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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

OpenCRUMS USA: An Open Machine Learning Framework for Characterizing Variability in Aerosol Reanalysis Data

Advances in artificial intelligence (AI) have called for exploring how these techniques can be used for exploring patterns in large climate datasets. To that regard, the U.S. Department of Energy AI for Earth System Predictability (AI4ESP) supported a pilot initiative called the Open Classification of Regimes in the Southeast USA (OpenCRUMS USA) project to explore how AI can be used to characterize modes of spatial variability in large climate datasets. For this study, we focus on comparing two methods for characterizing the modes of spatial variability of surface aerosol concentration over the Houston region: empirical orthogonal functions (EOFs) and layerwise relevance propagation (LRP) applied to a convolutional neural network (CNN) classifier. We show that EOF analysis typically attributes spatial variability modes that span all of southeast Texas, prohibiting the attribution of spatial variability to localized regions. However, using LRP on the CNN classifier resolves the explanatory parameters at a finer spatial resolution than EOFs. This allows for the attribution of the spatial variability of surface aerosols to local regions of organic carbon which was not possible using EOFs. In addition, the LRP analysis also suggests that synoptic-scale transport of dust is most prevalent during anticyclonic and pretrough synoptic conditions as categorized by self-organizing maps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Apparent dust size discrepancy in aerosol reanalysis in north African dust after long-range transport

North African dust reaches the southeastern United States every summer. Size-resolved dust mass measurements taken in Miami, Florida, indicate that more than one-half of the surface dust mass concentrations reside in particles with geometric diameters less than 2.1 µm, while vertical profiles of micropulse lidar depolarization ratios show dust reaching above 4 km during pronounced events. These observations are compared to the representation of dust in the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) aerosol reanalysis and closely related Goddard Earth Observing System model version 5 (GEOS-5) Forward Processing (FP) aerosol product, both of which assimilate satellite-derived aerosol optical depths using a similar protocol and inputs. These capture the day-to-day variability in aerosol optical depth well, in a comparison to an independent sun-photometer-derived aerosol optical depth dataset. Most of the modeled dust mass resides in diameters between 2 and 6 µm, in contrast to the measurements. Model-specified mass extinction efficiencies equate light extinction with approximately 3 times as much aerosol mass, in this size range, compared to the measured dust sizes. GEOS-5 FP surface-layer sea salt mass concentrations greatly exceed observed values, despite realistic winds and relative humidities. In combination, these observations help explain why, despite realistic total aerosol optical depths, (1) free-tropospheric model volume extinction coefficients are lower than those retrieved from the micro-pulse lidar, suggesting too-low model dust loadings in the free troposphere, and (2) model dust mass concentrations near the surface can be higher than those measured. The modeled vertical distribution of dust, when captured, is reasonable. Large, aspherical particles exceeding the modeled dust sizes are also occasionally present, but dust particles with diameters exceeding 10 µm contribute little to the measured total dust mass concentrations after such long-range transport. Remaining uncertainties warrant a further integrated assessment to confirm this study's interpretations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of Aerosol and Environmental Conditions on Maritime and Continental Deep Convective Systems Using a Bin Microphysical Model

A series of model simulations were conducted to investigate the effects of cloud condensation nuclei (CCN) loading and convective available potential energy (CAPE) on tropical maritime and midlatitude continental deep convection. Dynamical downscaling from global aerosol reanalysis was used to represent aerosol fields for the two convective regimes. We describe a control run and multiple sensitivity experiments using a limited-area model, employing spectral-bin cloud microphysics. The CCN loading is perturbed between the target maritime and continental conditions, roughly 40–2,000 cm -3 at 850 hPa and 1% supersaturation. Surface precipitation rates monotonically increase with increasing CCN loading for both the maritime and continental situations, while these monotonic increases are disrupted in the simulations with reduced CAPE. The increase in precipitation is in the form of convective precipitation, at the expense of stratiform precipitation. CCN increases promote increases in supercooled cloud water, in agreement with previous modeling studies. However, in the simulations investigated herein, the changes in supercooled water have different impacts on the cloud microphysics in the maritime and continental simulations. Increased supercooled water contents lead to more hail and less graupel in the continental simulation. For the maritime simulation, enhanced supercooled cloud water contents promote an increase in graupel since little or no hail is produced. This distinction is due to the difference in relative magnitudes and peak altitudes of supercooled water and snow amounts, which is further attributable to moisture and dynamical differences in the two cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Lagrangian analysis of pockets of open cells over the southeastern Pacific

