Ambient aerosol vertical profiles are critical for evaluating the role of aerosols in atmospheric chemistry and radiative transfer, but limited data on these profiles hinder our ability to fully assess their impact on the Earth's radiative balance. Here, we investigated the size-, time-, and altitude-resolved composition of individual particles and the bulk molecular composition of particle samples collected by an uncrewed aerial system─ArcticShark over the Southern Great Plains. Single-particle microanalysis shows that the free tropospheric (FT) samples are dominated (56-66%) by carbonaceous sulfate particles, while boundary layer (BL) samples are dominated (57-74%) by carbonaceous particles. Back-trajectory simulations suggest that FT particles are likely influenced by long-range transport and have undergone aqueous-phase processing. Conversely, in situ size distribution data show evidence of particle growth in the upper BL and just below the FT. This observation may indicate vertical transport of particles from an elevated aerosol layer in the FT, possibly linked to a new particle formation event. This observation is further supported by high-resolution molecular composition data, which reveals particle volatility increasing with increasing size, aligning with the growth event. This study aids in a fundamental understanding of the compositional and molecular specificity of vertically resolved organic aerosols to provide insights into particle size evolution for future atmospheric models.

This study presents the unique capability of the Department of Energy (DOE) ArcticShark – a mid-size fixed-wing uncrewed aerial system (UAS) – for measuring vertically resolved atmospheric properties over the Southern Great Plains (SGP) of the United States. Focusing on atmospheric states, such as ambient temperature, wind, and aerosol properties, we overview measurements from 32 research flights (∼ 97 flight hours) in 2023. The August operations, aided by a visual observer on a chase plane, allowed for extensive UAS coverage, surpassing typical UAS operation envelopes. Our data from March, June, and August 2023 reveal distinctive seasonal patterns within the atmospheric column through unique chemical composition measurements. In situ measurements combined with remote sensing retrievals and radiosonde measurements provided valuable insights into their consistency and complementarity. Furthermore, we demonstrate the capabilities of the ArcticShark through several case studies, including the analyses of correlations between UAS-derived atmospheric profiles and conventional radiosonde measurements, as well as the derivation of vertically resolved profiles of aerosol chemical, optical, and microphysical properties. These case studies highlight the versatility of the ArcticShark UAS as a powerful tool for comprehensive atmospheric research, effectively bridging data gaps and enhancing our understanding of vertical atmospheric structures in the region.

The spatial distribution of ambient aerosol particles significantly impacts aerosol- radiation-cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation-modeling integration, enabling an examination of how various assumptions about the organic-inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation -constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic -enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground -based cloud lidar measurements. This UAS-model-laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol-radiation-cloud interactions. SIGNIFICANCE STATEMENT: This study aims to introduce a framework harnessing the current midsize uncrewed aerial system (UAS) measurement capabilities to propel atmospheric research forward. By integrating observational constraints derived from offline chemical analysis with in situ UAS observations, we unveil the pivotal role of organic -enriched nanometer layers on aerosol optical and hygroscopic property profiles above the U.S. Southern Great Plains (SGP) observatory and showcase substantial improvements in the agreement between model results and ground -based cloud lidar measurements. This UAS-model-laboratory integration exemplifies how these advanced capabilities can revolutionize our understanding of aerosol-radiation-cloud interactions, offering unprecedented insights into the Earth system simulation.

Airborne measurements are pivotal for providing detailed, spatiotemporally resolved information about atmospheric parameters and aerosol and cloud properties, thereby enhancing our understanding of dynamic atmospheric processes. For 30 years, the US Department of Energy (DOE) Office of Science supported an instrumented Gulfstream 1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) Data Center and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated dataset was recently developed covering the final 6 years of G-1 operations (2013 to 2018, 10.5439/1999133; Mei and Gaustad, 2024). The integrated dataset includes data collected from 236 flights (766.4 h), which covered the Arctic, the US Southern Great Plains (SGP), the US West Coast, the eastern North Atlantic (ENA), the Amazon Basin in Brazil, and the Sierras de Cordoba range in Argentina. These comprehensive data streams provide much-needed insight into spatiotemporal variability in the thermodynamic quantities and aerosol and cloud properties for addressing essential science questions in Earth system process studies. This paper describes the DOE ARM merged G-1 datasets, including information on the acquisition, data collection challenges and future potentials, and quality control processes. It further illustrates the usage of this merged dataset to evaluate the Energy Exascale Earth System Model (E3SM) with the Earth System Model Aerosol-Cloud Diagnostics (ESMAC Diags) package.

