced operations days covering a variety of maritime, continental, outflow, and pre-frontal airmasses. This paper summarizes the TAMU TRACER deployment and measurement strategy, instruments, available datasets, and provides sample cases highlighting differences between these mobile measurements and those made at the ARM sites. We also highlight the exceptional TAMU TRACER undergraduate student participation in high impact learning activities through forecasting and field deployment opportunities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Summer Aerosol and Trace Gas Observations in Houston, Texas Using an Adaptable Mobile Facility

An aerosol container featuring a shared inlet system was deployed to Houston, Texas in July 2022, enabling direct, high-time-resolution in situ measurements of aerosols and trace gases. The internal rack system and floorplan was designed for adaptable modularity to elucidate aerosol physicochemical processes at fine scales. The design allowed for the deployment of a core instrument suite and additional customized research grade instruments. A heterogeneous mixture of aerosols was observed during three regimes: (1) intermittent black carbon (BC) and diurnal variations in aerosol chemical composition, (2) observed particle growth associated with SO 2 , (3) transported supermicron dust. The high variability of observed particles and gases in high time resolution indicated a complex urban area with multiple local and regional sources and processes. Particle growth rates of 7–16 nm/hr were observed for submicron particles during periods when SO 2 was >0.5 ppbv. Two periods of multi-day long-range transport events of dust from the African Sahara were observed in the supermicron and submicron particle modes with total mass concentrations up to 30 μg m −3 . Aerosol scattering angstrom exponents and extinction coefficients (B ext ) increased with humidity as a function of particle composition. The measurements demonstrate collaborative capabilities that can be used to increase observations of aerosol processing, microphysical and optical properties, internal mixing state, and supermicron aerosol that are not parameterized or missing in global Earth energy system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The Dual Nature of Entrainment-Mixing Signatures Revealed through Large-Eddy Simulations of a Convection-Cloud Chamber

Abstract Entrainment of subsaturated air into a cloud can influence its optical and microphysical properties in various ways, depending on the droplet evaporation and turbulent mixing time scales. Previous experiments in the Pi convection-cloud chamber have revealed that, given a fixed entrained air property, the mixing of entrained subsaturated air results in complete evaporation of some cloud droplets, with the rest remaining unchanged. This is a signature of inhomogeneous mixing. While comparing the results of entrainment with varying air properties, the mixing signature appears as if the subsaturated air is well mixed with the cloud to evenly reduce the droplets’ size. In other words, taken together, the experiments appear to have the signature of homogeneous mixing. To explore these results in a greater depth, we conduct large-eddy simulations combined with a bin microphysics scheme. Our results reproduce the similar signatures of inhomogeneous and homogeneous mixing, implying that LES can resolve the inhomogeneous mixing when the grid spacing is smaller than the entrained air parcel. Additionally, we observe that increasing the aerosol injection rate enhances the signature of inhomogeneous mixing, while coarser grid spacing diminishes it. Finally, the change in wall fluxes in response to various entrained air properties confirms that the homogeneous signature seen in the analysis of an ensemble of simulations is the result of various equilibrium states. This further strengthens the suggestion that the homogeneous mixing signature found in aircraft observations near the cloud top may result from combining entrainment events of different intensities, possibly caused by various-sized eddies. Significance Statement Large-eddy simulation and size-resolved microphysics can resolve time scales for turbulent mixing and evaporation and, therefore, are well suited for reproducing, extending, and interpreting the entrainment experiment in the Pi convection-cloud chamber. Our simulation results confirm (i) the inhomogeneous mixing signature for an individual entrainment event and (ii) the appearance of homogeneous mixing in an ensemble of entrainment episodes. Furthermore, we demonstrate that the inhomogeneous mixing signature is more pronounced in a polluted cloud, but coarser grid spacing in simulations may compromise the accuracy of this signature. Last, the homogeneous mixing signature results from various equilibrium states established for different entrainment intensities and adjusted wall fluxes, which are challenging to measure experimentally but can be easily analyzed in the simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Model Intercomparison of the Impacts of Varying Cloud Droplet–Nucleating Aerosols on the Life Cycle and Microphysics of Isolated Deep Convection