Abstract. Pockets of open cells (POCs) have been shown to develop within closed-cell stratocumulus (StCu), and a large body of evidence suggests that the development of POCs result from changes in small-scale processes internal to the boundary layer rather than large-scale forcings. Precipitation is widely viewed as a key process important to POC development and maintenance. In this study, GOES-16 satellite observations are used in conjunction with MERRA-2 winds to track and compare the microphysical and environmental evolution of two populations of closed-cell StCu selected by visual inspection over the southeastern Pacific Ocean: one group that transitions to POCs and another comparison group (CLOSED) that does not. The high spatiotemporal resolution of the new GOES-16 data allows for a detailed examination of the temporal evolution of POCs in this region. We find that POCs tend to develop near the coast, last tens of hours, are larger than 104 km2, and often (88 % of cases) do not re-close before they exit the StCu deck. Most POCs are observed to form at night and tend to exit the StCu during the day when the StCu is contracting in area. Relative to the CLOSED trajectories, POCs have systematically larger effective radii, lower cloud drop number concentrations, a comparable conditional in-cloud liquid water path, and a higher frequency of more intense precipitation. Meanwhile, no systematic environmental differences other than boundary layer height are observed between POC and CLOSED trajectories. Interestingly, there are no differences in reanalysis aerosol optical depth between both sets of trajectories, which may lead one to the interpretation that differences in aerosol concentrations are not influencing POC development or resulting in a large number that re-close. However, this largely depends on the reanalysis treatment of aerosol–cloud interactions, and the product used in this study has no explicit handling of these important processes. These results support the consensus view regarding the importance of precipitation on the formation and maintenance of POCs and demonstrate the utility of modern geostationary remote sensing data in evaluating the POC life cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of long-range transport of aerosols on marine-boundary-layer clouds in the eastern North Atlantic

Vertical profiles of aerosols are inadequately observed and poorly represented in climate models, contributing to the current large uncertainty associated with aerosol–cloud interactions. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) aircraft field campaign near the Azores islands provided ample observations of vertical distributions of aerosol and cloud properties. Here we utilize the in situ aircraft measurements from the ACE-ENA and ground-based remote-sensing data along with an aerosol-aware Weather Research and Forecast (WRF) model to characterize the aerosols due to long-range transport over a remote region and to assess their possible influence on marine-boundary-layer (MBL) clouds. The vertical profiles of aerosol and cloud properties measured via aircraft during the ACE-ENA campaign provide detailed information revealing the physical contact between transported aerosols and MBL clouds. The European Centre for Medium-Range Weather Forecasts Copernicus Atmosphere Monitoring Service (ECMWF-CAMS) aerosol reanalysis data can reproduce the key features of aerosol vertical profiles in the remote region. The cloud-resolving WRF sensitivity experiments with distinctive aerosol profiles suggest that the transported aerosols and MBL cloud interactions (ACIs) require not only aerosol plumes to get close to the marine-boundary-layer top but also large cloud top height variations. Based on those criteria, the observations show that the occurrence of ACIs involving the transport of aerosol over the eastern North Atlantic (ENA) is about 62 % in summer. For the case with noticeable long-range-transport aerosol effects on MBL clouds, the susceptibilities of droplet effective radius and liquid water content are -0.11 and +0.14, respectively. When varying by a similar magnitude, aerosols originating from the boundary layer exert larger microphysical influence on MBL clouds than those entrained from the free troposphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Signatures of aerosol-cloud interactions in GiOcean: a coupled global reanalysis with two-moment cloud microphysics

Aerosols influence the Earth's radiative balance through direct interactions with radiation and by affecting cloud properties. Anthropogenic aerosols have led to cooling during the industrial era through aerosol–cloud interactions (ACI), including aerosol effects on cloud microphysical properties and the subsequent adjustments. However, large uncertainties remain in Earth system models (ESMs) regarding the magnitude of this cooling. In part, ESMs substantially disagree on cloud properties, thermodynamics, the hydrological cycle, and general circulation. Reanalysis provides a useful avenue for exploring the impact of ACI on clouds and radiation because its atmosphere is forced to match realistic conditions through the assimilation of observations. Here, we explore the impact of ACI on clouds in the GiOcean reanalysis – the first to incorporate aerosol-cloud interactions. We contrast variables important for ACI between GiOcean and satellite observations and develop 2-dimensional lookup tables of ACI for both using a source-sink budget perspective to attribute the changes in cloud droplet number (Nd) and liquid water path (LWP) to aerosol and meteorology. A compositing analysis using lookup tables shows that GiOcean captures key aspects of aerosol–cloud–precipitation interactions, including (1) activation of aerosol into cloud droplets, (2) effective precipitation scavenging of Nd, (3) suppression of precipitation by high Nd in regions with heavy aerosol emissions. In contrast, satellite observations do not exhibit clear patterns for processes (2) and (3). Random Forest analysis shows that interannual variability in Nd and LWP over the Northern Hemisphere ocean in GiOcean is primarily driven by precipitation, consistent with satellite observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Realism of Lagrangian Large Eddy Simulations Driven by Reanalysis Meteorology: Tracking a Pocket of Open Cells Under a Biomass Burning Aerosol Layer

