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At least 343 records · Page 19

Constraining the Twomey effect from satellite observations: Issues and perspectives

The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd,ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions which also comprises rapid adjustments. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd,ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large scale (hundreds of kilometres) ΔNd,ant remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and vertical wind and by droplet sink processes. These operate at scales on the order of 10s of metres at which only localized observations are available and at which no approach exists yet to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are three key uncertainties in determining ΔNd,ant, namely the quantification (i) of the cloud-active aerosol – the cloud condensation nuclei concentrations (CCN) at or above cloud base –, (ii) of Nd, as well as (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data. A fourth uncertainty, the anthropogenic perturbation to CCN concentrations, is also not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: In terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, the non-direct relation to the concentration of aerosols, the impossibility to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilizing colocated polarimeter and lidar instruments, ideally including high spectral resolution lidar capability at two wavelengths to maximize vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity, and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd – to – CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

Twomey effect↗

Aircraft in-situ measurements from SOCRATES constrain the anthropogenic perturbations of cloud droplet number

Aerosol-cloud interactions (ACI) in warm clouds alter reflected shortwave radiation by influencing cloud microphysical and macrophysical properties. The variable of state controlling ACI is the cloud droplet number concentration (N d ). Here, we examine the perturbations in N d due to anthropogenic aerosols (ΔN d, PD-PI ) using a perturbed parameter ensemble (PPE) hosted in the sixth Community Atmosphere Model (CAM6). Surrogate models are created for the CAM6 PPE outputs and are used to generate 1 million model variants of CAM6 by sampling 45 sources of parameter uncertainty. The range of uncertain physical parameters related to ACI are constrained with observations of aerosol and cloud properties from SOCRATES. The likely range of uncertain parameters and the associated range of ΔN d, PD-PI are more strongly constrained with observations of N d relative to observations of cloud condensation nuclei. We conduct sensitivity tests of how constraints on ΔN d, PD-PI are affected by systematic uncertainties in observations and our limitations in our surrogate models created for CAM6 PPE outputs. Based on this, we provide guidance on the impact of reducing systematic uncertainty in airborne microphysical observations and in surrogate models.

Song, Ci [Univ. of Wyoming, Laramie, WY (United St↗

TPSAS-NF1676L-29931-DND

The ACE science working group satellite concept calls for a combination of high spectral resolution aerosol lidar and a polarimeter able to determine vertical profiles of aerosol extinction and clouds. Here we discuss why an HSRL lidar is required to achieve these requirements. The primary advantage of an HSRL over an elastic backscatter lidar is that the HSRL channel allows for the independent retrieval of vertically resolved aerosol extinction without constraint. Not requiring a constraint means greater availability of retrievals in polar regions, on the night side, and in broken cloud situations, plus greater accuracy particularly in the lowest part of the atmosphere and in scenes with aerosol heterogeneity. Advantages go beyond the extinction products. Unlike attenuated backscatter, which is an integrated quantity, the aerosol backscatter coefficient depends only on the aerosol at a specific level in the atmosphere, making it preferable for use in quantitative applications. The aerosol backscatter coefficient is more accurate from an HSRL system compared to the retrieval from a single-channel system. This is because errors in both extinction and backscatter from a single-channel system increase with decreasing altitude, due to the need to accurately characterize the overlying attenuation. This means that an HSRL will also have more valid data in and near the boundary layer where aerosol is of primary interest for air quality and weather applications and for many climate objectives including aerosol-cloud interaction studies. Even cloud properties that do not directly use the HSRL capability (cloud phase and thin cirrus retrievals) benefit from the more accurate calibration of an HSRL system. The improved accuracy of backscatter and extinction also lead to better capabilities for aerosol typing, improved retrievals of aerosol radiative effect, and increased information content for combined lidar + polarimeter retrievals of profiles of microphysical properties such as vertically resolved effective radius.

S P Burton↗

Buffering of Aerosol-Cloud Adjustments by Coupling Between Radiative Susceptibility and Precipitation Efficiency

Aerosol-cloud interactions (ACI) in warm clouds are the primary source of uncertainty in effective radiative forcing (ERF) during the historical period and, by extension, inferred climate sensitivity. The ERF due to ACI (ERFaci) is composed of the radiative forcing due to changes in cloud microphysics and cloud adjustments to microphysics. Here, we examine the processes that drive ERFaci using a perturbed parameter ensemble (PPE) hosted in CAM6. Observational constraints on the PPE result in substantial constraints in the response of cloud microphysics and macrophysics to anthropogenic aerosol, but only minimal constraint on ERFaci. Examination of cloud and radiation processes in the PPE reveal buffering of ERFaci by the interaction of precipitation efficiency and radiative susceptibility.

