Explore the vast range of titles available.

How clouds respond to anthropogenic sulfate aerosols is one of the largest sources of uncertainty in the radiative forcing of climate over the industrial era. This uncertainty limits our ability to predict equilibrium climate sensitivity (ECS)—the equilibrium global warming following a doubling of atmospheric CO₂. Here, we use satellite observations to quantify relationships between sulfate aerosols and low-level clouds while carefully controlling for meteorology.We then combine the relationships with estimates of the change in sulfate concentration since about 1850 to constrain the associated radiative forcing. We estimate that the cloud-mediated radiative forcing from anthropogenic sulfate aerosols is −1.11 ± 0.43 W m−2 over the global ocean (95% confidence). This constraint implies that ECS is likely between 2.9 and 4.5 K (66% confidence). Our results indicate that aerosol forcing is less uncertain and ECS is probably larger than the ranges proposed by recent climate assessments.

The change in planetary albedo due to aerosol–cloud interactions during the industrial era is the leading source of uncertainty in inferring Earth’s climate sensitivity to increased greenhouse gases from the historical record. The variable that controls aerosol–cloud interactions in warm clouds is droplet number concentration. Global climate models demonstrate that the present-day hemispheric contrast in cloud droplet number concentration between the pristine Southern Hemisphere and the polluted Northern Hemisphere oceans can be used as a proxy for anthropogenically driven change in cloud droplet number concentration. Remotely sensed estimates constrain this change in droplet number concentration to be between 8 cm−3 and 24 cm−3. By extension, the radiative forcing since 1850 from aerosol–cloud interactions is constrained to be −1.2 W·m−2 to −0.6 W·m−2. The robustness of this constraint depends upon the assumption that pristine Southern Ocean droplet number concentration is a suitable proxy for preindustrial concentrations. Droplet number concentrations calculated from satellite data over the Southern Ocean are high in austral summer. Near Antarctica, they reach values typical of Northern Hemisphere polluted outflows. These concentrations are found to agree with several in situ datasets. In contrast, climate models show systematic underpredictions of cloud droplet number concentration across the Southern Ocean. Near Antarctica, where precipitation sinks of aerosol are small, the underestimation by climate models is particularly large. This motivates the need for detailed process studies of aerosol production and aerosol–cloud interactions in pristine environments. The hemispheric difference in satellite estimated cloud droplet number concentration implies preindustrial aerosol concentrations were higher than estimated by most models.

A supervised neural network algorithm is used to categorize near‐global satellite retrievals into three mesoscale cellular convective (MCC) cloud morphology patterns. At constant cloud amount, morphology patterns differ in brightness associated with the amount of optically thin cloud features. Environmentally driven transitions from closed MCC to other morphology patterns, typically accompanied by more optically thin cloud features, are used as a framework to quantify the morphology contribution to the optical depth component of the shortwave cloud feedback. A marine heat wave is used as an out‐of‐sample test of closed MCC occurrence predictions. Morphology shifts in optical depth between 65°S and 65°N under projected environmental changes (i.e., from an abrupt quadrupling of CO2) assuming constant cloud cover contributes between 0.04 and 0.07 W m−2 K−1 (aggregate of 0.06) to the global mean cloud feedback. Plain Language Summary Marine boundary layer clouds are essential to the energy balance of Earth, reflecting sunlight back to space and covering a large percentage of the globe. These clouds can organize into open, closed, and disorganized cellular structures. Cloud morphology patterns differ in their ability to reflect sunlight back to space. Closed cellular clouds transition to open and disorganized clouds associated with changes in environmental factors (i.e., sea surface temperature and the stability of the lower atmosphere). This study examines how a shift in cloud morphology with climate change will change the amount of sunlight reflected back to space: a shortwave cloud feedback. We predict the frequency of occurrence of closed cellular clouds based on changes in environmental factors estimated from global climate model simulations under climate change scenarios. An observed marine heat wave is used to test occurrence predictions. The change in reflected sunlight due to the shift between morphology types at fixed fractional cloud cover produces a global feedback that ranges between 0.04 and 0.07 W m−2 K−1. Key Points Mesoscale cloud morphology albedo varies with fraction of optically thin cloud features Closed mesoscale cellular convection occurrence changes are predictable from environmental controls Environmentally driven cloud morphology changes in optical depth produce a shortwave feedback of 0.04–0.07 W m−2 K−1

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.

Marine low clouds play an important role in the climate system, and their properties are sensitive to cloud condensation nuclei concentrations. While new particle formation represents a major source of cloud condensation nuclei globally, the prevailing view is that new particle formation rarely occurs in remote marine boundary layer over open oceans. Here we present evidence of the regular and frequent occurrence of new particle formation in the upper part of remote marine boundary layer following cold front passages. The new particle formation is facilitated by a combination of efficient removal of existing particles by precipitation, cold air temperatures, vertical transport of reactive gases from the ocean surface, and high actinic fluxes in a broken cloud field. The newly formed particles subsequently grow and contribute substantially to cloud condensation nuclei in the remote marine boundary layer and thereby impact marine low clouds. Globally, new particle formation represents a major source of cloud condensation nuclei. Here, the authors present evidence of frequent occurrence of new particle formation in the upper part of remote marine boundary layer following cold front passages.