An approach to drive Lagrangian large eddy simulation (LES) of boundary layer clouds with reanalysis data is presented and evaluated using satellite (Spinning Enhanced Visible and Infrared Imager, SEVIRI) and aircraft (Cloud-Aerosol-Radiation Interactions and Forcing, CLARIFY) measurements. The simulations follow trajectories of the boundary layer flow. They track the formation and evolution of a pocket of open cells (POC) underneath a biomass burning aerosol layer in the free troposphere. The simulations reproduce the evolution of observed stratocumulus cloud morphology, cloud optical depth, and cloud drop effective radius, and capture the timing of the cloud state transition from closed to open cells seen in the satellite imagery on the three considered trajectories. They reproduce a biomass burning aerosol layer identified by the in-situ aircraft measurements above the inversion of the POC. Entrainment of aerosol from the biomass burning layer into the POC is limited to the extent of having no impact on cloud- or boundary layer properties, in agreement with the CLARIFY observations. The two-moment bin microphysics scheme used in the simulations reproduces the in-situ cloud microphysical properties reasonably well. A two-moment bulk microphysics scheme reproduces the satellite observations in the non-precipitating closed-cell state, but overestimates liquid water path and cloud optical depth in the precipitating open-cell state due to insufficient surface precipitation. A boundary layer cold and dry bias occurring in LES can be counteracted by reducing the grid aspect ratio and by tightening the large scale wind speed nudging towards the surface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Drivers of Cloud Condensation Nuclei in the Eastern North Atlantic as Observed at the ARM Site

Abstract Seven years of data collected at the Atmospheric Radiation Measurement's Eastern North Atlantic (ENA) site are analyzed to understand the controls of Cloud Condensation Nuclei (CCN) concentrations in the region. Day‐night differences in the aerosol data as segregated by wind direction demonstrate the aerosol observations to be impacted by local emissions when the wind direction (wdir) is between 90° and 310° (measured clockwise from the North where air is coming from). Data collected during marine conditions (wdir <90° or wdir >310°) show the CCN concentrations to be higher in the summer months as compared to the winter months. CCN budget analysis revealed advection and precipitation scavenging being primarily responsible for modulating the CCN concentrations at the site on monthly timescales, with rain rates driving the precipitation scavenging term. High (greater than 75th percentile) and low (lower than 25th percentile) CCN events were identified for each month to characterize the sub‐monthly variability of CCN concentrations. Low CCN events had thicker clouds, stronger rain rates, and lower reanalysis reported free‐tropospheric aerosol pseudo number concentration at the ENA site as compared to the high CCN events. Analysis of satellite data of air‐parcels 48 hr prior to their arrival at the ENA site demonstrated the air parcels during low CCN events to encounter higher cloudiness, stronger rain rates, and higher cloud top heights as compared to the high CCN events. The results presented herein provide key constraints for model evaluation studies and climatological studies conducted at the ENA site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cloud condensation nuclei concentrations derived from the CAMS reanalysis