Accurate airborne aerosol instrumentation is required to determine the spatial distribution of ambient aerosol particles, particularly when dealing with the complex vertical profiles and horizontal variations of atmospheric aerosols. A versatile water-based condensation particle counter (vWCPC) has been developed to provide aerosol concentration measurements under various environments with the advantage of reducing the health and safety concerns associated with using butanol or other chemicals as the working fluid. However, the airborne deployment of vWCPCs is relatively limited due to the lack of characterization of vWCPC performance at reduced pressures. Given the complex combinations of operating parameters in vWCPCs, modeling studies have advantages in mapping vWCPC performance.In this work, we thoroughly investigated the performance of a laminar-flow vWCPC using COMSOL Multiphysics (R) simulation coupled with MATLAB (TM). We compared it against a modified vWCPC (vWCPC model 3789, TSI, Shoreview, MN, USA). Our simulation determined the performance of particle activation and droplet growth in the vWCPC growth tube, including the supersaturation, D p , kel , 0 (smallest size of particle that can be activated), D p , kel , 50 (particle size activated with 50 % efficiency) profile, and final growth particle size D d under wide operating temperatures, inlet pressures P (30-101 kPa), and growth tube geometry (diameter D and initiator length L ini ) . The effect of inlet pressure and conditioner temperature on vWCPC 3789 performance was also examined and compared with laboratory experiments. The COMSOL simulation result showed that increasing the temperature difference ( Delta T ) between conditioner temperature T con and initiator T ini will reduce D p , kel , 0 and the cut-off size D p , kel , 50 of the vWCPC. In addition, lowering the temperature midpoint ( T mid = T con + T ini 2 ) increases the supersaturation and slightly decreases the D p , kel . The droplet size at the end of the growth tube is not significantly dependent on raising or lowering the temperature midpoint but significantly decreases at reduced inlet pressure, which indirectly alters the vWCPC empirical cut-off size. Our study shows that the current simulated growth tube geometry ( D = 6.3 mm and L ini = 30 mm) is an optimized choice for current vWCPC flow and temperature settings. The current simulation can more realistically represent the D p , kel for 7 nm vWCPC and also achieved good agreement with the 2 nm setting. Using the new simulation approach, we provide an optimized operation setting for the 7 nm setting. This study will guide further vWCPC performance optimization for applications requiring precise particle detection and atmospheric aerosol monitoring.

We assess the viability of deploying commercially available multispectral and thermal imagers designed for integration on small uncrewed aerial systems (sUASs, <25 kg) on a mid-size Group-3-classification UAS (weight: 25–600 kg, maximum altitude: 5486 m MSL, maximum speed: 128 m/s) for the purpose of collecting a higher spatial resolution dataset that can be used for evaluating the surface energy budget and effects of surface heterogeneity on atmospheric processes than those datasets traditionally collected by instrumentation deployed on satellites and eddy covariance towers. A MicaSense Altum multispectral imager was deployed on two very similar mid-sized UASs operated by the Atmospheric Radiation Measurement (ARM) Aviation Facility. This paper evaluates the effects of flight on imaging systems mounted on UASs flying at higher altitudes and faster speeds for extended durations. We assess optimal calibration methods, acquisition rates, and flight plans for maximizing land surface area measurements. We developed, in-house, an automated workflow to correct the raw image frames and produce final data products, which we assess against known spectral ground targets and independent sources. We intend this manuscript to be used as a reference for collecting similar datasets in the future and for the datasets described within this manuscript to be used as launching points for future research.

Commercially available multispectral and thermal imagers are commonly deployed for environmental monitoring on small uncrewed aerial systems (sUAS, <55 lbs). Our team assessed the challenges of deploying these imagers on a Group 3 classification UAS (weight: 55-1320 lbs, maximum altitude: 18,000 ft MSL, maximum speed: 250 kts) for the purpose of land-atmosphere interaction studies. A Micasense Altum multispectral imager was deployed on two very similar mid-sized (Group 3) UAS, a Mississippi State University (MSU) TigerShark XP and the Department of Energy (DOE) ArcticShark. This paper examines the effects of flight on imaging systems mounted on UASs flying at higher altitudes, faster speeds, and for longer duration, which near future technology will make more the norm. For these platforms we found that the acquisition rate may need to be higher to achieve a minimum 75% overlap, as required by certain post-processing algorithms. Additionally pre-flight calibration panel referencing was found to be problematic for converting flight images to reflectance, due to the changing illumination conditions during the extended duration flights. We developed an automated workflow to correct the image frames via data from an onboard hemispherical solar sensor mounted on the top of the airframe, and we assessed these data against known spectral ground targets and independent sources. Finally, this manuscript may be used as a reference for collecting similar datasets in the future. The datasets described within this manuscript may be used as a starting point for future research.

