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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals

By accounting for surface-based light source emissions and top-of-atmosphere (TOA) downward lunar fluxes, we adapted the spherical harmonics discrete ordinate method (SHDOM) 3-dimensional (3-D) radiative transfer model (RTM) to simulate nighttime 3-D TOA radiances as observed from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi-NPP satellite platform. Used previously for daytime 3-D applications, these new SHDOM enhancements allow for the study of the impacts of various observing conditions and aerosol properties on simulated VIIRS-DNB TOA radiances. Observations over Dakar, Senegal, selected for its bright city lights and a large range of aerosol optical depth (AOD), were investigated for potential applications and opportunities for using observed radiances containing VIIRS-DNB “bright pixels” from artificial light sources to conduct aerosol retrievals. We found that using the standard deviation (SD) of such bright pixels provided a more stable quantity for nighttime AOD retrievals than direct retrievals from TOA radiances. Further, both the mean TOA radiance and SD of TOA radiances over artificial sources are significantly impacted by satellite viewing angles. Light domes, the enhanced radiances adjacent to artificial light sources, are strong functions of aerosol properties and especially aerosol vertical distribution, which may be further utilized for retrieving aerosol layer height in future studies. Through inter-comparison with both day- and nighttime Aerosol Robotic Network (AERONET) data, the feasibility of retrieving nighttime AODs using 3-D RTM SHDOM over artificial light sources was demonstrated. Our study shows strong potential for using artificial light sources for nighttime AOD retrievals, while also highlighting larger uncertainties in quantifying surface light source emissions. This study underscores the need for surface light emission source characterizations as a key boundary condition, which is a complex task that requires enhanced input data and further research. We demonstrate how quality-controlled nighttime light data from NASA’s Black Marble product suite could serve as a primary input into estimations of surface light source emissions for nighttime aerosol retrievals.

Jianglong Zhang↗
NASA NTRSDate not supplied

The Representation of Aerosols in GMAO’s Newest Reanalyses

Over the past few years, NASA’s Global Modelling and Assimilation Office has been working on the configuration and production of three new reanalysis products, GEOS-IT, GiOcean, and MERRA-21C. GEOS-IT, or the Goddard Earth Observing System for Instrument Teams, is a 3D variational data assimilation system that runs in a near real time framework however retrospectively provides data back through 1998 to deliver a consistent view of the Earth-atmosphere system for the production of observational NASA products. Retrospective production for GEOS-IT is complete and the meteorology has since been used to produce the one way weakly coupled GiOcean reanalysis. Due to differences in the atmospheric model, particularly related to scavenging, aerosols are not identical in GEOS-IT and GiOcean. MERRA-21C, or the Modern Era Restrospective analysis for Research and Applications in the 21st century, is a hybrid 4D ensemble variational system at a finer horizontal resolution of 0.25 degrees. Although different in their intended use, and therefore configuration, these systems prominently feature coupling between meteorology and aerosols. The differences and similarities in the aerosol configuration between the three systems will be discussed, covering biomass burning and anthropogenic emissions as well as observations used for the assimilation of aerosol optical depth. A large emphasis will be placed on the version of the underlying aerosol module, GOCART, which underwent a complete refactoring and the addition of radiatively active brown carbon between GEOS-IT and MERRA-21C. Independent observations will be used to evaluate the performance of aerosols in both reanalyses, focusing on aerosol optical depth, surface particulate matter, and vertical profiles of aerosol backscatter.

Allison Collow↗
NASA NTRSDate not supplied

Providing Satellite-Assisted Particulate Matter (SAPM) Estimates for the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group

The Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group is an international forum that promotes collaboration amongst researchers of these three atmospheric aerosol communities. MIRA currently consists of a collection of five interdisciplinary and independently funded Topic groups with focused goals and generally involve requests for additional scientific datasets. Participants of the MIRA Satellite-Assisted Particulate Matter (SAPM) Topic group study particulate matter with diameters smaller than 2.5 microns (PM2.5), because of its substantial role in air pollution and the resulting negative impacts on human health. SAPM seeks to provide intercomparisons of different methods and techniques for obtaining surface PM2.5 proxies using spaceborne passive and active remote sensors, aerosol models, and in situ observations. The ultimate motivation of SAPM is to provide greater PM2.5 coverage than in situ ground stations, which are limited in some areas of the contiguous United States and large regions throughout the globe. In this poster presentation, we provide an overview of the PM2.5 estimation techniques applied by current SAPM team members, as well as the strengths and limitations of each technique. These approaches include spaceborne lidar (Cloud-Aerosol Lidar with Orthogonal Polarization) only, combined spaceborne lidar (Cloud Aerosol Transport System) and a model (Goddard Earth Observing System), and using aerosol optical depth (AOD) from a spaceborne passive remote sensor (Moderate Resolution Imaging Spectroradiometer) to explore city trends in AOD and relate those to city trends in PM2.5. Also in this poster presentation, we highlight results of our SAPM study of India, a country characterized by high levels of PM2.5 concentrations. We show the temporal and spatial variability of PM2.5 over India derived using various approaches and validation with ground-based in situ PM2.5 observations. The SAPM Topic group actively seeks additional collaborators, including those working with in situ aerosol measurements, and is interested in aerosol datasets to improve and/or validate the PM2.5 estimates.

Travis D Toth↗
DOE OSTI2022

Ambient Aerosol Is Physically Larger on Cloudy Days in Bondville, Illinois

Particle chemical composition affects aerosol optical and physical properties in ways important for the fate, transport, and impact of atmospheric particulate matter. For example, hygroscopic constituents take up water to increase the physical size of a particle, which can alter the extinction properties and atmospheric lifetime. At the collocated AERosol RObotic NETwork (AERONET) and Interagency Monitoring of PROtected Visual Environments (IMPROVE) network monitoring stations in rural Bondville, Illinois, we employ a novel cloudiness determination method to compare measured aerosol physicochemical properties on predominantly cloudy and clear sky days from 2010 to 2019. On cloudy days, aerosol optical depth (AOD) is significantly higher than on clear sky days in all seasons. Measured angstrom ngstro''m exponents are significantly smaller on cloudy days, indicating physically larger average particle size for the sampled populations in all seasons except winter. Mass concentrations of fine particulate matter that include estimates of aerosol liquid water (ALW) are higher on cloudy days in all seasons but winter. More ALW on cloudy days is consistent with larger particle sizes inferred from angstrom ngstro''m exponent measurements. Aerosol chemical composition that affects hygroscopicity plays a determining impact on cloudy versus clear sky differences in AOD, angstrom ngstro''m exponents, and ALW. This work highlights the need for simultaneous collocated, high-time-resolution measurements of both aerosol chemical and physical properties, in particular at cloudy times when quantitative understanding of tropospheric composition is most uncertain.

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 OSTI2020

Predicting secondary organic aerosol phase state and viscosity and its effect on multiphase chemistry in a regional-scale air quality model

Atmospheric aerosols are a significant public health hazard and have substantial impacts on the climate. Secondary organic aerosols (SOAs) have been shown to phase separate into a highly viscous organic outer layer surrounding an aqueous core. This phase separation can decrease the partitioning of semi-volatile and low-volatile species to the organic phase and alter the extent of acid-catalyzed reactions in the aqueous core. A new algorithm that can determine SOA phase separation based on their glass transition temperature (T g ), oxygen to carbon (O:C) ratio and organic mass to sulfate ratio, and meteorological conditions was implemented into the Community Multiscale Air Quality Modeling (CMAQ) system version 5.2.1 and was used to simulate the conditions in the continental United States for the summer of 2013. SOA formed at the ground/surface level was predicted to be phase separated with core–shell morphology, i.e., aqueous inorganic core surrounded by organic coating 65.4 % of the time during the 2013 Southern Oxidant and Aerosol Study (SOAS) on average in the isoprene-rich southeastern United States. Our estimate is in proximity to the previously reported ~70 % in literature. The phase states of organic coatings switched between semi-solid and liquid states, depending on the environmental conditions. The semi-solid shell occurring with lower aerosol liquid water content (western United States and at higher altitudes) has a viscosity that was predicted to be 10 2 –10 12 Pa s, which resulted in organic mass being decreased due to diffusion limitation. Organic aerosol was primarily liquid where aerosol liquid water was dominant (eastern United States and at the surface), with a viscosity <10 2 Pa s. Phase separation while in a liquid phase state, i.e., liquid–liquid phase separation (LLPS), also reduces reactive uptake rates relative to homogeneous internally mixed liquid morphology but was lower than aerosols with a thick viscous organic shell. The sensitivity cases performed with different phase-separation parameterization and dissolution rate of isoprene epoxydiol (IEPOX) into the particle phase in CMAQ can have varying impact on fine particulate matter (PM 2.5 ) organic mass, in terms of bias and error compared to field data collected during the 2013 SOAS. This highlights the need to better constrain the parameters that govern phase state and morphology of SOA, as well as expand mechanistic representation of multiphase chemistry for non-IEPOX SOA formation in models aided by novel experimental insights.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2014

Model-Based Estimation of Sampling-Caused Uncertainty in Aerosol Remote Sensing for Climate Research Applications

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiationtransport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125 deg × 1.125 deg and 2 deg × 3◦: the analysis is restricted to 60 deg S-60 deg N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.

long-term variability↗
NASA NTRS2020

Aerosol-Ice Formation Closure Pilot Study (AEROICSTUDY) Field Campaign Report

The aerosol-ice formation closure pilot study (AEROICESTUDY) was a field campaign conducted at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility at the Southern Great Plains (SGP) observatory from October 7 to 28, 2019. The purpose of this campaign was to test a field observational approach for conducting an aerosol-ice formation closure study. In other words, the goal was to predict the number of ice nucleating particles (INPs) from the measurements of physical and chemical aerosol properties and compare those to measured INP number concentrations. This project was motivated by the fact that the aerosol community has widely conducted aerosol radiative closure, aerosol-cloud condensation nuclei (CCN), and CCN-droplet closure studies to test the physical models and parameterizations that cloud-resolving and climate models rely on to perform reliable simulations of the Earth system and energy budget. However, very few closure studies related to INPs have been conducted, and to our knowledge, none using robust, size-resolved, ambient aerosol composition measurements as model inputs.

aerosol-ice formation↗
NASA NTRS2019

Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC(4)RS

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satellite‐borne Moderate‐resolution Imaging Spectroradiometer (MODIS), the Dark Target retrieval algorithm provides global aerosol optical depth (AOD; at 0.55 μm) in cloud‐free scenes. Since MODIS' resolution (500‐m pixels, 3‐ or 10‐km product) is too coarse for studying near‐cloud aerosol, we ported the Dark Target algorithm to the high‐resolution (~50‐m pixels) enhanced‐MODIS Airborne Simulator (eMAS), which flew on the high‐altitude ER‐2 during the Studies of Emissions, Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys Airborne Science Campaign over the United States in 2013. We find that even with aggressive cloud screening, the ~0.5‐km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degraded‐resolution AOD), coregistered Cloud Physics Lidar profiles, MODIS aerosol retrievals, and ground‐based Aerosol Robotic Network observations. We also define spatial metrics to indicate local cloud distributions near each retrieval and then separate into near‐cloud and far‐from‐cloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clear‐cloud transition zone microphysics such as aerosol swelling. However, 3‐D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds.

aerosol retrieval algorithm↗
NASA NTRS2024

Retrievals of Aerosol Optical Depth Over the Western North Atlantic Ocean During ACTIVATE

Aerosol optical depth was retrieved from two airborne remote sensing instruments, the Research Scanning Polarimeter (RSP) and Second Generation High Spectral Resolution Lidar (HSRL-2), during the National Aeronautics and Space Administration (NASA) Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The field campaign offers a unique opportunity to evaluate an extensive 3-year dataset under a wide range of meteorological conditions from two instruments on the same platform. However, a long-standing issue in atmospheric field studies is that there is a lack of reference datasets for properly validating field measurements and estimating their uncertainties. Here we address this issue by using the triple collocation method, in which a third collocated satellite dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) is introduced for comparison. HSRL-2 is found to provide a more accurate retrieval than RSP over the study region. The error standard deviation of HSRL-2 with respect to the ground truth is 0.027. Moreover, this approach enables us to develop a simple, yet efficient, quality control criterion for RSP data. The physical reasons for the differences in two retrievals are determined to be cloud contamination, aerosols near the surface, multiple aerosol layers, absorbing aerosols, non-spherical aerosols, and simplified retrieval assumptions. These results demonstrate the pathway for optimal aerosol retrievals by combining information from both lidars and polarimeters for future airborne and satellite missions.

Aerosol optical depth↗
DOE OSTI2023

TRACER-CAT-UCDAVIS Aerosol Optical Properties and Sizing - crdps

Aerosol size distribution and optical properties collected in La Port TX, during TRACER-CAT-UCDavis, July 2022. Speciated particle composition measurements are reported separately. All sampling was conducted with an identical aerosol inlet as the standard ARM-AOS systems. The TRacking Aerosol Convection interactions ExpeRiment Carbonaceous Aerosols Thrust by UC Davis (TRACER-CAT-UCDavis, July 2022) was designed to complement the larger ARM TRACER science goals to understand convective cloud lifecycles and aerosol-convection interactions. TRACER-CAT-UCDavis is focused on understanding the relationship between particle composition and light absorption and the influence of water uptake on this relationship. This aerosol data can be used to understand the relationship between particle composition and light absorption and the influence of water uptake on this relationship. Instruments include: UC Davis two-wavelength cavity ringdown-photoacoustic spectrometer (CRD-PAS); Brechtel scanning electrical mobility sizer (SEMS); modified humidified cavity attenuated phase shift spectrometer with single scatter albedo (H-CAPS-SSA)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Contemporary sources dominate carbonaceous aerosol on the North Slope of Alaska

As the Arctic continues to change and warm rapidly, it is increasingly important to understand the organic carbon (OC) contribution to Arctic aerosol. Biogenic sources of primary and secondary OC in the Arctic will be impacted by climate change, including warming temperatures and earlier snow and ice melt. Here, this study focuses on identifying potential sources and regional influences on the seasonal concentration of organic aerosol through analysis of chemical and isotopic composition. Aerosol samples were collected at two sites on the North Slope of Alaska ($Utqia\dot{g}vik$, UQK, and Oliktok Point, OLK, which is in an Arctic oilfield) over three summers from 2015 to 2017. The elemental carbon (EC) trends at each site were used to understand local combustion influences. Local sources drove EC concentrations at Oliktok Point, where high EC was attributed to oil and gas extraction activity, including diesel combustion emissions. $Utqia\dot{g}vik$ had very low EC in the summer. OC was more similar in concentration and well correlated between the two sites with high contributions of contemporary carbon by radiocarbon apportionment (UQK = 74%, OLK = 63%), which could include both marine and terrestrial sources of contemporary carbon (e.g. primary and secondary biogenic, biomass burning and/or associated SOA, and bioaerosols). OC concentrations are strongly correlated to maximum ambient temperatures on the NSA during the summer, which may have implications for predicting future OC aerosol concentrations in a warming Arctic. Biomass burning was determined to be an episodic influence at both sites, based on interpretation of combined aerosol composition, air mass trajectories, and remote sensing of smoke plumes. The results from this study overall strongly suggests contribution from regional sources of contemporary organic aerosol on the NSA, but additional analysis is needed to better constrain contributions from both biogenic sources (terrestrial and/or marine) and bioaerosol to better understand temperature-related aerosol processes in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Novel Application of Machine Learning Techniques for Rapid Source Apportionment of Aerosol Mass Spectrometer Datasets

In this work, we apply machine learning approaches sparse multinomial logistic regression to classify aerosol mass spectrometer (AMS) unit mass resolution (UMR) data followed by an ensemble regression technique for source apportionment of organic aerosols (OA). The classifier was trained on 60 well characterized laboratory and positive matrix factorization (PMF) deconvolved reference spectra to identify eight OA types. These include four laboratory-derived secondary organic aerosol (SOA) spectra, which include isoprene photooxidation SOA, isoprene epoxydiols (IEPOX) SOA, a monoterpene SOA type that includes a-pinene and ß-pinene SOA, and aromatic SOA from oxidation of naphthalene and m-xylene precursors, as well as PMF deconvolved spectra for three primary organic aerosol (POA) types, namely, hydrocarbon-like organic aerosol (HOA), biomass burning organic aerosol (BBOA), and cooking OA (COA), and a more oxidized oxygenated OA type (MO-OOA). A 5-fold cross-validation strategy, repeated 10 times, was used to assess the classifier’s performance. The classifier had high classification accuracy for COA, aromatic SOA, and isoprene SOA spectra but incorrectly classified ~9% by number of MO-OOA spectra as BBOA, 12% of BBOA spectra as HOA (and vice versa), and 18% of IEPOX-SOA spectra as aromatic SOA. Next, an ensemble regression model was trained on an artificially generated dataset consisting of mixtures of different OA types to assess its ability to predict fractional mass abundances from classification probabilities of various OA species obtained from the multinomial logistic regression classifier trained on the reference spectra. Ultimately, the proposed approach was applied for source apportionment of aircraft-based AMS measurements of OA UMR spectra during the HI-SCALE field campaign. On two representative days (May 6th and 18th, 2016), the algorithm determined that ~50-60% of OA by mass was MO-OOA, which represented a highly aged organic aerosol mixture from different sources. On both days, BBOA was determined to contribute less than 10% to OA by mass. However, on May 18th, the aromatic SOA fraction was higher compared to that on May 6th. The proposed approach is capable of rapidly analyzing AMS data in real time, making it suitable for applications where rapid source apportionment of AMS OA spectra is desirable.

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

Regional-Scale Modeling Parameterizations for Secondary Organic Aerosol Formation from Isoprene Epoxydiols: Experimentally Based Evaluation and Optimization

Isoprene is an abundant volatile organic compound emitted from broadleaf forests. Under low nitric oxide concentrations, isoprene is photochemically oxidized to form gas-phase isoprene epoxydiols (IEPOX). In the presence of acidified sulfate aerosols, IEPOX enhances the secondary organic aerosol (SOA) formation. Predictions of IEPOX-SOA in regional-scale models, e.g., the Community Multiscale Air Quality Model (CMAQ), are uncertain due to homogeneous aerosol assumptions, underpredictions of water uptake (hygroscopicity), and aerosol surface area. Here, we used experimental measurements of IEPOX-SOA tracers, 2-methyltetrols (2-MT) and 2-methyltetrol sulfates (2-MTS), formed at initial IEPOX-to-inorganic sulfate ratios ranging from 1–10.5, at ∼50% relative humidity to constrain key IEPOX-SOA parameters: phase separation, organic shell diffusivity (D org ), acidity, hygroscopic growth, mass accommodation, and kinetics. The base CMAQ parametrization overpredicted experimental IEPOX-SOA with an average normalized mean bias (NMB average ) of 1.63. CMAQ with phase separation underpredicted IEPOX-SOA (NMB average = −0.71). Using the phase-separated model, CMAQ model performance was optimized (NMB average = 0.077) with an increased D org = 2 × 10 –16 m 2 s –1 and increased rate constants (k 2-MT = 1 × 10 –3 M 2 s –1 , k 2-MTS = 8.83 × 10 –3 M 2 s –1 ). The optimized model explicitly accounted for hygroscopic growth by utilizing experimentally derived growth rates, improving aerosol surface area predictions. Our model highlights the importance of the aerosol mixing state (homogeneous versus phase-separated), aerosol size dynamics, and hygroscopic growth in modeling heterogeneous reactive uptake of IEPOX.

aerosols↗
DOE OSTI2023

Uncertainty in Simulating Twentieth Century West African Precipitation Trends: The Role of Anthropogenic Aerosol Emissions

Anthropogenic aerosol emissions from North America and Europe have strong effects on the decadal variability of the West African monsoon (WAM). Anthropogenic aerosol effective radiative forcing is model dependent, but the impact of such uncertainty on the simulation of long-term WAM variability is unknown. We use an ensemble of simulations with HadGEM3-GC3.1 that span the most recent estimates in simulated anthropogenic aerosol effective radiative forcing. We show that uncertainty in anthropogenic aerosol radiative forcing leads to significant uncertainty at simulating multi-decadal trends in West African precipitation. At the large scale, larger forcing leads to a larger decrease in the interhemispheric temperature gradients, in temperature over both the North Atlantic Ocean and northern Sahara. There are also differences in dynamic changes specific to the WAM (locations of the Saharan heat low and African Easterly Jet, of the strength of the West African westerly jet, and of African Easterly Wave activity). We also assess effects on monsoon precipitation characteristics and temperature. We show that larger aerosol forcing results in a decrease of the number of rainy days and of heavy and extreme precipitation events and warm spells. However, simulated changes in onset and demise dates do not appear to be sensitive to the magnitude of aerosol forcing. Our results demonstrate the importance of reducing the uncertainty in anthropogenic aerosol forcing for understanding and predicting multi-decadal variability in the WAM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Abundant Nitrate and Nitric Acid Aerosol in the Upper Troposphere and Lower Stratosphere

The tropospheric and stratospheric nitrate aerosol is simulated by a sectional aerosol model coupled to the Community Earth System Model. The simulated nitrate mass fractional contribution to aerosols is significantly higher in the upper troposphere and lower stratosphere (UTLS) than that at the surface. Both in situ measurements and simulations show that nitrate aerosol accounts for about 30%–40% of the aerosol mass at the tropopause of the Asian summer monsoon (ASM) region. Furthermore, simulated condensed nitric acid particles account for ~20% of the annual mean aerosol mass at the tropical tropopause, and over 95% in the UTLS at the South Pole in June-July-August. Here, our study suggests that the extremely cold ambient conditions in the UTLS of the tropics, ASM and polar regions thermodynamically favor the condensation of ammonia and nitric acid. The widely distributed nitrate aerosol in the global UTLS may be overlooked by climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Process Modeling of Aerosol‐Cloud Interaction in Summertime Precipitating Shallow Cumulus Over the Western North Atlantic

Abstract Process modeling of Aerosol‐cloud interaction (ACI) is essential to bridging gaps between observational analysis and climate modeling of aerosol effects in the Earth system and eventually reducing climate projection uncertainties. In this study, we examine ACI in summertime precipitating shallow cumuli observed during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). Aerosols and precipitating shallow cumuli were extensively observed with in‐situ and remote‐sensing instruments during two research flight cases on 02 June and 07 June, respectively, during the ACTIVATE summer 2021 deployment phase. We perform observational analysis and large‐eddy simulation (LES) of aerosol effect on precipitating cumulus in these two cases. Given the measured aerosol size distributions and meteorological conditions, LES is able to reproduce the observed cloud properties by aircraft such as liquid water content (LWC), cloud droplet number concentration ( N c ) and effective radius r eff . However, it produces smaller liquid water path (LWP) and larger N c compared to the satellite retrievals. Both 02 and 07 June cases are over warm waters of the Gulf Stream and have a cloud top height over 3 km, but the 07 June case is more polluted and has larger LWC. We find that the N a ‐induced LWP adjustment is dominated by precipitation feedback for the 2 June precipitating case and there is no clear entrainment feedback in both cases. An increase of cloud fraction due to a decrease of aerosol number concentration is also shown in the simulations for the 02 June case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Cloud processing and weeklong ageing affect biomass burning aerosol properties over the south-eastern Atlantic

Abstract Southern Africa produces a third of global biomass burning emissions, which have a long atmospheric lifetime and influence regional radiation balance and climate. Here, we use airmass trajectories to link different aircraft observations to investigate the evolution of biomass-burning aerosols during their westward transport from Southern Africa over the south-eastern Atlantic, where a semi-permanent stratocumulus cloud deck is located. Our results show secondary organic aerosol formation during the initial 3 days of transport, followed by decreases in organic aerosol via photolysis before reaching equilibrium. Aerosol absorption wavelength dependency decreases with ageing, due to an increase in particle size and photochemical bleaching of brown carbon. Cloud processing, including aqueous-phase reaction and scavenging, contributes to the oxidation of organic aerosols, while it strongly reduces large diameter particles and single-scattering albedo of biomass burning aerosols. Together, these processes resulted in a marine boundary layer with fewer yet more oxidized and absorbing aerosols.

54 ENVIRONMENTAL SCIENCES↗