Determining number concentrations of cloud condensation nuclei (CCN) is one of the first steps in the chain in analysis of cloud droplet formation, the direct microphysical link between aerosols and cloud droplets, and a process key for aerosol–cloud interactions (ACI). However, due to sparse coverage of in situ measurements and difficulties associated with retrievals from satellites, a global exploration of their magnitude, source as well as temporal and spatial distribution cannot be easily obtained. Thus, a better representation of CCN numbers is one of the goals for quantifying ACI processes and achieving uncertainty-reduced estimates of their associated radiative forcing. Here, we introduce a new CCN dataset which is derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework suitable for global models. The emitted aerosols in CAMSRA are not only based on input from emission inventories using aerosol observations, they also have a strong tie to satellite-retrieved aerosol optical depth (AOD) as this is assimilated as a constraining factor in the reanalysis. Furthermore, the reanalysis interpolates for cases of poor or missing retrievals and thus allows for a full spatiotemporal quantification of CCN numbers. The derived CCN dataset captures the general trend and spatial and temporal distribution of total CCN number concentrations and CCN from different aerosol species. A brief evaluation with ground-based in situ measurements demonstrates the improvement of the modelled CCN over the sole use of AOD as a proxy for CCN as the overall correlation coefficient improved from 0.37 to 0.71. However, we find the modelled CCN from CAMSRA to be generally high biased and find a particular erroneous overestimation at one heavily polluted site which emphasises the need for further validation. The CCN dataset (https://doi.org/10.26050/WDCC/QUAERERE_CCNCAMS_v1, Block, 2023), which is now freely available to users, features 3-D CCN number concentrations of global coverage for various supersaturations and aerosol species covering the years 2003–2021 with daily frequency. This dataset is one of its kind as it offers lots of opportunities to be used for evaluation in models and in ACI studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Regime-based aerosol–cloud interactions from CALIPSO-MODIS and the Energy Exascale Earth System Model version 2 (E3SMv2) over the Eastern North Atlantic

This study investigates aerosol-cloud interactions in marine boundary layer (MBL) clouds using an advanced deep-learning-driven synoptic-regime-based framework, combining satellite data (CALIPSO vertically resolved aerosol extinction and MODIS cloud properties) with 1° nudged Energy Exascale Earth System Model version 2 (E3SMv2) simulation over the Eastern North Atlantic (ENA; ∼10°×10°, 2006–2014). The E3SMv2 captures observed seasonal variations in cloud droplet number concentrations (N d ) and liquid water path (LWP), though it systematically underestimates N d . We then partition ENA meteorology into four synoptic regimes (Pre-Trough, Post-Trough, Ridge, Trough) via a deep-learning clustering of ERA5 reanalysis fields, enabling regime-dependent aerosol-cloud interactions analyses. Both satellite and E3SMv2 exhibit an inverted-V LWP-N d relationship. In Post-Trough and Ridge regimes, the satellite shows stronger negative LWP-N d sensitivities than in Pre-Trough regime. The Trough regime displays a muted satellite LWP response. In comparison, the model predicts more exaggerated LWP responses across regimes, with LWP increasing too quickly at low N d and decreasing more sharply at high N d , especially in Pre-Trough and Trough regimes. These exaggerated model LWP sensitivities may stem from uncertainties in representing drizzle processes, entrainment, and turbulent mixing. As for N d susceptibility to aerosols, N d increases with MBL aerosol extinction in both datasets, but the simulated aerosol-cloud interactions appear oversensitive to meteorological conditions. Overall, E3SMv2 better captures aerosol effects under regimes that favor stratiform clouds (Post-Trough, Ridge), but performance deteriorates for regimes with deeper, dynamically complex clouds (Trough), highlighting the need for improved representations of those cloud processes in climate models.

Environmental sciences↗
DOE OSTI2025

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

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

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Intensifying heat extremes in China attributed to rising greenhouse gases and declining aerosols since the 2010s

Rising temperatures have increased the frequency, duration, and intensity of extreme temperature events over China in recent decades. The upward trends in heat extremes in China in the warm season (May–September) and their relationships with changes in aerosols and greenhouse gases are investigated using observations, reanalysis data and model results. Significant increasing trends in China are observed in daily maximum temperatures (TXx), heatwave frequency, and heatwave mean duration during 2011–2023, with increasing rates of 0.70 °C/decade, 3.77 d/decade and 0.31 d/event/decade, respectively. This study shows that 43 ± 3% of the TXx increases in China are attributed to the rising CO2 concentrations. Aerosol optical depth in China decreased at a rate of 0.054 per decade from 2011 to 2023 due to significant air quality improvements. The weakened aerosol cooling effect due to declining aerosols contributes 27 ± 3% to the observed TXx trend. In eastern China, where aerosol reductions were most significant, aerosol reduction even accounts for 79 ± 10% of the TXx increasing trend. The intensifying heat waves attributed to GHGs and aerosols are in accordance with the increasing extreme high temperatures. The results highlight the significant impacts of rising GHGs and decreasing aerosols on heat extreme events over China in recent years, emphasizing the need of considering both GHGs and aerosols to address the issue of intensification of heat extremes in a warming future.