During the Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA), a variety of in situ optical sensors using shadow imaging, scattering and holography were deployed by the Atmospheric Radiation Measurement (ARM) Aerial Facility to determine cloud properties. Taking advantage of the wide, overlapping range of instrumentation, we compare in situ cloud data from several different measurement methods for droplets up to 100 µm. Data processing was tailored to the encountered conditions, leading to good agreement. Improvements include noise reduction for holography and better out-of-focus correction for shadow imaging. Comparison between direct liquid water content measurements and optical sensors showed better agreement at higher droplet number concentrations (>120/c m 3).

Aerosol generation techniques have expanded the utility of aerosol mass spectrometry (AMS) for offline chemical analysis of airborne particles and droplets. However, standard aerosolization techniques require relatively large liquid volumes (e.g., several milliliters) and high sample masses that limit their utility. Here we report the development and characterization of a micronebulization AMS (MN-AMS) technique that requires as low as 10 µL of sample and can provide the quantification of the nanogram level of organic and inorganic substances via the usage of an isotopically labeled internal standard (34SO42-). Using standard solutions, the detection limits for this technique were determined at 0.19, 0.75, and 2.2 ng for sulfate, nitrate, and organics, respectively. The analytical recoveries for these species are 104 %, 87 %, and 94 %, respectively. This MN-AMS technique was applied successfully to analyze filter and impactor samples collected using miniature particulate matter (PM) samplers deployable on uncrewed atmospheric measurement platforms, such as uncrewed aerial systems (UASs) and tethered balloon systems (TBSs). Chemical composition of PM samples collected from a UAS field campaign conducted at the Department of Energy's (DOE) Southern Great Plains (SGP) observatory was characterized. The offline MN-AMS data compared well with the in situ PM composition measured by a co-located aerosol chemical speciation monitor (ACSM). In addition, the MN-AMS and ion chromatography (IC) agreed well for measurements of sulfate and nitrate concentrations in the PM extracts. This study demonstrates the utility of combining MN-AMS with uncrewed measurement platforms to provide quantitative measurements of ambient PM composition.

With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, the ENA is periodically impacted by continental aerosols, making it an excellent location to study the cloud condensation nuclei (CCN) budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign was motivated by the need of comprehensive in situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation. The airborne deployments took place from 21 June to 20 July 2017 and from 15 January to 18 February 2018 in the Azores. The flights were designed to maximize the synergy between in situ airborne measurements and ongoing long-term observations at a ground site. Here we present measurements, observation strategy, meteorological conditions during the campaign, and preliminary findings. Finally, we discuss future analyses and modeling studies that improve the understanding and representation of marine boundary layer aerosols, clouds, precipitation, and the interactions among them.

Uncrewed Systems (UxS), including uncrewed aerial systems (UAS) and tethered balloon/kite systems (TBS), are significantly expanding observational capabilities in atmospheric science. Rapid adaptation of these platforms and the advancement of miniaturized instruments have resulted in an expanding number of datasets captured under various environmental conditions by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. In 2021, observational data collected using ARM UxS platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center (https://adc.arm.gov/discovery/#/, last access: 11 February 2022) and made publicly available at no cost for all registered users (https://doi.org/10.5439/1846798) (Mei and Dexheimer, 2022). These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research. This paper describes the DOE UAS/TBS datasets, including information on the acquisition, collection, and quality control processes, and highlights the potential scientific contributions using UAS and TBS platforms.

Capturing the vertical profiles and horizontal variations of atmospheric aerosols often requires accurate airborne measurements. With the advantage of avoiding health and safety concerns related to the use of butanol or other chemicals, water-based condensation particle counters have emerged to provide measurements under various environments. However, airborne deployments are relatively rare due to the lack of instrument characterization under reduced pressure at flight altitudes. This study investigates the performance of a commercial “versatile” water-based condensation particle counter (vWCPC, model 3789, TSI, Shoreview, MN, USA) under various ambient pressure conditions (500–920 hPa) with a wide range of particle total number concentrations (1500–70 000 cm−3). The effect of conditioner temperature on vWCPC 3789 performance at low pressure is examined through numerical simulation and laboratory experiments. We show that the default instrument temperature setting of 30 ∘C for the conditioner is not suitable for airborne measurement and that the optimal conditioner temperature for low-pressure operation is 27∘. Under the optimal conditioner temperature (27∘), the 7 nm cut-off size is also maintained. Additionally, we show that insufficient droplet growth becomes more significant under the low-pressure operation. The counting efficiency of the vWCPC 3789 can vary up to 20 % for particles of different chemical compositions (e.g., ammonium sulfate and sucrose particles). However, such variation is independent of pressure.

