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DOE OSTI2025

CROCUS Dual Polarization Ceilometer Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, CROCUS Urban Integrated Field Laboratory (https://crocus-urban.org/). The dual-polarization ceilometer (Vaisala CL61) is an autonomous lidar system operating at 910 nm wavelength, providing valuable measurements for understanding atmospheric boundary layer evolution, air quality, and cloud-aerosol interactions. The CL61 measures the backscattered signal intensity alternating between parallel- and cross-polarization signals. The unique depolarization measurement capability improves discrimination between different particle types, such as liquid droplets, ice crystals, and aerosols. The depolarization is highly dependent on the scatterer shape and orientation (spherical vs non-spherical particles), with the linear depolarization ratio providing a measure of dominant backscatter signal component from atmospheric particles at various heights, essentially allowing discrimination between liquid and solid particles. With its efficient optical system, CL61’s improved signal-to-noise ratio compared to traditional ceilometers allows studying detailed vertical profiles of aerosols and clouds up to 15 km height.Datasets are stored in a netCDF data format, and we we encourage users to make use of the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements

Cloud condensation nuclei (CCN) number concentrations are an important aspect of aerosol–cloud interactions and the subsequent climate effects; however, their measurements are very limited. We use a machine learning tool, random decision forests, to develop a random forest regression model (RFRM) to derive CCN at 0.4 % supersaturation ([CCN0.4]) from commonly available measurements. The RFRM is trained on the long-term simulations in a global size-resolved particle microphysics model. Using atmospheric state and composition variables as predictors, through associations of their variabilities, the RFRM is able to learn the underlying dependence of [CCN0.4] on these predictors, which are as follows: eight fractions of PM 2.5 (NH 4 , SO 4 , NO 3, secondary organic aerosol (SOA), black carbon (BC), primary organic carbon (POC), dust, and salt), seven gaseous species (NO x , NH 3 , O 3 , SO 2 , OH, isoprene, and monoterpene), and four meteorological variables (temperature (T), relative humidity (RH), precipitation, and solar radiation). The RFRM is highly robust: it has a median mean fractional bias (MFB) of 4.4 % with ≈96.33 % of the derived [CCN0.4] within a good agreement range of -60% 2.5 speciation (NH 4 , SO 4 , NO 3 , and organic carbon (OC)), NO x , O 3 , SO 2 , T, and RH, as well as [CCN0.4] are available. We modify, optimize, and retrain the developed RFRM to make predictions from 19 to 9 of these available predictors. This retrained RFRM (RFRM-ShortVars) shows a reduction in performance due to the unavailability and sparsity of measurements (predictors); it captures the [CCN0.4] variability and magnitude at SGP with ≈67.02 % of the derived values in the good agreement range. This work shows the potential of using the more commonly available measurements of PM 2.5 speciation to alleviate the sparsity of CCN number concentrations' measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Global quantification of the dispersion effect with POLDER satellite data

Increased aerosols can modify the shape of the cloud Particle Size Distribution (PSD), thereby influencing the radiative properties of clouds, known as the Dispersion Effect (DE). However, a global, observation-based quantification of its impact on Aerosol-Cloud Interactions (ACI) is lacking, leading to DE being typically ignored in satellite-based estimates of ACI forcing. Here we propose a physics-based method that combines polarimetric satellite data on cloud PSD to achieve global observational quantification of DE’s impact on ACI in liquid-phase stratiform clouds. Globally, DE offsets ACI changes induced by droplet number concentration variation and liquid water path adjustment by 7% and −1.4%, respectively. Furthermore, a parameterization based on the global dataset of PSD shape parameters is developed to improve DE estimation in large-scale models. Both the quantification and parameterization enhance our understanding of DE and facilitate the inclusion of this non-negligible impact of DE on ACI in estimating aerosol climate forcing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Laboratory study of the heterogeneous ice nucleation on black-carbon-containing aerosol

Abstract. Soot and black carbon (BC) particles are generated in the incomplete combustion of fossil fuels, biomass, and biofuels. These airborne particles affect air quality, human health, aerosol–cloud interactions, precipitation formation, and climate. At present, the climate effects of BC particles are not well understood. Their role in cloud formation is obscured by their chemical and physical variability and by the internal mixing states of these particles with other compounds. Ice nucleation in field studies is often difficult to interpret. Nonetheless, most field studies seem to suggest that BC particles are not efficient ice-nucleating particles (INPs). On the other hand, laboratory measurements show that in some cases, BC particles can be highly active INPs under certain conditions. By working with well-characterized BC particles, our aim is to systematically establish the factors that govern the ice nucleation activity of BC. The current study focuses on laboratory measurements of the effectiveness of BC-containing aerosol in the formation of ice crystals in temperature and ice supersaturation conditions relevant to cirrus clouds. We examine ice nucleation on BC particles under water-subsaturated cirrus cloud conditions, commonly understood as deposition-mode ice nucleation. We study a series of well-characterized commercial carbon black particles with varying morphologies and surface chemistries as well as ethylene flame-generated combustion soot. The carbon black particles used in this study are proxies for atmospherically relevant BC aerosols. These samples were characterized by electron microscopy, mass spectrometry, and optical scattering measurements. Ice nucleation activity was systematically examined in temperature and saturation conditions in the ranges of 217≤T≤235 K and 1.0≤Sice≤1.5 and 0.59≤Swater≤0.98, respectively, using a SPectrometer for Ice Nuclei (SPIN) instrument, which is a continuous-flow diffusion chamber coupled with instrumentation to measure light scattering and polarization. To study the effect of coatings on INPs, the BC-containing particles were coated with organic acids found in the atmosphere, namely stearic acid, cis-pinonic acid, and oxalic acid. The results show significant variations in ice nucleation activity as a function of size, morphology, and surface chemistry of the BC particles. The measured ice nucleation activity dependencies on temperature, supersaturation conditions, and the physicochemical properties of the BC particles are consistent with an ice nucleation mechanism of pore condensation followed by freezing. Coatings and surface oxidation modify the initial formation efficiency of pristine ice crystals on BC-containing aerosol. Depending on the BC material and the coating, both inhibition and enhancement in INP activity were observed. Our measurements at low temperatures complement published data and highlight the capability of some BC particles to nucleate ice under low ice supersaturation conditions. These results are expected to help refine theories relating to soot INP activation in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Size-resolved ice nucleating particle (INP) concentrations from the MOSAiC campaign

Sample collection: Ground-based immersion mode ice nucleation measurements were conducted on samples collected at the U.S. DOE ARM AMF2 onboard the R/V Polarstern P-deck during MOSAiC from 23 Oct 2019 to 01 Oct 2020. Samples were collected using a Davis Rotating-drum Unit for Monitoring (DRUM; DRUMAir, LLC) cascading impactor in 4 stages (i.e., size bins). Instrument information on the model used, the DA400, can be found at the DRUMAir website (http://www.drumair.com/). Stages A, B, C, and D had particle size cuts at 2.96, 1.21, 0.34, and 0.15 µm in particle diameter, respectively. Strips of sample substrate (PFA, perfluoroalkoxy; McMaster) were adhered to each disc in each stage and coated with petrolatum to enable particles to stick on impact. The discs move slowly over time, such that aerosol loading is streaked onto the PFA. Every 24 hours, a blank is created on the PFA to separate daily samples. During MOSAiC, the pump typically pulled 20 – 35 lpm (average of 32 lpm) at the inlet with all the discs in place in each stage. Daily samples were collected for each of the four stages, equaling 28,800 – 50,400 total L of air (average of 46,080 L total L of air) per sample. Discs rotated for approximately 24 days before the sampling per strip was complete and changed to a new disc. Discs were stored frozen after collection. Sample preparation for analysis: Following collection and transport from MOSAiC to the Kreidenweis/DeMott laboratory, care of PI Creamean, in Fort Collins, CO, strips were removed from the discs and cut up to separate daily samples. Each daily portion of the strip was stored in separate sterile 15-mL centrifuge tubes and stored in a standard commercial freezer until analysis (approximately 4 – 12 months after collection). Sample analysis: Drop freezing assays (DFAs) were conducted on one daily sample set every 3 – 4 days of the study for all four stages using the Colorado State University (CSU) cold plate (CP). Sample set days were chosen to cover the entire year of MOSAiC and avoiding days where the AOS purge system was activated. Immediately after removal from the freezer, 2 mL of 0.1-µm filtered deionized water was added with a single-use sterile syringe directly to the tubes, then mixed using a vortex mixer for at least 30 minutes at 500 rpm to resuspend particles from the PFA into the deionized water. Following sample preparation, another single-use syringe was used to create 100 aliquots on a 3-inch diameter copper plate, then covered with a transparent plastic dome. The drops were approximately the same volume (2.5 µL each), though careful inspection. The plate was cooled at approximately 3 – 10 K min-1 from room temperature until all drops froze on the plate. Temperature was measured by an Omega thermocouple probes and meter. Drop freezing was visually detected but recorded through monitoring software to provide the time frozen, channel of the meter used, temperature, and cooling rate for each drop. Not all 100 drops were always detected; the total number of rows in each data file equals the number of drops recorded, which typically was > 80 %. Each sample was tested three times (i.e., a new set of 100 drops was created for each test). Data provided are files containing these parameters. From the freezing temperatures recorded, the fraction frozen was and INP concentrations were calculated per L of air using the equation from Vali (1971): [INPs] = −(ln(f)/Valiquot)*(Vsuspension/Vair) where f is the proportion of droplets not frozen, Valiquot is the volume of each aliquot (i.e., 2.5e-6 L), Vsuspension is the volume of the suspension (i.e., 0.002 L), and Vair is the volume of air per sample (i.e., 36000 L). Data usage guidance: There are three files included with this dataset: (1) dumcp_inp_concentrations.csv which includes cumulative INP concentrations binned every 0.5 °C from 0 to –30 °C for all samples and size ranges (i.e., DRUM stages) processed via DFA using the CSU CP; (2) dumcp_inp_standard_deviation.csv which includes the standard deviations for all samples and temperatures in dumcp_inp_concentrations.csv; and (3) dumcp_blank_concentrations_standard_deviation.csv which includes the INP concentrations and standard deviations for the deionized water and PFA blanks binned every 0.5 °C from 0 to –30 °C. The first column in each file represents the freezing temperature in °C binned every 0.5 °C from 0 to –30 °C (first cell in this column = header = “temp”). The second column in each file represents the standard deviation of each temperature bin in °C (first cell in this column = header = “temperr”). For file (1) dumcp_inp_concentrations.csv, the remaining columns indicate the INP concentrations per L of air for each temperature bin. For each sample column, the header in the first row indicates the stage (i.e., size bin as “A_”, “B_”, “C_”, or “D_”) and date (“_yyyymmdd) of collection. For file (2) dumcp_inp_standard_deviation.csv, the remaining columns indicate the INP concentration standard deviation per L of air for each temperature bin. For each sample column, the header in the first row indicates the stage (i.e., size bin as “A_”, “B_”, “C_”, or “D_”) and date (“_yyyymmdd) of collection. For file (3) dumcp_blank_concentrations_standard_deviation.csv, the remaining columns indicate the INP concentrations and standard deviations for the deionized water blank (“di_0.1” and “di_0.1sd” for the concentrations and standard deviations, respectively) and PFA blank (“pfa” and “pfasd” for the concentrations and standard deviations, respectively). Please see Creamean et al. (2019a; 2018a; 2018b; 2019b) for additional details on DRUM sample collection and offline processing. For questions or help with data interpretation, contact Dr. Jessie Creamean (jessie.creamean@colostate.edu). References: Creamean, J. M., Mignani, C., Bukowiecki, N., and Conen, F.: Using spectra characteristics to identify ice nucleating particle populations during winter storms in the Alps, Atmos. Chem. Phys., 19, 8123–8140, 2019a. Creamean, J. M., Kirpes, R. M., Pratt, K. A., Spada, N. S., Maahn, M., de Boer, G., Schnell, R. C., and China, S.: Marine and terrestrial influences on ice nucleating particles during continuous springtime measurements in an Arctic oilfield location, Atmospheric Chemistry and Physics, 18, 18023-18042, 10.5194/acp-18-18023-2018, 2018a. Creamean, J. M., Primm, K. M., Tolbert, M. A., Hall, E. G., Wendell, J., Jordan, A., Sheridan, P. J., Smith, J., and Schnell, R. C.: HOVERCAT: A novel aerial system for evaluation of aerosol-cloud interactions, Atmospheric Measurement Techniques, 11, 3969-3985, 10.5194/amt-11-3969-2018, 2018b. Creamean, J. M., Cross, J. N., Pickart, R., McRaven, L., Lin, P., Pacini, A., Hanlon, R., Schmale, D. G., Ceniceros, J., Aydell, T., Colombi, N., Bolger, E., and DeMott, P. J.: Ice nucleating particles carried from below a phytoplankton bloom to the Arctic atmosphere, Geophys. Res. Lett., 46, 8572-8581, https://doi.org/10.1029/2019GL083039, 2019b. Vali, G.: Quantitative Evaluation of Experimental Results an the Heterogeneous Freezing Nucleation of Supercooled Liquids, Journal of the Atmospheric Sciences, 28, 402-409, 10.1175/1520-0469(1971)028<0402:qeoera>2.0.co;2, 1971.

4-stage DRUM aerosol collector (DA400),Ice nuclei,↗

DOE OSTI2015

Incorporating an advanced aerosol activation parameterization into WRF-CAM5: Model evaluation and parameterization intercomparison

Aerosol activation into cloud droplets is an important process that governs aerosol indirect effects. The advanced treatment of aerosol activation by Fountoukis and Nenes (2005) and its recent updates, collectively called the FN series, have been incorporated into a newly developed regional coupled climate-air quality model based on the Weather Research and Forecasting model with the physics package of the Community Atmosphere Model version 5 (WRF-CAM5) to simulate aerosol-cloud interactions in both resolved and convective clouds. The model is applied to East Asia for two full years of 2005 and 2010. A comprehensive model evaluation is performed for model predictions of meteorological, radiative, and cloud variables, chemical concentrations, and column mass abundances against satellite data and surface observations from air quality monitoring sites across East Asia. The model performs overall well for major meteorological variables including near-surface temperature, specific humidity, wind speed, precipitation, cloud fraction, precipitable water, downward shortwave and longwave radiation, and column mass abundances of CO, SO 2 , NO 2 , HCHO, and O 3 in terms of both magnitudes and spatial distributions. Larger biases exist in the predictions of surface concentrations of CO and NO x at all sites and SO 2 , O 3 , PM 2.5 , and PM 10 concentrations at some sites, aerosol optical depth, cloud condensation nuclei over ocean, cloud droplet number concentration (CDNC), cloud liquid and ice water path, and cloud optical thickness. Compared with the default Abdul-Razzack Ghan (2000) parameterization, simulations with the FN series produce ~107–113% higher CDNC, with half of the difference attributable to the higher aerosol activation fraction by the FN series and the remaining half due to feedbacks in subsequent cloud microphysical processes. With the higher CDNC, the FN series are more skillful in simulating cloud water path, cloud optical thickness, downward shortwave radiation, shortwave cloud forcing, and precipitation. Here, the model evaluation identifies several areas of improvements including emissions and their vertical allocation as well as model formulations such as aerosol formation, cloud droplet nucleation, and ice nucleation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Southern Ocean Sulfate Aerosol Sources Quantified From Sulfur Isotopes in Antarctic Ice Cores

The Southern Ocean has emerged as a key region for constraining aerosol-climate interactions due to its relatively low anthropogenic influence. Sulfate is an important aerosol over the Southern Ocean, and models suggest dimethyl sulfide (DMS) is the largest source of sulfate during summer. However, sulfur isotopes of sulfate (δ 34 S(SO 4 2− )) in Antarctic ice cores suggest a significant contribution from a previously unexplained non-DMS source. Here we show that the fractional contribution from passive volcanic degassing (f volc ) explains observed δ 34 S(SO 4 2− ), and that a global chemical transport model underestimates f volc across Antarctica. Underestimated f volc implies that the model mischaracterizes sulfate sources in this important region. The discrepancy between observed and modeled sulfate sources can be reconciled by increasing passive volcanic sulfur degassing emissions and decreasing DMS emissions. Our results imply that current biases in emissions inventories could bias assessments of aerosol-cloud interactions in the Southern Ocean region and globally.

Jongebloed, Ursula A. [Univ. of Washington, Seattl↗

DOE OSTI2025

Multi-seasonal measurements of the ground-level atmospheric ice-nucleating particle abundance on the North Slope of Alaska

Atmospheric ice-nucleating particles (INPs) are an important subset of aerosol particles that are responsible for the heterogeneous formation of ice crystals. INPs modulate the arctic cloud phase (liquid vs. ice), resulting in implications for radiative feedbacks. The number of arctic INP studies investigating specific INP episodes or sources increased recently. However, existing studies are based on short-duration field data, and long-term datasets are lacking. Continuous, long-term measurements are key to determining the abundance and variability of ambient arctic INPs and constraining aerosol–cloud interactions, e.g., to verify and/or improve simulations of mixed-phase clouds. Here, we present a new long-duration INP dataset from the Arctic: 2 years of predominantly immersion-mode INP concentrations (n INP ) measured continuously at the National Oceanic and Atmospheric Administration's Barrow Atmospheric Baseline Observatory (BRW) on the North Slope of Alaska. A portable ice nucleation experiment chamber (PINE-03), which simulates adiabatic expansion cooling, was used to directly measure the ground-level INP abundance with an approximately 12 min time resolution from October 2021 to December 2023. We document PINE-03 n INP measurements as well as estimated ice nucleation active surface site density (n s ) over a wide range of heterogeneous freezing temperatures from −16 to −31 °C from which we introduce new season-specific parameterizations suitable for modeling mixed-phase clouds. Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient n INP , air mass origin region, and meteorological variability. Our findings suggest (1) very high freezing efficiency of INPs across the measured temperatures (n s ≈ 2×10 8 –10 10 m −2 for −16 to −31 °C), which is a factor of 10–1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in fall using the same instrument; (2) surprisingly high n INP (≥ 1 L −1 at −25 °C) for the examined temperatures throughout the year that were not measured by PINE-03 at other sites; and (3) high n INP in spring, possibly related to arctic haze episodes. Relatively low concentrations of aerosol surface area and contrasting high-INP concentrations at BRW relative to mid-latitude sites are the possible reasons for the observed high freezing efficiency.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

The Energy Exascale Earth System Model Version 3: 2. Overview of the Coupled System

The Energy Exascale Earth System Model version 3 (E3SMv3) represents the latest advancement in Earth system modeling developed by the U.S. Department of Energy (DOE). Building upon previous versions, E3SMv3 introduces significant updates across its coupled components to enhance capability and improve fidelity. The atmosphere component incorporates advancements in chemistry, aerosol-cloud interactions, convection, and microphysics. The ocean features a new time-stepping scheme and a higher-resolution unstructured mesh with sub-ice-shelf cavities, while the sea ice model integrates advanced snow and ice physics for more realistic cryospheric simulations. The land model introduces prognostic vegetation dynamics and a new sub-grid topographic treatment of solar radiation. A new tri-grid configuration harmonizes the horizontal grids of the land and river components for improved process coupling. It is enabled by a new non-linear remapping between the atmosphere and land. E3SMv3 underwent extensive testing through a comprehensive simulation campaign, including pre-industrial control, idealized CO 2 experiments, and historical simulations spanning 1850–2024. The model demonstrates significant improvements in simulating the evolution of the historical surface temperature, particularly addressing the “pothole cooling” bias in earlier versions. Reduced aerosol-related forcing contributes to more realistic radiative forcing and better alignment with the observational record. Ocean heat content (OHC) and sea ice trends are also improved as a result.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Characteristics and sources of fluorescent aerosols in the central Arctic Ocean

The Arctic is sensitive to cloud radiative forcing. Due to the limited number of aerosols present throughout much of the year, cloud formation is susceptible to the presence of cloud condensation nuclei and ice nucleating particles (INPs). Primary biological aerosol particles (PBAP) contribute to INPs and can impact cloud phase, lifetime, and radiative properties. We present yearlong observations of hyperfluorescent aerosols (HFA), tracers for PBAP, conducted with a Wideband Integrated Bioaerosol Sensor, New Electronics Option during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (October 2019–September 2020) in the central Arctic. We investigate the influence of potential anthropogenic and natural sources on the characteristics of the HFA and relate our measurements to INP observations during MOSAiC. Anthropogenic sources influenced HFA during the Arctic haze period. But surprisingly, we also found sporadic “bursts” of HFA with the characteristics of PBAP during this time, albeit with unclear origin. The characteristics of HFA between May and August 2020 and in October 2019 indicate a strong contribution of PBAP to HFA. Notably from May to August, PBAP coincided with the presence of INPs nucleating at elevated temperatures, that is, >–9°C, suggesting that HFA contributed to the “warm INP” concentration. The air mass residence time and area between May and August and in October were dominated by the open ocean and sea ice, pointing toward PBAP sources from within the Arctic Ocean. As the central Arctic changes drastically due to climate warming with expected implications on aerosol–cloud interactions, we recommend targeted observations of PBAP that reveal their nature (e.g., bacteria, diatoms, fungal spores) in the atmosphere and in relevant surface sources, such as the sea ice, snow on sea ice, melt ponds, leads, and open water, to gain further insights into the relevant source processes and how they might change in the future.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2001