54 ENVIRONMENTAL SCIENCES↗

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

Christensen, Matthew [Pacific Northwest National L↗

Cloud microphysical structure analysis based on high-resolution insitu measurements

This study investigates the microphysical parameters and shapes of droplet size distributions (DSDs) along three aircraft traverses of developing convective clouds during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) Phase III 2015 at a sampling frequency of 25 Hz. The droplet number concentration (Nc, cm -3 ), and liquid water content (LWC, g m -3 ) present steep gradients within zones of a few tens of meters near the cloud edges and relatively gentle gradients in the strong updraft zones. Sometimes, the horizontal LWC distribution resembles a trapezoidal shape with steep LWC and Nc gradients near the cloud edges. The LWC maximums (LWC max ) are lower than the adiabatic LWCs, but the high adiabatic fractions in the cloud core indicate low dilution. High LWC/LWC max , largest droplets, and narrow and similarly shaped DSDs are found in the regions of high updrafts. Zones of low LWC/LWC max are found close to the cloud edges, where DSDs are highly diverse, containing both large and small droplets. Finally, we analyze the mixing diagrams. Significant in-phase turbulent fluctuations in LWC and N c were found. The effective radii change slightly across cloud updraft zones but decrease at the zone of low LWC/LWC max ratio close to cloud edges. The spectra of LWC and N c obey Kolmogorov -5/3 turbulence law. The radii of the correlation of LWC and N c in updraft zones are of several tens of meters. Filaments up to 120–175 m in size are also noticed.

54 ENVIRONMENTAL SCIENCES↗

Effective radiative forcing of anthropogenic aerosols in E3SMv1: historical changes, causality, decomposition, and parameterization sensitivities

The effective radiative forcing of anthropogenic aerosols (ERF aer ) is an important measure of the anthropogenic aerosol effects simulated by a global climate model. Here we analyze ERF aer simulated by the E3SMv1 atmosphere model using both century-long free-running atmosphere-land simulations and short nudged simulations. We relate the simulated ERF aer to characteristics of the aerosol composition and optical properties, and evaluate the relationships between key aerosol and cloud properties. In terms of historical changes from the year 1870 to 2014, our results show that the global mean anthropogenic aerosol burden and optical depth increase during the simulation period as expected, but the regional averages show large differences in the temporal evolution. The largest regional differences are found in the emission-induced evolution of the burden and optical depth of the sulfate aerosol: a strong decreasing trend is seen in the Northern Hemisphere high-latitude region after around 1970, while a continued increase is simulated in the tropics. Consequently, although the global mean anthropogenic aerosol burden and optical depth increase from 1870 to 2014, the ERF aer magnitude does not increase after around year 1970. The relationships between key aerosol and cloud properties (relative changes between preindustrial and present-day conditions) also show evident changes after 1970, diverging from the linear relationships exhibited for the period from 1870 to 2014. The ERF aer in E3SMv1 is relatively large compared to the recently published multi-model estimates; the primary reason is the large indirect aerosol effect (i.e., through aerosol-cloud interactions). Compared to other models, E3SMv1 features a stronger sensitivity of the cloud droplet effective radius to changes in the cloud droplet number concentration. Large sensitivity is also seen in the liquid cloud optical depth, which is determined by changes in both the effective radius and liquid water path. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 are found to have a strong correlation, as the evolution of anthropogenic sulfate aerosols affects both the liquid cloud formation and the homogeneous ice nucleation in cirrus clouds. The ERF aer estimates in E3SMv1 for the shortwave and longwave components are sensitive to the parameterization changes in both liquid and ice cloud processes. When the parameterization of ice cloud processes is modified, the top-of-atmosphere forcing changes in the shortwave and longwave components largely offset each other, so the net effect is negligible. This suggests that, to reduce the magnitude of the net ERF aer , it would be more effective to reduce the anthropogenic aerosol effect through liquid or mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗

The MODIS Aerosol Algorithm: Critical Evaluation and Plans for Collection 6

For ten years the MODIS aerosol algorithm has been applied to measured MODIS radiances to produce a continuous set of aerosol products, over land and ocean. The MODIS aerosol products are widely used by the scientific and applied science communities for variety of purposes that span operational air quality forecasting in estimates o[ clear-sky direct radiative effects over ocean and aerosol-cloud interactions. The products undergo continual evaluation, including self-consistency checks and comparisons with highly accurate ground-based instruments. The result of these evaluation exercises is a quantitative understanding of the strengths and weaknesses of the retrieval, where and when the products are accurate and the situations where and when accuracy degrades. We intend 10 present results of the most recent critical evaluations including the first comparison of the over ocean products against the shipboard aerosol optical depth measurements of the Marine Aerosol Network (MAN), the demonstration of the lack of sensitivity to size parameter in the over land products and identification of residual problems and regional issues. While the current data set is undergoing evaluation, we are preparing for the next data processing, labeled Collection 6. Collection 6 will include transparent Quality Flags, a 3 km aerosol product and the 500m resolution cloud mask used within the aerosol n:bicvu|. These new products and adjustments to algorithm assumptions should provide users with more options and greater control, as they adapt the product for their own purposes.

Remer, Lorraine↗

Can Biomass Burning Aerosol Induced Surface Cooling Be Amplified Through Sea Surface Temperature‐Cloud Feedback Over the Southeast Atlantic?

Biomass burning (BB) aerosols exert a strong surface cooling effect over the southeast Atlantic (SEA) via aerosol-radiation and aerosol-cloud interactions. The reduction of the sea surface temperature (SST) can trigger the SST-low cloud feedback. Whether this feedback can amplify the surface cooling effect is examined. The modeling results from the Community Earth System Model version 2 (CESM2) demonstrate that counterintuitively the cloud radiative effect (CRE) caused by the BB aerosols is weaker if SST-low cloud feedback is considered compared to fixed-SST simulation (-2.99 W m -2 vs. -4.79 W m -2 ). This is caused by (a) stronger sea breeze due to larger sea-land temperature contrast causing less smoke transport over SEA and (b) less moisture supply from surface due to colder SST. Changes in SST also lead to counterclockwise rotation of ocean circulation anomalies. Consequently, the excess heat transport from the equator reverses the direction of SST-cloud feedback in this region.

0305↗

Present-day correlations are insufficient to predict cloud albedo change by anthropogenic aerosols in E3SM v2

Cloud albedo susceptibility to droplet number perturbation remains a source of uncertainty in understanding aerosol–cloud interactions and thus both past and present climate states. Through the Energy Exascale Earth System Model (E3SM) v2 experiments, we probe the effects of competing processes on cloud albedo susceptibility of low-lying marine stratocumulus in the northeast Pacific. In present-day conditions, we find that increasing precipitation suppression by aerosols increases cloud albedo susceptibility, whereas increasing cloud sedimentation decreases it. By constructing a hypothetical model configuration exhibiting negative susceptibility under all conditions, we conclude that cloud albedo change due to aerosol perturbation cannot be predicted by present-day co-variabilities in E3SM v2. As such, our null result herein challenges the assumption that present-day climate observations are sufficient to constrain past states, at least in the context of cloud albedo changes to aerosol perturbation.

54 ENVIRONMENTAL SCIENCES↗

Direct numerical simulations of activation and deactivation in turbulent atmospheric clouds

Significant knowledge gaps remain in our understanding of turbulence–cloud–aerosol interactions in the Earth's atmosphere, and direct numerical simulation (DNS) has increasingly become an indispensable tool to fill such critical knowledge gaps. Here, this study is an extension of our previous DNS model [Gao et al., J. Geophys. Res.: Atmos., 123(4), 2194–2214 (2018)], with a focus on the activation of aerosol particles into cloud droplets and deactivation of cloud droplets into aerosol particles in a microscale cloud environment. The effects of turbulence intensity, particle curvature, and solute, as well as the initial distributions of the aerosol particles (monodisperse or polydisperse) are investigated. The governing equations for the flow of air, temperature, and water vapor mixing ratio are solved numerically in the Eulerian fashion, assuming homogeneous and isotropic turbulence. The dynamics of the aerosol and cloud particles are calculated with the Lagrangian particle tracking method. The results show that the deviations of the thermodynamic variables from their respective means are significantly reduced, the activation process appears to be delayed, and the deactivation process occurs more rapidly, as the turbulence intensity is increased. The inclusion of particle curvature and solute effects, as well as polydispersity, tends to retard the activation of aerosols into cloud droplets. It is also observed that fluctuations in supersaturation broaden the spread of particle radii, and the broadening is followed by a narrowing as turbulent homogenization reduces thermodynamic fluctuations over time.