Low, marine clouds cool the Earth system, reflecting sunlight back to space. Low cloud response to environmental change is a key uncertainty in future climate projections. It is especially uncertain how much warming amplification will occur due to tropical cumulus feedback. A potentially important feedback modulator is the ability for cumulus to cluster through mesoscale circulations. Janssens et al. (2025, ) demonstrate that moisture convergence in ascending circulation branches organizes clouds into fewer and brighter structures while moisture divergence dries descending branches, reducing cloud and increasing longwave cooling. These offsetting effects result in a small net radiative effect due to organization. Janssens et al. (2025, )'s results imply that the influence of organization on cumulus feedback is insignificant. The proposed offsetting of radiative effects across mesoscale organization patterns, or “symmetry,” is worthy of continued research. Observational support and further investigations into whether cumulus organization has other climate impacts is encouraged.

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 H2SO4, SO2, and DMS as prognostic variables to capture basic influences of sulfur chemistry on the model aerosols. Nucleation of H2SO4 aerosol particles from gas‐phase H2SO4 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. Plain Language Summary Aerosols can have large effects on low‐level oceanic clouds, and cloud processes strongly affect aerosols as well. Both aerosols and clouds are a major source of uncertainty in climate projections. A standard tool for studying low altitude ocean clouds and their interactions with aerosols is large‐eddy‐simulation (LES), but this tool can be very computationally expensive when aerosols of many different sizes are included, which can restrict the geographic coverage, the model resolution, and the time extent of model simulations. We present a new numerical framework for LES that allows treatment of two size categories of aerosols and their interactions with clouds in a relatively simple and inexpensive manner. We use this framework and perform a wide range of numerical simulations where aerosol number, properties, and physics are varied in a 10‐day simulation of low clouds in a small region over the Southeast Pacific Ocean. Our simulations show that small aerosols can have large effects on low cloud survival in some circumstances. Key Points A simple two‐mode aerosol scheme allows exploration of Aitken effects on aerosol and cloud evolution Aitken aerosols supplement the accumulation mode and can prevent boundary‐layer collapse in some cases Scavenging of unactivated aerosol particles by cloud droplets has a strong effect on aerosol evolution

Classifications of mesoscale cellular convection (MCC) for marine boundary layer clouds are produced using a supervised neural network algorithm applied to MODIS daytime liquid water path data. The classifier, used in prior studies, distinguishes closed, open, and cellular but disorganized MCC. This work uses trajectories in four eastern subtropical ocean basins to compare meteorological variables and the structures of boundary layers for trajectories that begin as closed cells but evolve into either open cells or disorganized cells or remain closed cells over one afternoon–afternoon cycle. Results show contrasts between the trajectory sets: Trajectories for MCC that remain closed cells are more frequently observed nearer coasts, whereas trajectories that break into open and disorganized cells begin farther offshore. The frequency at which closed cells transition to open cells is seasonally invariant. The fraction of trajectories that stay as closed MCC varies throughout the year in opposition to those that break into disorganized cells, so that their annual cycles are 180° out of phase. Trajectories remain as closed cell more frequently in austral spring and boreal summer when the trade inversion is stronger. The closed–disorganized MCC breakup is associated with weaker subsidence, a weaker inversion, a drier free troposphere, and enhanced nighttime boundary layer deepening, consistent with a warming–drying mechanism. The closed–open transition occurs in meteorological conditions similar to closed–closed trajectories. However, prior to the transition, the closed–open trajectories exhibit stronger surface winds and lower cloud droplet concentrations and rain more heavily overnight. Results suggest that multiple, independent mechanisms drive changes in cloud amount and morphology.

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.

This study uses cloud and radiative properties collected from in situ and remote sensing instruments during two coordinated campaigns over the Southern Ocean between Tasmania and Antarctica in January–February 2018 to evaluate the simulations of clouds and precipitation in nudged‐meteorology simulations with the CAM6 and AM4 global climate models sampled at the times and locations of the observations. Fifteen SOCRATES research flights sampled cloud water content, cloud droplet number concentration, and particle size distributions in mixed‐phase boundary layer clouds at temperatures down to −25°C. The 6‐week CAPRICORN2 research cruise encountered all cloud regimes across the region. Data from vertically pointing 94 GHz radars deployed was compared with radar simulator output from both models. Satellite data were compared with simulated top‐of‐atmosphere (TOA) radiative fluxes. Both models simulate observed cloud properties fairly well within the variability of observations. Cloud base and top in both models are generally biased low. CAM6 overestimates cloud occurrence and optical thickness while cloud droplet number concentrations are biased low, leading to excessive TOA reflected shortwave radiation. In general, low clouds in CAM6 precipitate at the same frequency but are more homogeneous compared to observations. Deep clouds are better simulated but produce snow too frequently. AM4 underestimates cloud occurrence but overestimates cloud optical thickness even more than CAM6, causing excessive outgoing longwave radiation fluxes but comparable reflected shortwave radiation. AM4 cloud droplet number concentrations match observations better than CAM6. Precipitating low and deep clouds in AM4 have too little snow. Further investigation of these microphysical biases is needed for both models. Key Points CAM6 and AM4 simulate observed cloud properties and compositions fairly well within the variability of observations CAM6 clouds are “too frequent, too bright”; AM4 clouds are “too few, too bright” Cloud droplet number concentration in CAM6 is typically too low; AM4 clouds include too much small ice and too little snow