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Large-eddy simulation (LES) is often used as a benchmark simulation in climate science and is suggested as a fundamental tool to examine, e.g., marine cloud brightening. Therefore, it is necessary to critically evaluate if these high-resolution models can skillfully simulate expected physical phenomena. This study focuses on the first indirect aerosol effect in warm stratocumulus clouds. We investigate if an LES code with explicit aerosol-cloud interactions and a widely used two-moment bulk microphysical scheme can reproduce well-known cloud droplet number susceptibility regimes previously identified by observations and supported by detailed parcel model simulations—the updraft-limited regime (typically occurring at high aerosol number concentrations and low updraft speeds) and the aerosol-limited regime (typically occurring at low aerosol number concentrations and high updraft speeds). Our simulations show that the LES in its default configuration cannot reproduce the two regimes if the initial droplet radius of newly activated droplets (rid) is estimated by integrating the wet aerosol size distribution. The main reason is related to the relatively coarse (but commonly used) time step in the model (Δt ≈ 1s), which is too long to resolve relevant microphysical processes adequately at high aerosol concentrations. A regime transition does occur if the timestep is decreased to Δt ≈ 0.1s and if a renormalization procedure is applied, which limits the number of activated droplets so that the water mass of the newly activated droplets cannot exceed the available amount of supersaturated water vapor. Another way to obtain a regime transition is to increase rid to values >1 µm. However, a clear recommendation for the choice of rid cannot be made upon physical arguments. An alternative solution could be to introduce a sub-time-stepping or adaptive time-stepping algorithm to calculate droplet formation and growth, particularly for updraft-limited conditions. Our study highlights the importance of critically evaluating LES results to guarantee that relevant physical processes are properly represented.

The Italian Po Valley is one of the most polluted regions in Europe. During winter, meteorological conditions favor long and dense fogs, which strongly affect visibility and human health. In spring, the frequency of nighttime fogs reduces while daytime new particle formation events become more common. This transition is likely caused by a reduction in particulate matter (PM2.5), leading to a decrease in the relevant condensation sink. The physics and chemistry of fog and aerosol have been studied at the San Pietro Capofiume site since the 1980s, but the detailed processes driving the observed trends are not fully understood. Hence, during winter and spring 2021/22, the Fog and Aerosol Interaction Research Italy (FAIRARI) campaign was carried out, using a wide spectrum of approaches, including in situ measurements, outdoor chamber experiments, and remote sensing. Atmospheric constituents and their properties were measured ranging from gas molecules and molecular clusters to fog droplets. One unique aspect of this study is the direct measurement of the aerosol composition inside and outside of fog, showing a slightly greater dominance of organic compounds in the interstitial compared to the droplet phase. Satellite observations of fog provided a spatial context and agreed well with in situ measurements of droplet size. They were complemented with in situ chamber experiments, providing insights into oxidative processes and revealing a large secondary organic aerosol-forming potential of ambient air upon chemical aging. The oxidative potential of aerosol and fog water inferred the impact of aerosol–fog interactions on particle toxicity. SIGNIFICANCE STATEMENT: Aerosol and fog influence our climate and can have adverse effects on human health and visibility. Through anthropogenic emissions, such as from industry or transport, humans can influence the physical and chemical properties of fog and aerosol. The FAIRARI campaign investigated the formation of aerosols and aerosol–fog interactions in the Italian Po Valley, one of the most polluted regions in Europe. State-of-the-art experimental methods revealed the details of aerosols and fogs from the molecular level to the droplet scale. We observed a clear transition from winter to spring, with fog-dominated periods followed by an intensified secondary aerosol formation period. Organic and nitrate compounds dominated the composition of aerosol and fog residuals. The results will contribute to various aerosol–fog interaction modeling activities. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs), unlike other lines of evidence, indicate that anthropogenic aerosols cause a global-mean increase in cloud liquid water path (L) and thus a negative adjustment to radiative forcing of the climate by aerosol–cloud interactions. In part 1 of this series of papers, we showed that this is true even in models that reproduce the negative correlation observed in present-day internal variability in L and cloud droplet number concentration (Nd). We studied several possible confounding mechanisms that could explain the noncausal cloud–aerosol correlations in GCMs and that possibly contaminate observational estimates of radiative adjustments. Here, we perform single-column and full-atmosphere GCM experiments to investigate the causal model-physics mechanisms underlying the model radiative adjustment estimate. We find that both aerosol–cloud interaction mechanisms thought to be operating in real clouds – precipitation suppression and entrainment evaporation enhancement – are active in GCMs and behave qualitatively in agreement with physical process understanding. However, the modeled entrainment enhancement has a negligible global-mean effect. This raises the question of whether the GCM estimate is incorrect due to parametric or base-state representation errors or whether the process understanding gleaned from a limited set of canonical cloud cases is insufficiently representative of the diversity of clouds in the real climate. Regardless, even at limited resolution, the GCM physics appears able to parameterize the small-scale microphysics–turbulence interplay responsible for the entrainment enhancement mechanism. We suggest ways to resolve tension between current and future (storm-resolving) global modeling systems and other lines of evidence in synthesis climate projections. [ABSTRACT FROM AUTHOR]