The microphysical impacts of aerosol particles on scattered isolated deep convective cells near Houston, Texas, on 19 June 2013, are examined using multiple cloud-resolving model (CRM) simulations initialized with vertical profiles of low and high concentrations of cloud droplet–nucleating aerosols. These simulations formed part of the Model Intercomparison Project (MIP) conducted by the Deep Convective Working Group of the Aerosol, Cloud, Precipitation and Climate (ACPC) initiative. Each CRM generated a field of convective cells representing those observed during the case study with varying degrees of accuracy. The Tracking and Object-Based Analysis of Clouds (tobac) cell-tracking algorithm was applied to each MIP CRM simulation to track relatively long-lived convective cells (20–60 min). Most of the CRMs produced similar aerosol loading impacts on the warm phase of tracked cell properties with reduced autoconversion and accretion growth of rain, increased cloud water, reduced rainfall, and reduced near-surface evaporation of rain. The sign of aerosol impacts on the warm-phase properties of the convective cells was also quite consistent over cell lifetimes with the greatest magnitude of influence in the first half of the life cycle in most CRMs. In contrast, the ice-phase response to aerosol loading was highly variable among CRMs and included increases or decreases in ice amounts at inconsistent stages of the cell life cycle and midlevel versus upper-level changes in ice. This intermodel variability in ice is indicative both of the complex indirect interactions between aerosols and ice-phase processes in deep convection and their associated parameterizations.

Aerosol-cloud interaction↗

DOE OSTI2025

Investigating Aerosol and Meteorological Influences on Convective Clouds in Houston, Texas, during the TRACER/ESCAPE Field Campaigns

Aerosols serve as cloud condensation nuclei, shaping the microphysical properties of cloud droplets. Aerosol effects on convective clouds are complex and remain controversial. The debate centers around the process of aerosol-induced invigoration of deep convection, a phenomenon that could significantly affect convective cloud properties but lacks robust evidence due to methodological limitations in observational approaches and questions about the robustness of modeling studies. Resolving these discrepancies is crucial for understanding how aerosols affect the atmosphere. Here, this study examines the effects of meteorological and aerosol parameters in a weakly synoptic-driven convective environment, where the influence of aerosols may be more pronounced and observable. Daily atmospheric soundings and aerosol concentrations from several ground instruments collected during the summer of 2022 in Houston, Texas, as part of the Tracking Aerosol Convection interactions Experiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) field campaigns are analyzed. Statistical learning methods are applied to uncover the complex relationships between aerosols, meteorology, and convective cloud characteristics, such as cell area and echo-top height. The findings reveal that higher aerosol concentrations are associated with narrower convective cells, which we argue contradicts the idea of stronger convection with increased aerosol loading. However, once the data are clustered by the synoptic environment, the relationship between aerosol loading and convective cell area diminishes, indicating that the covariablity between synoptic-scale weather patterns, local thermodynamics, and aerosol loading makes it challenging to draw definitive conclusions about the specific impacts of aerosols on convective cloud properties.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) (Final Campaign Report)

The Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) campaign was conducted at the National Oceanic and Atmospheric Administration’s (NOAA) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W, “BRW” hereafter), next to the Atmospheric Radiation Measurement (ARM) user facility NSA site and ~ 6 km northeast of the town of Utqiaġvik. The location of the NSA site is shown in Figure 1. Our observing period began in October 2021 and continued until May 2024. This campaign was funded by the U.S. Department of Energy (DOE) Office of Science Early Career Research Program through grant number DE-SC001879. This grant contains funding for three ARM field campaigns. The previous field campaigns were performed at ARM’s Southern Great Plains atmospheric observatory in Oklahoma (SGP; 36.6073° N, 97.4876° W) and the ARM’s Eastern North Atlantic atmospheric observatory on Graciosa Island, Azores (ENA; 39.0916° N, 28.0257° W). The ExINP-NSA campaign aims included: • Determining the number concentration of ice-nucleating particles (n INPs ) active at temperatures spanning the range of heterogeneous freezing processes (from ≈−30 °C to 0 °C) using a combination of online and offline measurements, • Determining whether local meteorological conditions and/or synoptic scale air mass transport impact INP abundance and/or ice nucleation efficiency, • Examining if the physicochemical properties of INPs relate to aerosol chemistry, and • Assessing if there is a similarity in INP properties across three ARM sites Multi-seasonal datasets of INP abundance in the NSA region were delivered from this campaign. This campaign also allowed researchers to perform a comprehensive analysis of atmospheric INPs based on long- term ground-based measurements in the Alaskan Arctic. Our data and results from the ExINP-NSA campaign will help refine current earth system models. One of the stated goals of ARM is to advance aerosol-cloud ice interaction, which will be a direct result of this campaign. Current earth system models poorly represent INPs, and the 15-minute time resolution data over several seasons generated during this campaign will provide an invaluable resource, especially combined with the datasets generated during two previous ARM ExINP campaigns. These datasets will allow for a greater understanding of ice nucleation processes as they may (or may not) relate to local meteorological processes and aerosol chemistry and will eventually help further the understanding of the Earth’s atmospheric processes and energy balance.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Dry and warm conditions in Australia exacerbated by aerosol reduction in China

A substantial decline in anthropogenic aerosols in China has been observed since the initiation of clean air actions in 2013. This study reveals a linkage between aerosol reductions in China and drier and warmer conditions in Australia. Aerosol decline in China trigger alterations in temperature and pressure gradients between the two hemispheres, leading to intensified outflow from Asia towards the South Indian Ocean, strengthening the Southern Indian Subtropical High and its related Southern Trade Winds. Consequently, this atmospheric pattern results in a moisture divergence over Australia. The reduction in surface moisture further results in more surface energy being converted into sensible heat instead of evaporating as latent heat, warming the near-surface air. The intensified dry and warm climate conditions further cause the increase in wildfire risks during fire seasons in Australia. Our study illuminates the potential impact of distant aerosols on precipitation and temperature variations in Australia, offering valuable insights for drought and wildfire risk mitigation in Australia.

aerosol-cloud interaction↗

DOE OSTI2026

Understanding the causes of satellite–model discrepancies in aerosol–cloud interactions using near-LES simulations of marine boundary layer clouds

Aerosol–cloud interactions (ACI) remain the largest source of uncertainty in model estimates of anthropogenic radiative forcing, primarily because of deficiencies in representing aerosol–cloud microphysical processes that lead to inconsistent cloud liquid water path (LWP) responses to aerosol perturbations between observations and models. To investigate this discrepancy, we conducted a series of large-eddy-scale simulations driven by realistic meteorology over the eastern North Atlantic, and evaluated LWP susceptibility, precipitation processes, and boundary layer thermodynamics using satellite and ground-based observations. Simulated LWP responses show a strong dependence on cloud state. Non-precipitating thin clouds exhibit a modest LWP decrease with increasing cloud droplet number concentration (N d ), consistent in sign but weaker in magnitude than satellite estimates, reflecting enhanced turbulent mixing and evaporation. The largest model-observation discrepancy occurs in non-precipitating thick clouds, where simulated LWP susceptibilities are strongly positive (+0.32) while observations indicate large negative values (−0.69). This discrepancy stems from excessive precipitation driven by underestimated entrainment, overly active accretion, and overly broad drop-size distributions in polluted conditions. While our high-resolution setup mitigates the excessive drizzling common in coarser models and captures key regime transitions, these biases persist – highlighting that improved parameterizations of cloud-top processes, precipitation, and aerosol effects are needed beyond simply increasing model resolution. Additionally, misrepresented moisture inversions in reanalysis introduce a moist bias in cloud-top relative humidity, further amplifying positive LWP susceptibility. Our results also suggest that large negative N d –LWP relationships in observations may reflect internal cloud processes rather than true ACI effects.

Aerosol-cloud interaction↗