Numerical simulation of three-stage water-based CPC operation Assumption 1. Water vapor through a cylindrical growth tube is described by the energy equation of a Newtonian fluid under steady laminar flow conditions.2. The particle flow is assumed to be an incompressible Newtonian fluid with a fully developed parabolic flow profile: () = 0 �1 - 2 2 � = 0 (1 - 2 ), where 0 , r, and R represent initial velocity (m/s), radial position (mm), and growth tube radius, respectively, and x is the dimensionless length.3. Axial thermal diffusion and other second-order effects such as Stefan flow are ignored. Simplified 1-D heat and mass transferThe 1-D heat transfer: a partial differential equation of steady laminar flow: ℎ is the thermal diffusivity of the air, 0.215 cm 2 /sec at STP.At the other operation conditionThe 1-D mass transfer: a partial differential equation for partial vapor pressure: is the mass diffusivity of the water vapor, 0.251 cm 2 /sec (0.21 by Steve) at STP.At the other operation condition, , = (/1()) ⁄ *

In 2018, the Atmospheric Radiation Measurement Aerial Facility (AAF) deployed its G-1 research aircraft to the Sierras de Córdoba mountain range in north-central Argentina to support the research of environmental factors on deep convective cycles as part of the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The aircraft was fitted with a suite of instruments to holistically measure in situ the current state of the atmosphere. In this study, we organize the campaign's 22 flights by environmental conditions. Data from each flight was transected by the aircraft's position relative to cloud, allowing for in depth analysis of cloud processing on aerosol populations. My project was a case study of selected flights where warm, shallow orographic cumulus clouds were observed. During my time at PNNL, I worked towards my goals for the internship, which were both professional and educational goals. I learned about some of the instruments AAF uses on their aircraft campaign and utilized data from those instruments to perform my analysis. I improved my skills in the programming language Python. I gained the confidence to analyze data critically and independently, which has further encouraged and prepared me for graduate school level research. I also met many amazing scientists at PNNL. II INTRODUCTION Climate models are used to predict future climate and study processes that occur to better understand the climate system. Aerosols are solid or liquid particles suspended in the atmosphere. The biggest uncertainty in climate models are clouds and how aerosols can interact with and impact clouds1. The uncertainty from climate models is largely due to geographically limited datasets. Instrumentation is necessary to quantify the number of aerosols in the atmosphere. A large fraction of aircraft data is collected in the northern hemisphere. Most aircraft campaigns are away from severe storms due to dangerous atmospheric conditions or are over oceans that have horizontally uniform clouds. Aerosols have a direct effect on the amount of radiation absorbed on Earth's surface and an effect on clouds2,3. A fraction of aerosols, called cloud condensation nuclei (CCN), are needed for water to condense on to form cloud droplets. The number of aerosols in clouds is one factor that determines how long a cloud's lifetime is and if a cloud will precipitate or not4 .The more aerosols that are in a cloud, the smaller the droplets and smaller droplets are less likely to precipitate because they cannot get large enough to precipitate 2. Climate models that model cloud and aerosol interactions have uncertainty regarding aerosol concentrations. While we can observe aerosols from the surface, which is cheaper and easier to operate, it is important to consider where aerosols are vertically. Where the aerosols are vertically determines their atmospheric lifetime, which extends their spatial and temporal effect on the climate. Aerosols in the boundary layer, the layer in the atmosphere that is in contact with the surface, have a shorter lifetime, in the scale of hours, than in the free troposphere which is on a scale of days to weeks to months5. Aerosols in the boundary layer are the ones interacting with clouds. However, aerosols in the free troposphere can transport across the world and can get pulled into the boundary layer if there are strong vertical winds. Only in-situ measurements can give the true picture of where aerosols are vertically. In 2018, the Department of Energy's Atmospheric Radiation Measurement (ARM) group conducted the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) to study environmental factors on deep convective cycles in north-central Argentina. The campaign included the use of the ARM Mobile Facility (ARM) ground site as well as the use of the ARM Aerial Facility's (AAF) G-1 research aircraft. While the campaign was conducted for a total of 6 months, the aircraft flew for an intensive period of 6 week

The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft. A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain.