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DOE OSTI2023

Scanning Mobility Particle Sizer (SMPS)-Aerodynamic Particle Sizer (APS) Merged Size Distribution (mergedsmpsaps) Value-Added Product Report

Aerosol particles influence the Earth’s radiation balance directly by absorbing and scattering light and indirectly by influencing cloud formation, properties, and lifetimes. Measurements of aerosol particle optical properties, mass loading, size distributions, microphysical properties, cloud formation properties, and chemical composition are important for understanding the aerosol life cycle and for validating earth system models that predict these quantities. The Atmospheric Radiation Measurement (ARM) user facility’s Aerosol Observing System (AOS) is a highly instrumented platform designed to house instruments that measure many of these aerosol properties in situ. Currently, ARM operates at least four different instruments that measure a portion of the ambient aerosol size distribution. Most users are interested in the entire size distribution or a portion of the size distribution that extends across the measurement range of multiple instruments. However, merging these distributions is not trivial as the instruments employ different measurement principals and, in most cases, report data as a function of different representations of the aerosol diameter.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

TRACER-MAP Field Campaign Report

During July-August 2022, the U.S. Department of Energy (DOE) Atmospheric System Research (ASR)-funded Tracking Aerosol Convection Interactions Experiment (TRACER)-MAP campaign completed an Atmospheric Radiation Measurement (ARM) user facility field study to measure and map aerosol, volatile organic compounds (VOC), trace gas, and select meteorological observations across Houston, Texas. That ASR project and ARM field campaign, TRACER-MAP, was designed to complement measurements made at the first ARM Mobile Facility (AMF1) by the Aerosol Observing System (AOS) during the TRACER campaign. In this manner, TRACER-MAP effectively extended aerosol measurements from the TRACER AMF deployment, increasing the spatial coverage across the Houston metropolitan area, characterizing a greater diversity of source mixtures (e.g., industrial, traffic, residential, and biogenic) and capturing air masses with differential aging of urban source emissions (e.g., downtown versus downwind). That rich data set now offers many possibilities for in-depth analysis that align with the ASR mission to “research aerosol processes that affect Earth’s radiative balance and hydrological cycle.”

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

CACTI ARM Mobile Facility (AMF) Measurements of Ice Nucleating Particles

The dataset comprises measures, using Colorado State University's Ice Spectrometer (IS, an immersion freezing device with a range from 0°C down to -26 to -29°C) of atmosperic ice nucleating particle (INP) concentrations taken on ARM's Mobile Facility (AMF-1) Aerosol Observing System, near Villa Yacanto in central Argentina, during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Experiment. A filter sampler was mounted on the AOS trailer (2 m below the AOS inlet). Single-use filter units open to the atmosphere fitted with pre-cleaned and pre-sterilized, 47-mm dia. Nuclepore polycarbonate filters were used. Filters were typically drawn for an 8-hour period, totaling 6000 liters sampled on average. After collection, filters were stored at -20°C until processed. Initial processing to obtain spectra of INP number concentration active via the immersion freezing mechanism versus temperature was conducted using CSU's IS instrument (McCluskey et al., 2018). For measurment of INPs, collected aerosol particles were re-suspended in 7-8 mL of 0.1 µm-filtered deionized (DI) water. Aliquots of each suspension, and serial dilutions, were dispensed into trays which were fit into aluminum blocks in the IS. Samples are cooled at 0.33°C min-1 and the freezing temperatures of wells recorded automatically. Cumulative INP concentrations were determined by first calculating the INPs per mL of suspension based on Vali (1971) and then converting to concentration per standard liter of air using the proportion of the total liquid sample dispensed and the air sample volumes. An aliquot of suspension fro selected samples were also heat treated (95°C for 20 min) to denature and deactivate biological INPs, and another aliquot digested in 10% H2O2 at 95°C under UV-B to remove all organic carbon INPs. McCluskey, C. S., J. Ovadnevaite, M. Rinaldi, J. Atkinson, F. Belosi, D. Ceburnis, S. Marullo, T. C. J. Hill, U. Lohmann, Z. A. Kanji, C. O’Dowd, S. M. Kreidenweis, P. J. DeMott, 2018: Marine and Terrestrial Organic Ice Nucleating Particles in Pristine Marine to Continentally-Influenced Northeast Atlantic Air Masses, Journal of Geophysical Research: Atmospheres, 123, 6196–6212, https://doi.org/10.1029/2017JD028033. Vali, G., 1971: Quantitative evaluation of experimental results on the heterogeneous freezing nucleation of supercooled liquids. J. Atmos. Sci., 28, 402–409.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Optical Particle Measurements during EPCAPE Field Campaign Report

This campaign requested the deployment of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility optical particle counter (OPC) at the first ARM Mobile Facility (AMF1) located at the Scripps Pier in La Jolla, California during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE). The addition of the OPC was requested for two reasons. (1) Close the gap between the scanning mobility particle sizer (SMPS) and aerodynamic particle sizer (APS) size distribution from the Aerosol Observing System (AOS) measurements. (2) Principal investigator Petters has been working with Tracking Aerosol Convection Interaction Experiment (TRACER) data to compute particle fluxes from Doppler lidar (Petters et al. 2024). Briefly, backscatter flux is obtained using the eddy covariance technique using the Doppler vertical velocity and attenuated backscatter. Building upon prior studies, we were able to relate backscatter to particle number concentration by calibrating the lidar retrievals against optical particle counter-measured ground-based aerosol size distribution and radiosonde-interpolated relative humidity at lidar sample height. Performing similar analysis was of interest to EPCAPE to better understand the emissions and vertical transport of large particles into the overlying stratus clouds. However, as stated above, this analysis requires an optical size distribution that covers the 0.3-30-μm-diameter size range. The OPC was deployed between 2023-04-14 and 2024-02-14. The deployment, data quality analysis, and data archiving was handled by the DOE ARM instrument mentor team without additional involvement by the principal investigator. Data quality was marked as “routine” for the majority of the campaign.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Investigating Spatial Variability of Aerosol, Cloud Condensation Nuclei, and Ice Nucleating Particles in Mountainous Terrain Field Campaign Report

The U.S. Department of Energy Atmospheric System Research (ASR)-supported Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River Watershed (ERW) of the Upper Colorado River Basin in southwestern Colorado ran from fall 2021 to spring 2023. Two monitoring sites were deployed in the ERW as part of SAIL. The two sites were the Aerosol Observation System (AOS) located on Crested Butte Ski Mountain, and the second ARM Mobile Facility (AMF2), located at the Rocky Mountain Biological Laboratory in Gothic, Colorado. To gain a more comprehensive understanding of aerosols in complex, mountainous terrain, Handix Scientific deployed SAIL-Net, a distributed network of six measurement nodes spanning the domain of the SAIL research area from October 2021 to July 2023. Each node measured aerosol particles between 140 nm and 3.4 μm in diameter using a small portable optical particle spectrometer (POPS; Gao et al. 2016), cloud condensation nuclei (CNN) using a miniature CCN counter (CloudPuck), and ice nucleating particles (INP) using the time-resolved aerosol filter sampler (TRAPS; Creamean et al. 2018). Our approach was similar to other studies that aimed to better characterize and understand aerosols and gas-phase pollutants using networks of lower-cost sensors (Caubel et al. 2019, Kelly et al. 2021, Asher et al. 2022). Such studies have identified neighborhood-level variations in pollutant concentrations (Schneider et al. 2017, Popoola et al. 2018, Caubel et al. 2019). Small-scale variations such as this are poorly represented in models and poorly measured by a single monitoring system (Caubel et al. 2019). Previous work has shown the representation error (the ability of measurements to represent a larger area) increases with complex orography, leading to decreases in model accuracy (Schutgens et al. 2017). The overall goal of SAIL-Net was to improve our understanding of the variability of aerosol in the ERW, thus increasing our knowledge of aerosol-cloud interactions in this region and informing the usefulness of distributed networks of measurements for future studies. We met this goal by answering the following science questions: 1. What is the aerosol temporal variability, and how does aerosol inhomogeneity vary seasonally? Is there significant seasonal variability in sources, or are short-term meteorological conditions the most important determining factor in sources for cloud nuclei? 2. What is the aerosol spatial variability? What are the aerosol characteristics at cloud base, presumably the particles most representative of those acting as cloud nuclei? 3. How should measurement networks be designed to capture aerosol-cloud interactions, and what do they need to measure? Can a single measurement site accurately represent aerosol properties in regions of complex terrain? SAIL-Net consisted of six measurement nodes spread across the ERW near Crested Butte, Colorado. The primary objective in site placement was to select locations that captured the vertical variation in aerosol properties while also spanning the domain of the SAIL campaign. The elevation of the sites ranged from roughly 2750 m along the valley floor of the ERW to approximately 3500 m near the top of Crested Butte Mountain, which is one of the taller peaks in the ERW. The farthest distance between sites was 14 km, while the closest two sites were approximately 1 km apart. Two of the sites were collocated with the ARM SAIL sites; our instruments sat on top of one of the trailers at AOS and another one of our sites was located in a meadow just above AMF2.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

ARM FY2024 Aerosol Operations Plan

The Atmospheric Radiation Measurement user facility (ARM) deploys a suite of aerosol and trace gas (further mentions of aerosols will assume inclusion of trace gases) instrumentation at each of ARM's observatories. ARM currently deploys five Aerosol Observing Systems, one each at: Southern Great Plains (SGP); Eastern North Atlantic (ENA); ARM Mobile Fabilities (AMFI 1, 2, and 3). Aerosol measurements at ARM’s North Slope of Alaska (NSA) observatory have historically been made by the National Oceanic and Atmospheric Administration (NOAA) and provided to ARM through a collaboration. As ARM’s support for aerosol instrumentation increases, it is important for ARM to communicate plans and priorities for aerosol measurements to the community to maximize the benefit and planning around scientific activities and to advance confidence in ARM’s aerosol measurements. ARM will develop a yearly aerosol operations plan for the upcoming fiscal year (October 1-September 30) starting with FY24. This plan will be open and available through the ARM aerosol instrument webpages and will include: Review of the previous activities since the last plan (in this case, 2018); Planned activities and their priorities for the upcoming FY; Calibration timing and efforts; Planned activities for data products and value-added products (VAP).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Investigating spatial variability of aerosol, cloud condensation nuclei, and ice nucleating particles in mountainous terrain

The ASR-supported Surface Atmosphere Integrated field Laboratory (SAIL) in the East River Watershed (ERW) of the Upper Colorado River Basin in southwestern Colorado ran from fall 2021 to spring 2023. Two monitoring sites were deployed in the East River Watershed as part of SAIL. The two sites were the Aerosol Observation System (AOS) located on Crested Butte Ski Mountain, and the ARM Mobile Facility (AMF-2), located at the Rocky Mountain Biological Laboratory in Gothic, Colorado. To gain a more comprehensive understanding of aerosols in complex, mountainous terrain, Handix Scientific deployed SAIL-Net, a distributed network of six measurement nodes spanning the domain of the SAIL research area from October 2021 to July 2023. Each node measured aerosol particles between 140 nm and 3.4 μm in diameter using a small particle counter (POPS, (Gao et al., 2016)), CNN using a miniature CCN counter (CloudPuck), and INP using the Time-Resolved Aerosol Filter Sampler (TRAPS, Creamean et al. (2018)). Our approach was similar to other studies that aimed to better characterize and understand aerosols and gas-phase pollutants using networks of lower-cost sensors (Caubel et al., 2019; Kelly et al., 2021; Asher et al., 2022). Such studies have identified neighborhood-level variations in pollutant concentrations (Schneider et al., 2017; Popoola et al., 2018; Caubel et al., 2019). Small-scale variations such as this are poorly represented in models and poorly measured by a single monitoring system (Caubel et al., 2019). Previous work has shown the representation error (the ability of measurements to represent a larger area) increases with complex orography, leading to decreases in model accuracy (Schutgens et al., 2017). The overall goal of SAIL-Net was to improve our understanding of the variability of aerosol in ERW, thus increasing our knowledge of aerosol-cloud interactions in this region and informing the usefulness of distributed networks of measurements for future studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

MOSAiC-Colorado State University Ice Spectrometer

This data set contains atmospheric ice nucleating particle (INP) measurements, using Colorado State University’s (CSU) Ice Spectrometer (IS), of filter collections taken at the U.S. DOE ARM AMF2 site onboard the R/V Polarstern P-deck during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign. Samples were collected from October 27, 2019 to September 24, 2020. A filter sampler was mounted approximately 15 m above ground level on a railing in proximity to (and approximately 3 m below) the Aerosol Observation System (AOS) inlet. Single-use filter units open to the atmosphere were pre-cleaned and pre-loaded with 47-mm diameter Nuclepore polycarbonate (0.2 µm pore-diameter) filters. Filters were typically drawn for a three-day period, with an average volume of air filtered of 87,000 standard liters. Total volumes were calculated through recorded daily flow rates using a mass flow meter (TSI). After collection, filters were stored and transported frozen until analysis using CSU’s IS instrument (McCluskey et al., 2018). Aerosol particles were first re-suspended in 8 mL of 0.1 µm-filtered deionized (DI) water. Aliquots of each suspension, and corresponding 11-fold dilutions, were dispensed into polymerase chain reaction (PCR) trays and placed into the aluminum blocks of the IS. Samples were cooled at approximately 0.33 °C min -1 and freezing detected optically with corresponding temperatures recorded. Cumulative INP concentrations were determined through calculating the number of INPs per mL of suspension (Vali, 1971) and converting to concentration per standard L of air by accounting for the proportion of liquid used and volume of air collected. All samples were corrected for the number of INPs on the average of four field blanks (cleaned, handled, transported, and analyzed in the same way without air flow). Two-tailed, 95% confidence intervals for binomial sampling are provided (Agresti and Coull, 1998). Select samples were also heat treated (95 °C for 20 min) to denature and deactivate biological INPs present and digested in 10% H 2 O 2 at 95 °C under UV-B for 20 min to remove any organic carbon INPs. Agresti, A, and BA Coull. 1998. "Approximate is better than “exact” for interval estimation of binomial proportions." American Statistics 52: 119–126. https://doi.org/10.2307/2685469 McCluskey, CS, J Ovadnevaite, M Rinaldi, J Atkinson, F Belosi, D Ceburnis, … and PJ DeMott. 2018. "Marine and Terrestrial Organic Ice-Nucleating Particles in Pristine Marine to Continentally Influenced Northeast Atlantic Air Masses." Journal of Geophysical Research: Atmospheres 123 (11): 6196–6212, https://doi.org/10.1029/2017JD028033 Vali, G. 1971. "Quantitative Evaluation of Experimental Results and the Heterogeneous Freezing Nucleation of Supercooled Liquids." Journal of the Atmospheric Sciences 28: 402-209. https://doi.org/10.1175/1520-0469(1971)028<0402:QEOERA>2.0.CO;2

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Diurnal Trends and Meteorological Factors Influencing the Variability of Fluorescent Bioaerosol in Mt. Crested Butte, Colorado During SAIL

Abstract Despite the crucial role of bioaerosol particles (BAP) in our climate system, local ecosystems, and human health, our grasp on their atmospheric interactions is hampered by a lack of high‐resolution and long‐term data, which is essential for understanding their abundance and variability in response to meteorological conditions. To discern these relationships in a high‐altitude mountainous terrain is even less well‐studied. Therefore, we deployed a Wideband Integrated Bioaerosol Sensor (WIBS‐Neo) for three months during the first biologically active season of the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in summer 2022 on Mt. Crested Butte in Colorado (elevation 3,140 m ASL). Here, we report real‐time fluorescent BAP (FBAP) data collected from 15 June to 13 September 2022, sampled from within the ARM Aerosol Observing System (AOS). To our knowledge, these are the first high altitude (>3,000 m ASL) continuous measurements of FBAP made in North America. During this deployment, we observed on average 21% and as many as 48% (hourly maximum) of particles within the detection size range ( to ) of the WIBS as FBAP. Our analysis presents the diurnal cycles for seven distinct types of FBAP, showing unique patterns and, in some cases, correlations with temperature and solar radiation cycles. Abundance and composition of FBAP varied with relative humidity and precipitation. Precipitation events appeared to both cause emission and removal of FBAP, whereas dust and smoke events had no significant effect, highlighting the critical role of meteorology on FBAP at high altitudes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Bioaerosol Properties using WIBS from SAIL on Mt. Crested Butte, CO

We deployed a Wideband Integrated Bioaerosol Sensor (WIBS-Neo, DMT) to measure different properties of fluorescent bioaerosol particles (FBAP) during SAIL. Our measurements were collected at the supplementary site on Crested Butte Mountain from inside the ARM Aerosol Observing System (AOS) sampling from the AOS inlet. We had two deployment periods at SAIL during biologically active seasons: summer 2022 (15 June 2022 - 13 September 2022) and spring 2023 (21 March 2023 - 19 June 2023). The WIBS is an online single-particle measurement that detects FBAPs (within a size range of 0.5 - 30 microns in diameter) based on the excitation and emission wavelengths of the individual particles. Using two xenon lamps, the WIBS excites FBAPs at 280 nm and 370 nm. Their emission is detected across two wavebands of 310-400 nm and 420-650 nm. We classified the FBAPs into seven different categories (A, B, C, AB, BC, AC, and ABC) using the classification scheme in Perring et. al. (2015) [1]. Here, we report one-minute averaged number concentration of FBAPs (total and by category) and NFBAPs. We also present one-minute-averaged size distributions and the asymmetry factor (AF, a surrogate for shape) of all FBAPs and NFBAPs. The logarithmic bin width of the size bins is the same as the average bin width of the AOS's optical particle counter (OPC, Grimm) for the range of sizes in which they overlap (26 bins from 0.5 - 30 microns). AF of the particles ranges from 0-100 and is divided into five bins with a linear spacing at increments of 20. The smallest AF bin represents more spherical particles while the largest bin represents more rod-shaped particles. We recommend referring to the readme file for more details of the variables present in the files. [1] Perring, A. E., et al. (2015), Airborne observations of regional variation in fluorescent aerosol across the United States, J. Geophys. Res. Atmos., 120, 1153-1170, doi:10.1002/2014JD022495. Abstract and description of the campaign can be found here: https://www.arm.gov/research/cam

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Examining the Ice Nucleating Particles from Southern Great Plains Part II (ExINP-SGP). Field Campaign Report

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, recent INP measurements at the Southern Great Plains observatory (SGP; 36'' 36' 18→ N, 97° 29' 6'' W) during multiple campaigns, such as SINCE-2014 (DeMott et al. 2015), Examining the Ice-Nucleating Particles from SGP (ExINP-2019; Hiranuma and Vepuri 2020), and Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY; Knopf et al. 2021a), strongly suggested the contribution of supermicron aerosol particles to observed INP abundance at SGP. However, verification of this hypothesis was hampered since additional offline laboratory analyses require sufficient amounts of collected airborne PM, which was lacking. Therefore, the principal investigators (PIs) conducted a field campaign, named ExINP-SGP II, to collect airborne PM at SGP for complementary laboratory characterization of the particles’ physicochemical properties (including ice nucleation properties). We used a passive particle sampler, which is a 4’ x 4’ x 2” (L x W x D) aluminum pan inside the 12”-high wooden windshield wall at the rooftop deck of the ARM Aerosol Observing System (AOS) trailer to collect dry PM deposits from January to April 2021. Figure 1 shows images of our experimental setup at the site. Additionally, we also collected surface soil near the ARM AOS trailer on 20 November 2020 (Figure 1b) to examine the ground soil dust particles (< 63 µm sieved) for their propensities to initiate immersion freezing compared to collected ambient PM. Surface soil and airborne samples were stored in the chemically inert container separately and kept in a dry, cool place until analyzed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Polar Cloud Microphysics and Surface Energy Budget from AWARE (Final Technical Report)

This was a collaborative project between the Scripps Institution of Oceanography at the University of California San Diego (SIO), Byrd Polar and Climate Research Center at The Ohio State University (BPCRC), The Department of Meteorology and Atmospheric Science at The Pennsylvania State University (Penn State), and Brookhaven National Laboratory (BNL). The project’s over-arching objectives involved maximizing the scientific potential of the ARM West Antarctic Radiation Experiment (AWARE) data set, in two respects: (1) application of polar-optimized climate models to test the most current and comprehensive cloud microphysical parameterizations; and (2) analysis of the most advanced ARM Mobile Facility sensors (e.g., cloud radar, spectroradiometer, and aerosol observing system data) to advance understanding of Antarctic cloud microphysical and radiative properties, particularly on a climatological basis with emphasis on contrasts with the high Arctic. The team’s efforts have resulted in 16 peer-review publications, in addition to an overview of the AWARE campaign in the Bulletin of the American Meteorological Society. Our emphasis throughout this program was to go beyond the traditional “case study” approach to model evaluation, in which a “classical” or otherwise well-characterized surface-atmosphere-cloud system of short duration is simulated by several climate models. Instead, we attempted analysis of longer time series in the AWARE data, both climatologically and with models. We have numerous successful results from both AWARE locations: The main AMF-2 deployment at McMurdo Station on Ross Island (13 months duration), and the extended facility at the West Antarctic Ice Sheet (WAIS) Divide Ice Camp (40 days during austral summer 2015-16).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

ARM FY2025 Aerosol Operations Plan

The U.S. Department of Energy’s Atmospheric Radiation Measurement user facility (ARM) deploys at each of ARM’s observatories a suite of aerosol and trace gas (further mention of aerosols will assume inclusion of trace gases) instrumentation that constitute the Aerosol Observing Systems (AOS; Uin et al. 2019).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

ARM FY2026 Aerosol Operations Plan

The U.S. Department of Energy’s Atmospheric Radiation Measurement User Facility (ARM) deploys at each of ARM’s observatories a suite of aerosol and trace gas (further mention of aerosols will assume inclusion of trace gases) instrumentation that constitute the Aerosol Observing System (AOS; Uin et al. 2019).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

mergedsmpsaps

Merged aerosol particle size distributions for the Aerodynamic Particle Sizer (APS) and Scanning Mobility Particle Sizer (SMPS) instruments

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

mergedsmpsapsml

Merged aerosol particle size distributions for the Aerodynamic Particle Sizer (APS) and Scanning Mobility Particle Sizer (SMPS) instruments with Machine Learning Quality Checks Applied

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations

Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.

54 ENVIRONMENTAL SCIENCES↗