Satellite Remote Sensing of the Liquid Water Sensitivity in Water Clouds

In estimation of the aerosol indirect effect, cloud liquid water path is considered either constant (Twomey effect) or increasing with enhanced droplet number concentrations (drizzle-suppression effect, or Albrecht effect) if cloud microphysics is the prevailing mechanism during the aerosol-cloud interactions. On the other hand, if cloud thermodynamics and dynamics are considered, the cloud liquid water path may be decreased with increasing droplet number concentration, which is predicted by model calculations and observed in ship-track and urban influence studies. This study is to examine the different responses of cloud liquid water path to changes of cloud droplet number concentration. Satellite data (January, April, July and October 1987) are used to retrieve the cloud liquid water sensitivity, defined as the changes of liquid water path versus changes of column droplet number concentrations. The results of a global survey reveal that 1) in at least one third of the cases the cloud liquid water sensitivity is negative, and the regional and seasonal variations of the negative liquid water sensitivity are consistent with other observations; 2) cloud droplet sizes are always inversely proportional to column droplet number concentrations. Our results suggest that an increase of cloud droplet number concentration leads to reduced cloud droplet size and enhanced evaporation, which weakens the coupling between water clouds and boundary layer in warm zones, decreases water supply from surface and desiccates cloud liquid water. Our results also suggest that the current evaluations of negative aerosol indirect forcing by global climate models (GCM), which are based on Twomey effect or Albrecht effect, may be overestimated.

Han, Qing-Yuan↗

NASA NTRS2008

Ground-Based Lidar Measurements During the CALIPSO and Twilight Zone (CATZ) Campaign

The CALIPSO and Twilight Zone (CATZ) field campaign was carried out between June 26th and August 29th of 2007 in the multi-state Maryland-Virginia-Pennsylvania region of the U.S. to study aerosol properties and cloud-aerosol interactions during overpasses of the CALIPSO satellite. Field work was conducted on selected days when CALIPSO ground tracks occurred in the region. Ground-based measurements included data from multiple Cimel sunphotometers that were placed at intervals along a segment of the CALIPSO ground-track. These measurements provided sky radiance and AOD measurements to enable joints inversions and comparisons with CALIPSO retrievals. As part of this activity, four ground-based lidars provided backscatter measurements (at 523 nm) in the region. Lidars at University of Maryland Baltimore County (Catonsville, MD) and Goddard Space Flight Center (Greenbelt, MD) provided continuous data during the campaign, while two micro-pulse lidar (MPL) systems were temporarily stationed at various field locations directly on CALIPSO ground-tracks. As a result, thirteen on-track ground-based lidar observations were obtained from eight different locations in the region. In some cases, nighttime CALIPSO coincident measurements were also obtained. In most studies reported to date, ground-based lidar validation efforts for CALIPSO rely on systems that are at fixed locations some distance away from the satellite ground-track. The CATZ ground-based lidar data provide an opportunity to examine vertical structure properties of aerosols and clouds both on and off-track simultaneously during a CALIPSO overpass. A table of available ground-based lidar measurements during this campaign will be presented, along with example backscatter imagery for a number of coincident cases with CALIPSO. Results indicate that even for a ground-based measurements directly on-track, comparisons can still pose a challenge due to the differing spatio-temporal properties of the ground and satellite observations. The multiple-lidar data during the CATZ campaign is expected to provide additional information on regional aerosol and cloud dynamics for give overpass, and enable a more realistic assessment of ground-to-satellite correlations. Future work is anticipated to finalize calibrated lidar backscatter profiles and utilization of wind trajectory information to further enable comparisons to CALIPS data.

Berkoff, Timothy↗

DOE OSTI2026

Polar primary aerosols across the ocean-sea ice-snow-atmosphere interface: From sources to impacts

Primary aerosols play a critical role in polar climate systems, influencing cloud formation, precipitation, radiative balance, and surface energy budgets. This paper provides a comprehensive synthesis of primary aerosol sources, transformation and removal processes, and broader atmospheric impacts in polar regions, emphasizing their links to ocean and sea ice biogeochemistry. These aerosols (including sea salt, primary organic aerosol, and primary biological aerosol particles) originate from marine and cryospheric environments and are emitted through physical processes, such as wave breaking, bubble bursting, and blowing snow. Emission sources include seawater, sea ice, snow, and freshwater from river discharge and glacial runoff. Once airborne, these particles can serve as a chemical reservoir, influencing atmospheric composition and reactivity, and as seeds for cloud droplet and ice crystal formation, influencing cloud microphysics and polar climate. Despite their importance, many of the processes governing primary aerosol emissions and transformations remain poorly constrained. The most pressing knowledge gaps pertain to emission processes, limited spatiotemporal observational coverage, instrumentation constraints, parameterization development, and the integration of interdisciplinary expertise. To improve our understanding of primary aerosol drivers and their response to climate, future research efforts should prioritize strategically coordinated and cross-disciplinary process studies, advancements in measurement technologies and coverage, and close collaboration between modelers and observational scientists to inform and refine model parameterizations. As polar regions continue to undergo profound changes marked by increased precipitation, reduced sea and land ice, freshening oceans, and shifting ecosystem dynamics, characterizing present-day primary aerosol populations is vital. Improved understanding will be essential for anticipating future changes in aerosol-radiation and aerosol-cloud interactions and their implications for polar and global climate systems.

Aerosol-cloud↗

DOE OSTI2025

Assessment of Extinction‐, Satellite‐, and Model‐Based Vertical Cloud Condensation Nuclei (CCN) Retrieval Methods Using Airborne CCN Measurements Over the Southern Great Plains

Abstract Accurate estimates of the vertical profile of cloud condensation nuclei (CCN) concentration are crucial to better quantify aerosol‐cloud interactions. We assessed the correlation between the vertical CCN concentrations obtained from extinction‐, satellite‐, and model‐based retrieval methods and airborne CCN concentrations collected at 0.24% supersaturation within the 3, 9, 27, and 81 km regions centered over the U.S. Department of Energy's Atmospheric Radiation Measurement User Facility Southern Great Plains (SGP) site during the spring and summer of 2016. The extinction profiles at a wavelength 355 nm were provided by the ground‐based Raman lidar. Our analysis showed moderate correlation between dry‐corrected extinction and airborne CCN data. We found the retrieved number concentration of CCN (RNCCN) method showed regression best‐fit slopes close to unity and consistent prediction errors for the majority of the data. The Lenhardt et al. (2023, https://doi.org/10.5194/amt‐16‐2037‐2023 ) method showed similar conclusions but only during spring, whereas the Mamouri and Ansmann (2016, https://doi.org/10.5194/acp‐16‐5905‐2016 ) method showed poor correlation. The Shinozuka et al. (2015, https://doi.org/10.5194/acp‐15‐7585‐2015 ) satellite‐based method exhibited reasonable agreement during summer but poor correlation during periods where both high (∼1,400 #/cm 3 ) and low (∼50 #/cm 3 ) airborne CCN concentrations were observed. The Copernicus Atmosphere Monitoring Service reanalysis modeled 3‐D CCN data set showed a moderate to weak positive correlation but performed poorly at high airborne CCN concentrations. Our analysis suggests the extinction‐based RNCCN method performed better than other methods across most observation periods under the diverse meteorological conditions observed at the SGP site.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Modeling the Impact of the Organic Aerosol Phase State on Multiphase OH Reactive Uptake Kinetics and the Resultant Heterogeneous Oxidation Timescale of Organic Aerosol in the Amazon Rainforest

Accurate predictions of chemical lifetime, i.e., oxidation timescale and change in the mass of organic aerosols (OAs) in atmospheric models, are critical to quantify the impacts of OA on aerosol–cloud interactions, radiative forcing, and air quality. The heterogeneous oxidation of OA by hydroxyl (OH) radicals is a key process governing OA mass changes during their oxidation. Recently, laboratory observations of the OH uptake coefficient (γ OH ) and heterogeneous reaction rate (k het,OH ) for different OA systems with varying phase states have been combined to develop a new parameterization of γ OH and k het,OH as a function of the OA phase state, i.e., viscosity (η OA ). Here, in this work, we use a recently published viscosity prediction framework to analyze the new γ OH and k het,OH parameterization with a box model. Subsequently, we implement this box model to predict γ OH and k het,OH over the Amazon rainforest in the dry-to-wet transition season with both significant biomass burning and biogenic influences. Relevant parameters within our box model are specified based on detailed regional model simulations over the Amazon using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). η OA is predicted as a function of species volatility, OA composition (including water uptake) along with ambient relative humidity (RH), and temperature. Based on ambient conditions simulated by WRF-Chem over the entire atmospheric column, we use the box model to predict the upper bounds of the heterogeneous oxidation timescale of OA. Based on previous laboratory measurements, we assume that this heterogeneous OH oxidation causes fragmentation (carbon loss) of OA, followed by the evaporation of the fragmented molecules that results in the exponential decay of OA. We predict that the oxidation timescale of OA is ~1 month near the Earth’s surface in the pristine Amazonian background because of low OH concentrations. But OA is oxidized more rapidly within urban and wildfire plumes near the Earth’s surface with an order of magnitude higher OH concentrations compared to the pristine background, causing the simulated oxidation timescale of OA to be much shorter, ~3–4 days. At 3–5 km altitudes where biomass burning OA is predicted to be semisolid, the heterogeneous oxidation timescale is estimated as ~6 days to 3 weeks and decreases with increasing OH concentrations within plumes. We show that the simulated mass loss of OA is strongly size-dependent, where smaller particles oxidize more rapidly compared to larger particles due to their greater per-particle surface area-to-volume ratio. Increasing urbanization and deforestation in the Amazon in the future might increase OH concentrations in the background Amazon, causing faster oxidation of OA. At higher altitudes above liquid clouds, especially in the upper troposphere where temperatures approach ~250 K, future measurements are needed to reduce the uncertainties related to the mass loss of OA at colder temperatures and low relative humidity conditions due to its heterogeneous OH oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Surface and free tropospheric sources of methanesulfonic acid over the tropical Pacific Ocean

