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Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb ). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb ), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day.

Collisional growth of cloud droplets is an essential yet uncertain process for drizzle and precipitation formation. To improve the quantitative understanding of this key component of cloud‐aerosol‐turbulence interactions, observational studies of collision‐coalescence in a controlled laboratory environment are needed. In an existing convection‐cloud chamber (the Pi Chamber), collisional growth is limited by low liquid water content and short droplet residence times. In this work, we use numerical simulations to explore various configurations of a convection‐cloud chamber that may intensify collision‐coalescence. We employ a large‐eddy simulation (LES) model with a size‐resolved (bin) cloud microphysics scheme to explore how cloud properties and the intensity of collision‐coalescence are affected by the chamber size and aspect ratio, surface roughness, side‐wall wetness, side‐wall temperature arrangement, and aerosol injection rate. Simulations without condensation and evaporation within the domain are first performed to explore the turbulence dynamics and wall fluxes. The LES wall fluxes are used to modify the Scalar Flux‐budget Model, which is then applied to demonstrate the need for non‐uniform side‐wall temperature (two side walls as warm as the bottom and the two others as cold as the top) to maintain high supersaturation in a tall chamber. The results of LES with full cloud microphysics reveal that collision‐coalescence is greatly enhanced by employing a taller chamber with saturated side walls, non‐uniform side‐wall temperature, and rough surfaces. For the conditions explored, although lowering the aerosol injection rate broadens the droplet size distribution, favoring collision‐coalescence, the reduced droplet number concentration decreases the frequency of collisions. Plain Language Summary A convection‐cloud chamber is useful in understanding how turbulence affects the interaction between aerosols and cloud droplets. The current convection‐cloud chamber (the Pi Chamber) is likely too small to explore how turbulence affects the collision‐coalescence among cloud droplets. To see whether collisional growth may be observable in a larger cloud chamber, we use numerical simulations to model the cloud droplet size distributions under several different configurations of the cloud chamber. The results suggest that the likelihood of detectable collisional growth increases significantly in a tall chamber with two warm and two cold saturated side walls and rough wall surfaces. Key Points Collision‐coalescence effects on a steady‐state droplet size distribution are stronger in a taller chamber Wet side walls are essential for maintaining cloud liquid water in a chamber with a low width‐to‐height aspect ratio Rougher surfaces increase surface heat and moisture fluxes, leading to larger liquid water content that promotes collision‐coalescence

Aerosol‐cloud interactions (ACI) pose the largest uncertainty for climate projection. Among many challenges of understanding ACI, the question of whether ACI can be deterministically predicted has not been explicitly answered. Here we attempt to answer this question by predicting cloud droplet number concentration Nc${N}_{c}$from aerosol number concentration Na${N}_{a}$and ambient conditions using a data‐driven framework. We use aerosol properties, vertical velocity fluctuations, and meteorological states from the ACTIVATE field observations (2020–2022) as predictors to estimate Nc${N}_{c}$ . We show that the campaign‐wide Nc${N}_{c}$can be successfully predicted using machine learning models despite the strongly nonlinear and multi‐scale nature of ACI. However, the observation‐trained machine learning model fails to predict Nc${N}_{c}$in individual cases while it successfully predicts Nc${N}_{c}$of randomly selected data points that cover a broad spatiotemporal scale. This suggests that, within a data‐driven framework, the Nc${N}_{c}$prediction is uncertain at fine spatiotemporal scales. Plain Language Summary Ambient aerosol particles act as seeds for ice crystals and cloud droplets that form clouds. Both aerosols and clouds regulate the energy and water budgets of the Earth via radiative and cloud micro/macro‐processes. This is the so‐called aerosol‐cloud interactions (ACI). ACI remains the source of the largest uncertainty for accurate climate projections, due to incomplete understanding of nonlinear multi‐scale processes, limited observations across various cloud regimes, and insufficient computational power to resolve them in models. Quantifying the relation between the cloud droplet Nc$\\left({N}_{c}\\right)$and aerosol Na$\\left({N}_{a}\\right)$number concentration has been a central challenge of understanding and representing ACI. In this work, we tackle this challenge by predicting Nc${N}_{c}$from observations made during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) using machine learning models. We show that the climatological Nc${N}_{c}$can be successfully predicted despite the strongly nonlinear and multi‐scale nature of ACI. However, the observation‐trained machine learning model fails to predict Nc${N}_{c}$at fine spatiotemporal scales. Key Points Three‐year in situ measurements (179 flights) provide adequate data to train and validate a random forest model (RFM) to study aerosol‐cloud interactions The RFM can successfully predict cloud droplet number concentration Nc${N}_{c}$and identify importance of key predictors Data‐driven Nc${N}_{c}$prediction in individual cases shows strong dependency on sampling strategy

Marine stratocumulus clouds cover nearly one-quarter of the ocean surface and thus play an extremely important role in determining the global radiative balance. The semipermanent marine stratocumulus deck over the southeastern Atlantic Ocean is of particular interest, because of its interactions with seasonal biomass burning aerosols that are emitted in southern Africa. Understanding the impacts of biomass burning aerosols on stratocumulus clouds and the implications for regional and global radiative balance is still very limited. Previous studies have focused on assessing the magnitude of the warming caused by solar scattering and absorption by biomass burning aerosols over stratocumulus (the direct radiative effect) or cloud adjustments to the direct radiative effect (the semidirect effect). Here, using a nested modeling approach in conjunction with observations from multiple satellites, we demonstrate that cloud condensation nuclei activated from biomass burning aerosols entrained into the stratocumulus (the microphysical effect) can play a dominant role in determining the total radiative forcing at the top of the atmosphere, compared with their direct and semidirect radiative effects. Biomass burning aerosols over the region and period with heavy loadings can cause a substantial cooling (daily mean −8.05 W m−2), primarily as a result of clouds brightening by reducing the cloud droplet size (the Twomey effect) and secondarily through modulating the diurnal cycle of cloud liquid water path and coverage (the cloud lifetime effect). Our results highlight the importance of realistically representing the interactions of stratocumulus with biomass burning aerosols in global climate models in this region.

The largest uncertainty in the historical radiative forcing of climate is caused by the interaction of aerosols with clouds. Historical forcing is not a directly measurable quantity, so reliable assessments depend on the development of global models of aerosols and clouds that are well constrained by observations. However, there has been no systematic assessment of how reduction in the uncertainty of global aerosol models will feed through to the uncertainty in the predicted forcing. We use a global model perturbed parameter ensemble to show that tight observational constraint of aerosol concentrations in the model has a relatively small effect on the aerosol-related uncertainty in the calculated forcing between preindustrial and present-day periods. One factor is the low sensitivity of present-day aerosol to natural emissions that determine the preindustrial aerosol state. However, the major cause of the weak constraint is that the full uncertainty space of the model generates a large number of model variants that are equally acceptable compared to present-day aerosol observations. The narrow range of aerosol concentrations in the observationally constrained model gives the impression of low aerosol model uncertainty. However, these multiple “equifinal” models predict a wide range of forcings. To make progress, we need to develop a much deeper understanding of model uncertainty and ways to use observations to constrain it. Equifinality in the aerosol model means that tuning of a small number of model processes to achieve model–observation agreement could give a misleading impression of model robustness.

The radiative effect of aerosol on cloud albedo via altering cloud droplet effective radius (re) is a major uncertainty in the Earth's climate system. Remote sensing studies have reported either negative or positive relationships between re and aerosol number concentration (Na) or other aerosol proxies. However, there are much fewer in situ observational evidences and physical explanation remains elusive for the contrasting Na‐re relationships. Here we quantify the Na‐re relationship by using in situ aircraft measurements, together with a re decomposition method. Our analysis reveals that the cloud‐planetary boundary layer (PBL) coupling plays a pivotal role on the Na‐re relationship. Quantitative re decomposition indicates that the contrasting Na‐re relationships in two cloud‐PBL coupling regimes result from different balances of four distinct aspects. The widely recognized number effect may be outweighed by the joint effects of the remaining three that have been rarely investigated and largely ignored in Na‐re parameterizations.

The idea of cooling the Earth by marine cloud brightening is well established. All prior studies considered enhancing cloud albedo only with fine aerosols (FA). Adding coarse sea spray aerosols (CSA, radius>1 μm) has been thought to have the opposite effect. Using nearly a decade of satellite observations and global aerosol reanalysis, we found that the maximum radiative cooling effect from marine stratocumulus occurs when FA is around 3 μg m−3 and CSA is around 30 μg m−3. Under low winds and high stability conditions, optimal FA and CSA can enhance cooling by −95 W m−2, nearly 60% more than adding FA alone. This CRE response to FA and CSA was consistently observed across various cloud‐controlling factors, thus minimizing the probability of being caused by meteorological co‐variability. These findings improve our understanding of how different aerosols affect Earth's climate, improve the evaluation of cooling achieved through marine cloud brightening, and support its feasibility.

The new Energy Exascale Earth System Model Version 1 (E3SMv1) developed for the U.S. Department of Energy has significant new treatments of aerosols and light‐absorbing snow impurities as well as their interactions with clouds and radiation. This study describes seven sets of new aerosol‐related treatments (involving emissions, new particle formation, aerosol transport, wet scavenging and resuspension, and snow radiative transfer) and examines how they affect global aerosols and radiative forcing in E3SMv1. Altogether, they give a reduced total aerosol radiative forcing (−1.6 W/m2) and sensitivity in cloud liquid water to aerosols, but an increased sensitivity in cloud droplet size to aerosols. A new approach for H2SO4 production and loss largely reduces a low bias in small particles concentrations and leads to substantial increases in cloud condensation nuclei concentrations and cloud radiative cooling. Emitting secondary organic aerosol precursor gases from elevated sources increases the column burden of secondary organic aerosol, contributing substantially to global clear‐sky aerosol radiative cooling (−0.15 out of −0.5 W/m2). A new treatment of aerosol resuspension from evaporating precipitation, developed to remedy two shortcomings of the original treatment, produces a modest reduction in aerosols and cloud droplets; its impact depends strongly on the model physics and is much stronger in E3SM Version 0. New treatments of the mixing state and optical properties of snow impurities and snow grains introduce a positive present‐day shortwave radiative forcing (0.26 W/m2), but changes in aerosol transport and wet removal processes also affect the concentration and radiative forcing of light‐absorbing impurities in snow/ice. Plain Language Summary Aerosol and aerosol‐cloud interactions continue to be a major uncertainty in Earth system models, impeding their ability to reproduce the observed historical warming and to project changes in global climate and water cycle. The U.S. DOE Energy Exascale Earth System Model version 1 (E3SMv1), a state‐of‐the‐science Earth system model, was developed to use exascale computing to address the grand challenge of actionable predictions of variability and change in the Earth system critical to the energy sector. It has been publicly released with new treatments in many aspects, including substantial modifications to the physical treatments of aerosols in the atmosphere and light‐absorbing impurities in snow/ice, aimed at reducing some known biases or correcting model deficiencies in representing aerosols, their life cycle, and their impacts in various components of the Earth system. Compared to its predecessors (without the new treatments) and observations, E3SMv1 shows improvements in characterizing global distributions of aerosols and their radiative effects. We conduct sensitivity experiments to understand the impact of individual changes and provide guidance for future development of E3SM and other Earth system models. Key Points A description and assessment of new aerosol treatments in the Energy Exascale Earth System Model Version 1 (E3SMv1) is provided Contributions to the total aerosol‐related radiative forcing by individual new treatments and different processes are quantified Some of the new treatments are found to depend on model physics and require further improvement for E3SM or other Earth system models

Aerosols emitted from wildfires could significantly affect global climate through perturbing global radiation balance. In this study, the Community Earth System Model with prescribed daily fire aerosol emissions is used to investigate fire aerosols’ impacts on global climate with emphasis on the role of climate feedbacks. The total global fire aerosol radiative effect (RE) is estimated to be −0.78 ± 0.29 W m−2, which is mostly from shortwave RE due to aerosol–cloud interactions (REaci; −0.70 ± 0.20 W m−2). The associated global annual-mean surface air temperature (SAT) change ΔT is −0.64 ± 0.16 K with the largest reduction in the Arctic regions where the shortwave REaci is strong. Associated with the cooling, the Arctic sea ice is increased, which acts to reamplify the Arctic cooling through a positive ice-albedo feedback. The fast response (irrelevant to ΔT) tends to decrease surface latent heat flux into atmosphere in the tropics to balance strong atmospheric fire black carbon absorption, which reduces the precipitation in the tropical land regions (southern Africa and South America). The climate feedback processes (associated with ΔT) lead to a significant surface latent heat flux reduction over global ocean areas, which could explain most (~80%) of the global precipitation reduction. The precipitation significantly decreases in deep tropical regions (5°N) but increases in the Southern Hemisphere tropical ocean, which is associated with the southward shift of the intertropical convergence zone and the weakening of Southern Hemisphere Hadley cell. Such changes could partly compensate the interhemispheric temperature asymmetry induced by boreal forest fire aerosol indirect effects, through intensifying the cross-equator atmospheric heat transport.

Anthropogenic aerosols (AA) can affect cloud and precipitation through aerosol–radiation interaction (ARI) and aerosol–cloud interaction (ACI). Over the past few decades, anthropogenic aerosol emissions have exhibited remarkable changes in the magnitude and in spatial pattern. The most significant changes are the increased emissions over both South Asia and East Asia. In this study, the atmospheric component of a state-of-the-art climate model that includes eight species of tropospheric aerosols, coupled to a multi-level mixed-layer ocean model, has been used to investigate the impacts of Asian anthropogenic aerosol precursor emission changes from 1970s to 2000s on large scale circulation and precipitation in boreal summer over East Asia. Results reveal significant changes in circulation and clouds over East Asia and over the tropical and western North Pacific (WNP). Increased Asian AA emissions lead to anomalous cyclonic circulation over the Maritime continent (MC) and anomalous anticyclonic circulation over the WNP, resulting in anomalous moisture transport convergence over the MC and therefore increased precipitation. They also lead to anomalous moisture flux divergence over both the WNP and large land areas of East Asia, especially over northern China, and therefore decreased precipitation there. These large scale circulation anomalies over the adjacent oceans are related to aerosol change induced ocean feedbacks, predominantly through ACI. It is the slow responses over the adjacent oceans (e.g., SST changes) through coupled atmosphere–ocean interaction in pre-monsoon seasons and summer that shape the changes of the East Asian summer monsoon and local precipitation. The results in this study suggest that increased Asian AA emissions from 1970s to 2000s may have played an important role for the observed southward shift of the Pacific intertropical convergence zone and precipitation belt, weakening of East Asian summer monsoon and reduced precipitation over northern China in East Asia during the latter half of the twentieth century.