Heterogeneous radiative forcing in mid-latitudes, such as that exerted by aerosols, has been found to affect the Arctic climate, though the mechanisms remain debated. In this study, we leverage deep learning (DL) techniques to explore the complex response of the Arctic climate system to local radiative forcing over Europe. We conducted sensitivity experiments using the Max Planck Institute Earth System Model (MPI-ESM1.2) coupled with atmosphere–ocean–land-surface components. Large-scale circulation patterns can mediate the impact of the forcing on Arctic climate dynamics. We employed a DL-based clustering approach to classify large-scale atmospheric circulation patterns. To enhance the analysis of how these patterns impact the Arctic climate, the poleward moist static energy transport (PMSET) associated with the atmospheric circulation patterns was incorporated as an additional similarity metric in the clustering process. Furthermore, we developed a novel method to analyze the circulation patterns' contributions to various climatic parameter anomalies. Our findings indicate that the negative radiative forcing over Europe alters existing circulation patterns and their occurrence frequency without introducing new ones. Specifically, our analysis revealed that while the regional radiative forcing alters the occurrence frequencies of the circulation patterns, these changes are not the primary drivers of the forcing's impact on the Arctic parameters. Instead, it is the shifts in the mean spatial characteristics of the atmospheric circulation patterns, induced by the forcing, that predominantly determine the effects on the Arctic climate. Our methodology facilitates the uncovering of complex, nonlinear interactions within the climate system, capturing nuances that are often obscured in broader seasonal anomaly analyses. This approach enables a deeper understanding of the dynamics driving observed climatic anomalies and their links to specific atmospheric circulation patterns. [ABSTRACT FROM AUTHOR]

General circulation models' (GCMs) estimates of the liquid water path adjustment to anthropogenic aerosol emissions differ in sign from other lines of evidence. This reduces confidence in estimates of the effective radiative forcing of the climate by aerosol–cloud interactions (ERFaci). The discrepancy is thought to stem in part from GCMs' inability to represent the turbulence–microphysics interactions in cloud-top entrainment, a mechanism that leads to a reduction in liquid water in response to an anthropogenic increase in aerosols. In the real atmosphere, enhanced cloud-top entrainment is thought to be the dominant adjustment mechanism for liquid water path, weakening the overall ERFaci. We show that the latest generation of GCMs includes models that produce a negative correlation between the present-day cloud droplet number and liquid water path, a key piece of observational evidence supporting liquid water path reduction by anthropogenic aerosols and one that earlier-generation GCMs could not reproduce. However, even in GCMs with this negative correlation, the increase in anthropogenic aerosols from preindustrial to present-day values still leads to an increase in the simulated liquid water path due to the parameterized precipitation suppression mechanism. This adds to the evidence that correlations in the present-day climate are not necessarily causal. We investigate sources of confounding to explain the noncausal correlation between liquid water path and droplet number. These results are a reminder that assessments of climate parameters based on multiple lines of evidence must carefully consider the complementary strengths of different lines when the lines disagree. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs), unlike other lines of evidence, indicate that anthropogenic aerosols cause a global-mean increase in cloud liquid water path (퓛), and thus a negative adjustment to radiative forcing of the climate by aerosol–cloud interactions. In part 1 of this manuscript series, we showed that this is true even in models that reproduce the negative correlation observed in present-day internal variability of 퓛 and cloud droplet number concentration (Nd). We studied several possible confounding mechanisms that could explain the noncausal cloud–aerosol correlations in GCMs and that possibly contaminate observational estimates of radiative adjustments. Here, we perform single-column and full-atmosphere GCM experiments to investigate the causal model-physics mechanisms underlying the model radiative adjustment estimate. We find that both aerosol–cloud interaction mechanisms thought to be operating in real clouds – precipitation suppression and entrainment evaporation enhancement – are active in GCMs and behave qualitatively in agreement with physical process understanding. However, the modeled entrainment enhancement has a negligible global-mean effect. This raises the question whether the GCM estimate is incorrect due to parametric or base-state representation errors, or whether the process understanding gleaned from a limited set of canonical cloud cases is insufficiently representative of the diversity of clouds in the real climate. Regardless, even at limited resolution, the GCM physics appears able to parameterize the small-scale microphysics–turbulence interplay responsible for the entrainment enhancement mechanism. We suggest ways to resolve tension between current and future (storm-resolving) global modeling systems and other lines of evidence in synthesis climate projections. [ABSTRACT FROM AUTHOR]