Zou, Aili↗
DOE OSTI2025

Aerosol Decline Accelerates the Increasing Extreme Precipitation in China

Extreme precipitation is becoming more intense and frequent. The increasing trends in extreme precipitation in China in warm season related to changes in aerosols and greenhouse gases (GHGs) are investigated using observations, reanalysis data and model simulations. A significant accelerating increase in extreme precipitation occurred around 2010, with the trend in accumulated extreme rainfall amount (R95pTOT) increasing from 2.88 mm per decade during 2000–2010 to 22.88 mm per decade during 2010–2023. The sudden acceleration of the increasing extreme precipitation is largely attributed to the reverse in aerosol trends associated with China’s clean air actions, which affects extreme precipitation through perturbing cloud microphysics and atmospheric dynamics, accounting for half of the change in R95pTOT trends. Future aerosol reduction to achieve carbon neutrality is shown to continue to intensify the extreme precipitation, which overweighs the effect induced by GHGs, highlighting the importance of aerosol changes in modulating future climate and weather extremes.

58 GEOSCIENCES↗
DOE OSTI2022

Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects

Abstract. A previous study on the use of nudging in E3SM Atmosphere Model version 1 (EAMv1) had an unresolved issue; i.e., a simulation nudged to EAMv1's own meteorology showed non-negligible deviations from the free-running baseline simulation over some of the subtropical marine stratocumulus and trade cumulus regions. Here, we demonstrate that the deviations can be substantially reduced by (1) changing where the nudging tendency is calculated in the time integration loop of a nudged EAM simulation so as to improve consistency with the free-running baseline and (2) increasing the frequency of the constraining data so as to better capture strong sub-diurnal variations. The fact that modification (2) improves the climate representativeness of the nudged simulations has motivated us to investigate whether the use of newer reanalysis products with higher data frequency can help improve nudged hindcast simulations by better capturing the observed weather events. To answer this question, we present simulations conducted at EAMv1's standard horizontal resolution (approximately 1∘) with nudging towards 6-hourly ERA-Interim reanalysis or 6-hourly, 3-hourly, or hourly ERA5 reanalysis. These simulations are evaluated against the climatology of free-running EAMv1 simulations as well as reanalyses, satellite retrievals, and in situ measurements from the Atmospheric Radiation Measurement user facility. For the 1∘ EAMv1 simulations, we recommend using the relocated nudging tendency calculation and the ERA5 reanalysis at 3-hourly or higher frequency. Simulations used for estimating the anthropogenic aerosol effects often use nudging to help discern signal from noise. The sensitivity of such estimates to the configuration of nudging is investigated in EAMv1, again using the standard 1∘ horizontal resolution. We find that, when estimating the global mean effects, the frequency of constraining data has relatively small impacts, while the choice of nudged variables can change the results substantially. The nudging of air temperature (in addition to horizontal winds) has two non-negligible effects. First, when the constraining data come from reanalysis, the nudging-induced mean bias correction can cause significant changes in the simulated clouds and hence substantially different estimates of the aerosol effects. The impact of the mean bias correction on ice cloud formation has been noted in previous studies and is also seen in EAMv1. For applications like ours, where the preferred configurations of nudging are those capable of providing results consistent with the multi-year free-running simulations, the consequence of the mean bias correction is undesirable. The second important impact of temperature nudging is a significant suppression of adjustments to aerosol forcing, which also causes changes in the estimated aerosol effects. This effect can be seen in simulations nudged to either reanalysis or EAM's own meteorology. These results suggest that nudging horizontal winds but not temperature is a better choice for estimating the anthropogenic aerosol effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Contrasting characteristics of open- and closed-cellular stratocumulus cloud in the eastern North Atlantic

Abstract. Extensive regions of marine boundary layer cloud impact the radiative balance through their significant shortwave albedo while having little impact on outgoing longwave radiation. Despite this importance, these cloud systems remain poorly represented in large-scale models due to difficulty in representing the processes that drive their life cycle and coverage. In particular, the mesoscale organization and cellular structure of marine boundary clouds have important implications for the subsequent cloud feedbacks. In this study, we use long-term (2013–2018) observations from the Atmospheric Radiation Measurement (ARM) Facility's Eastern North Atlantic (ENA) site on Graciosa Island, Azores, Portugal, to identify cloud cases with open- or closed-cellular organization. More than 500 h of each organization type are identified. The ARM observations are combined with reanalysis and satellite products to quantify the cloud, precipitation, aerosol, thermodynamic, and large-scale synoptic characteristics associated with these cloud types. Our analysis shows that both cloud organization populations occur during similar sea surface temperature conditions, but the open-cell cases are distinguished by stronger cold-air advection and large-scale subsidence compared to the closed-cell cases, consistent with their formation during cold-air outbreaks. We also find that the open-cell cases were associated with deeper boundary layers, stronger low-level winds, and higher rain rates compared to their closed-cell counterparts. Finally, raindrops with diameters larger than 1 mm were routinely recorded at the surface during both populations, with a higher number of large drops during the open-cellular cases. The similarities and differences noted herein provide important insights into the environmental and cloud characteristics during varying marine boundary layer cloud mesoscale organization and will be useful for the evaluation of model simulations for ENA marine clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Misrepresentation of the Southern African Easterly Jet in Models and Its Implications for Aerosol, Clouds, and Precipitation Distributions

The southern African easterly jet (AEJ-S) is an important midtropospheric feature critical to understanding the tropical convective system over central Africa and the aerosol–cloud interactions over the southeast Atlantic Ocean. However, it remains unclear how well models represent the AEJ-S and its influence on aerosol transport, clouds, and precipitation distribution. Here, in this work, we use ground- and satellite-based observations and reanalysis datasets to assess the representation of AEJ-S in the Coupled Model Intercomparison Project phase 6 (CMIP6) models between September and October during the peak of midtropospheric winds, aerosol transport, clouds, and precipitation. We find that most CMIP6 models have difficulty accurately simulating the strength, position, and spatial distribution of the AEJ-S. Specifically, the AEJ-S is relatively weaker and at a slightly lower altitude in the ensemble of CMIP6 models than represented by observation and reanalysis datasets. To assess the influence of the misrepresented the AEJ-S on CMIP6-simulated aerosol, clouds, and precipitation distributions, we performed composite analyses using models with low and high biases based on the estimates of their midtropospheric easterly wind speed. We find that the misrepresentation of the AEJ-S in CMIP6 models is associated with the overestimation of clouds and precipitation over central Africa, the underestimation of clouds over the southeast Atlantic Ocean, and the limitation of aerosol transport over the continent or the deviation of its spatial distribution from the typical zonal transport over the Atlantic Ocean. Because aerosols, clouds, and precipitation are important components of the regional climate system, we conclude that accurate representation of the AEJ-S is essential over central Africa and the southeast Atlantic Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of aerosol–cloud interactions in E3SM using a Lagrangian framework

A Lagrangian framework is used to evaluate aerosol–cloud interactions in the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 1 (E3SMv1) for measurements taken at Graciosa Island in the Azores where a U.S. Department of Energy Atmosphere Radiation Measurement (ARM) site is located. This framework uses direct measurements of cloud condensation nuclei (CCN) concentration (instead of relying on satellite retrievals of aerosol optical depth) and incorporates a suite of ground-based ARM measurements, satellite retrievals, and meteorological reanalysis products that when applied to over a 1500 trajectories provides key insights into the evolution of low-level clouds and aerosol radiative forcing that is not feasible from a traditional Eulerian analysis framework. Significantly lower concentrations (40 %) of surface CCN concentration are measured when precipitation rates in 48 h back trajectories average above 1.2 mm d -1 in the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product. The depletion of CCN concentration when precipitation rates are elevated is nearly twice as large in the ARM observations compared to E3SMv1 simulations. The model CCN concentration bias remains significant despite modifying the autoconversion and accretion rates in warm clouds. As the clouds in trajectories associated with larger surface-based CCN concentration advect away from Graciosa Island, they maintain higher values of droplet number concentrations (N d ) over multiple days in observations and E3SM simulations compared to trajectories that start with lower CCN concentrations. The response remains robust even after controlling for meteorological factors such as lower troposphere stability, the degree of cloud coupling with the surface, and island wake effects. E3SMv1 simulates a multi-day aerosol effect on clouds and a Twomey radiative effect that is within 30 % of the ARM and satellite observations. However, the mean cloud droplet concentration is more than 2–3 times larger than in the observations. While Twomey radiative effects are similar amongst autoconversion and accretion sensitivity experiments, the liquid water path and cloud fraction adjustments are positive when using a regression model as opposed to negative when using the present-day minus pre-industrial aerosol emissions approach. This result suggests that tuning the autoconversion and accretion alone is unlikely to produce the desired aerosol susceptibilities in E3SMv1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