54 ENVIRONMENTAL SCIENCES↗

CMIP5 Climate Models Overestimate Cooling by Volcanic Aerosols

We compare projections of the observed hemispherical mean surface temperature (HadCRUT4.6.0.0) and the ensemble mean of CMIP5 climate models' simulations on a set of standard regression model forcing variables. We find that the volcanic aerosol regression coefficients of the CMIP5 simulations are consistently significantly larger (by 40–49%) than the volcanic aerosol coefficients of the observed temperature. The probability that the observed differences are caused just by chance is much less than 0.01. The overestimate is due to the climate models' response to volcanic aerosol radiative forcing. The largest overestimate occurs in the winter season of each hemisphere. We hypothesize that the models' parameterization of aerosol-cloud interactions within ice and mixed phase clouds is a likely source of this discrepancy. Furthermore, the models significantly underestimate the effect of solar variability on temperature for both hemispheres.

54 ENVIRONMENTAL SCIENCES↗

Untangling causality in midlatitude aerosol–cloud adjustments

Aerosol–cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (Nd) (the first indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of forcing associated with changes in cloud macrophysics in response to aerosol (aerosol–cloud adjustments) remain uncertain. This uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud microphysical state to the cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path (LWP) averaged across cloudy and clear regions (here characterizing the macrophysical state) and Nd (characterizing the microphysical) is the sum of two causal pathways linking Nd to LWP: Nd altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting Nd. Only the former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We hypothesize that the diversity of constraints on aerosol–cloud adjustments in the literature may be partly due to not explicitly characterizing covariance flowing from cloud to aerosol and aerosol to cloud. Here, we restrict our analysis to the regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP (Multisensor Advanced Climatology of Liquid Water Path) and MODIS are compared to simulations in the Met Office Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat flux enhance LWP, while increasing subsidence and sea surface temperature decrease it. A simulation where cloud microphysics are insensitive to changes in Nd is used to characterize covariance between Nd and LWP that is induced by factors other than aerosol–cloud adjustments. By removing variability associated with meteorology and scavenging, we infer the sensitivity of LWP to changes in Nd. Application of this technique to UM GA7.1 simulations reproduces the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments and observed covariability between Nd and LWP predict a 25 %–30 % overestimate by the UM GA7.1 in LWP change and a 30 %–35 % overestimate in associated radiative forcing.

Daniel T. McCoy↗

High Free-Tropospheric Aitken-Mode Aerosol Concentrations Buffer Cloud Droplet Concentrations in Large-Eddy Simulations of Precipitating Stratocumulus

A new Aitken mode aerosol microphysics scheme is developed for a large eddy simulation model in order to better investigate cloud-aerosol interactions in the marine boundary layer and to study the Aitken buffering hypothesis of McCoy et al. (2021), https://doi.org/10.1029/2020jd033529. This scheme extends the single-mode two-moment prognostic aerosol scheme of Berner et al. (2013), https://doi.org/10.5194/acp-13-12549-2013. Seven prognostic variables represent accumulation and Aitken log-normal aerosol modes in air and droplets as well as 3 gas species. Scavenging of interstitial and other unactivated aerosol by cloud and rain drops are treated using the scheme described in Berner et al. (2013), https://doi.org/10.5194/acp-13-12549-2013. The scheme includes coagulation of unactivated aerosol and a simple chemistry model with gas phase H 2 SO 4 , SO 2 , and DMS as prognostic variables to capture basic influences of sulfur chemistry on the model aerosols. Nucleation of H 2 SO 4 aerosol particles from gas-phase H 2 SO 4 is neglected. A deep, precipitating stratocumulus case (VAMOS Ocean Cloud Atmosphere Land Study RF06) is used to test the new scheme. The presence of the Aitken mode aerosol increases the cloud droplet concentration through activation of the larger Aitken particles and delays the creation of an ultraclean, strongly precipitating cumulus state. Scavenging of unactivated accumulation and Aitken particles by cloud and precipitation droplets accelerates the collapse. Increasing either the above-inversion Aitken concentration or the surface Aitken flux increases the Aitken population in the boundary layer and prevents the transition to an ultraclean state.

54 ENVIRONMENTAL SCIENCES↗

Assessing the climate impact of an improved volcanic sulfate aerosol representation in E3SM

Accurately simulating historical surface temperature variations is essential for evaluating climate models, yet many struggle to reproduce the mid-20th-century temperature trends associated with significant volcanic eruptions. This study examines the impact of volcanic sulfate aerosol representation on these biases using the Energy Exascale Earth System Model (E3SM). The standard CMIP6 protocol prescribes volcanic forcing through radiative perturbations, omitting volcanic aerosol–cloud interactions (VACIs). Here, we implement an emission-based approach with an updated volcanic eruption inventory that directly incorporates volcanic sulfur dioxide (SO 2 ) emissions, enabling a more process-based representation of volcanic forcing. This approach leads to improved surface temperature variability and a modest reduction in cold biases between 1940 and 1980 compared to the CMIP6 setup. Additionally, we assess cloud property responses to a more realistic volcanic sulfate aerosol representation, which weakens cloud-induced cooling during periods of lower volcanic activity. However, despite these refinements, a significant temperature cold bias remains, indicating that further improvements in atmospheric chemistry, aerosol microphysics, cloud processes, and model parameterizations are needed to fully resolve this issue in E3SM.

54 ENVIRONMENTAL SCIENCES↗

Human-Induced Climate Variations Linked to Urbanization: From Observations to Modeling

The goal of this session is to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results focusing on the impact of urbanization on the climate. The discussion will highlight current observational and modeling capabilities being employed for investigating the urban environment and its linkage to the change in the Earth's climate system. The goal of the session is to identify our current stand and the future direction on the topic. Urbanization is one of the extreme cases of land use change. Most of population of the world has moved to urban areas. By 1995, more than 70% of population of North America and Europe were living in cities. By 2025, the United Nations estimates that 60% of the worlds population will live in cities. Although currently only 1.2% of the land is urban, better understanding of how the atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of human activities on this system is critical. Our understanding of urbanization effect is incomplete, partly because human activities induce new changes on climate in addition to the original natural variations, and partly because previously few data available for study urban effect globally. Urban construction changes surface roughness, albedo, heat capacity and vegetation coverage. Traffic and industry increase atmospheric aerosol. It is suggested that urbanization may modify rainfall processes through aerosol-cloud interactions or dynamic feedbacks. Because urbanization effect on climate is determined by many factors including land cover, the city's microscale features, population density, and human lifestyle patterns, it is necessary to study urban areas over globe.

Shepherd, J. Marshall↗

Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble

Abstract. Aerosol–cloud interactions (ACIs) are the largest source of uncertainty in inferring the magnitude of future warming consistent with the observational record. The effective radiative forcing due to ACI (ERFaci) is dominated by liquid clouds and is composed of two terms: the change in cloud albedo due to redistributing liquid over a larger number of cloud droplets (Nd) and the change in cloud macrophysical properties due to changes in cloud microphysics. These terms are, respectively, referred to as the radiative forcing due to ACI (RFaci) and aerosol–cloud adjustments. While the magnitude of RFaci is uncertain, its sign is confidently negative and results in a cooling in the historical record. In contrast, the adjustment of cloud liquid water path (LWP) to enhanced Nd and associated radiative forcing is uncertain in sign. Increased LWP in response to increased Nd is consistent with precipitation suppression, while decreased LWP in response to increased Nd is consistent with enhanced evaporation from cloud top. Observational constraints of these processes are poor in part because of causal ambiguity in the relationship between Nd and LWP. To better understand this relationship, precipitation (P), Nd, and LWP surface observations from the Eastern North Atlantic (ENA) atmospheric observatory are combined with the output from a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model version 6 (CAM6). This allows for causal interpretation of observed covariability. Observations of precipitation and cloud from ENA constrain the range of possible LWP aerosol–cloud adjustments relative to the prior from the PPE by 15 %, resulting in a global value that is confidently positive (a historical cooling) ranging from 2.1 to 6.9 g m−2. It is found that observed covariability between Nd and LWP is dominated by coalescence scavenging and that this observed covariability is not strongly related to aerosol–cloud adjustments.

54 ENVIRONMENTAL SCIENCES↗

CROCUS Dual Polarization Ceilometer Data at Northeastern Illinois University Rooftop

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

54 ENVIRONMENTAL SCIENCES↗