The production of sulfate aerosols through marine sulfur chemistry is critical to the climate system. However, not all sulfur compounds have been studied in detail. One such compound is methanesulfonic acid (MSA). In this study, we use a one-dimensional chemical transport model to analyze observed vertical profiles of gas-phase MSA during the Pacific Atmospheric Sulfur Experiment (PASE). The observed sharp decrease in MSA from the surface to 600m implies a surface source of 4.0×107 molecules/cm2/s. Evidence suggests that this source is photolytically enhanced. We also find that the observed large increase of MSA from the boundary layer into the lower free troposphere (1000-2000m) results mainly from the degassing of MSA from dehydrated aerosols. We estimate a source of 1.2×107 molecules/cm2/s through this pathway. This source of soluble MSA potentially provides an important precursor for new particle formation in the free troposphere over tropics, affecting the climate system through aerosol-cloud interactions.

Zhang, Yuzhong↗

DOE OSTI2014

Aerosol effects on global land surface energy fluxes during 2003–2010

Abstract Aerosols affect downward solar radiation, impacting the terrestrial ecosystem carbon dynamics and energy budget. Here we apply a coupled modeling framework of a terrestrial ecosystem model and an atmospheric radiative transfer model to evaluate aerosol direct radiative effects on the surface heat fluxes of global terrestrial ecosystems during 2003–2010. We find that aerosol loadings decrease the mean latent heat flux by 2.4 Wm −2 (or evapotranspiration by 28 mm) and sensible heat flux by 16 Wm −2 . As a result, global mean soil moisture and water evaporative fraction have increased by 0.5% and 4%, respectively. Spatially, aerosol effects are significant in tropical forests and temperate broadleaf evergreen forests. This study is among the first quantifications of aerosols' effects on the heat fluxes of the global terrestrial ecosystems. The study further suggests that both direct and indirect aerosol radiative effects through aerosol‐cloud interactions should be considered to quantify the energy budget of the global terrestrial ecosystems.

Liu, Shaoqing↗

DOE OSTI2015

Aerosol variability, synoptic‐scale processes, and their link to the cloud microphysics over the northeast Pacific during MAGIC

Abstract Shipborne aerosol measurements collected from October 2012 to September 2013 along 36 transects between the port of Los Angeles, California (33.7°N, 118.2°), and Honolulu, Hawaii (21.3°N, 157.8°W), during the Marine ARM GPCI (Global Energy and Water Cycle Experiment (GEWEX)‐Cloud System Study (GCSS)‐Pacific Cross‐section Intercomparison) Investigation of Clouds campaign are analyzed to determine the circulation patterns that modulate the synoptic and monthly variability of cloud condensation nuclei (CCN) in the boundary layer. Seasonal changes in CCN are evident, with low magnitudes during autumn/winter, and high CCN during spring/summer accompanied with a characteristic westward decrease. CCN monthly evolution is consistent with satellite‐derived cloud droplet number concentration N d from the Moderate Resolution Imaging Spectroradiometer. One‐point correlation ( r ) analysis between the 1000 hPa zonal wind time series over a region between 125°W and 135°W, 35°N and 45°N, and the N d field yields a negative r (up to −0.55) over a domain that covers a zonal extent of at least 20° from the California shoreline, indicating that N d decreases when the zonal wind intensifies. The negative r expands southwestward as the zonal wind precedes N d by up to 3 days, suggesting a transport mechanism from the coast of North America mediated by the California low‐coastal jet, which intensifies in summer when the aerosol concentration and N d reach a maximum. A first assessment of aerosol‐cloud interaction (ACI) is performed by combining CCN and satellite N d values from the Fifteenth Geostationary Operational Environmental Satellite. The CCN‐ N d correlation is 0.66–0.69, and the ACI metric defined as ACI = ∂ln( N d )/∂ln(CCN) is high at 0.9, similar to other aircraft‐based studies and substantially greater than those inferred from satellites and climate models.

Painemal, David↗