Heterogeneous radiative forcing in mid-latitudes, such as that exerted by aerosols, has been found to affect the Arctic climate, though the mechanisms remain debated. In this study, we leverage Deep Learning (DL) techniques to explore the complex response of the Arctic climate system to local radiative forcing over Europe. We conducted sensitivity experiments using the Max Planck Institute Earth System Model (MPI-ESM1.2) coupled with atmosphere-ocean–land surface components. Utilizing a DL-based clustering method, we classify atmospheric circulation patterns in a lower-dimensional space, focusing on Poleward Moist Static Energy Transport (PMSET) as our primary parameter. We developed a novel method to analyze the circulation patterns' contributions to various climatic parameter anomalies. Our findings indicate that the negative forcing over Europe alters existing circulation patterns and their occurrence frequency without introducing new ones. Specifically, we identify changes in a circulation pattern with a high-pressure system over Scandinavia as a key driver for reduced Sea Ice Concentration (SIC) in the Barents-Kara Sea during autumn. This circulation pattern also influences middle atmospheric dynamics, although its contribution is relatively minor compared to other circulation patterns that resemble the phases of the North Atlantic Oscillation (NAO). Our multidimensional approach combines DL algorithms and human expertise to offer a novel analytical tool that could have broader applications in climate science. [ABSTRACT FROM AUTHOR]

Using the method of offline radiative transfer modelling within the partial radiative perturbations (PRP) approach, the effective radiative forcing (ERF) by aerosol-cloud interactions (ACI) in the ECHAM-HAMMOZ aerosol climate model is decomposed into a radiative forcing by anthropogenic cloud droplet number change and adjustments of the liquid water path and cloud fraction. The simulated radiative forcing and liquid water path adjustment are of approximately equal magnitude at -0.52Wm-2 and -0.53Wm-2, respectively, while the cloud fraction adjustment is somewhat weaker at -0.31Wm-2 (constituting 38%, 39%, and 23% of the total ERFaci, respectively); geographically, all three ERF components in the simulation peak over China, the subtropical eastern ocean boundaries, the northern Atlantic and Pacific Ocean, Europe, and eastern North America (in order of prominence). Spatial correlations indicate that the temporal-mean liquid water path adjustment is proportional to the temporal-mean radiative forcing, while the relationship between cloud fraction adjustment and radiative forcing is less direct. While the estimate of warm-cloud ACI is relatively insensitive to the treatment of ice and mixed-phase cloud overlying warm cloud, there are indications that more restrictive treatments of ice in the column result in a low bias in the estimated magnitude of the liquid water path adjustment and a high bias in the estimated magnitude of the droplet number forcing. Since the present work is the first PRP decomposition of the aerosol ERF into RFaci and fast cloud adjustments, idealized experiments are conducted to provide evidence that the PRP results are accurate. The experiments show that using low-frequency (daily or monthly) time-averaged model output of the cloud property fields underestimates the ERF, but 3-hourly mean output is sufficiently frequent. [ABSTRACT FROM AUTHOR]

The impact of aerosols on cloud properties is one of the largest uncertainties in the anthropogenic radiative forcing of the climate. In recent years, significant progress has been made in constraining this forcing using observations, but uncertainty still remains, particularly in the adjustments of cloud properties to aerosol perturbations. Cloud liquid water path (LWP) is the leading control on liquid-cloud albedo, making it important to observationally constrain the aerosol impact LWP. Previous modelling and observational studies have shown that multiple processes play a role in determining the LWP response to aerosol perturbations, but that the aerosol effect can be difficult to isolate. Following previous studies using mediating variables, this work investigates use of the relationship between cloud droplet number concentration (Nd) and LWP for constraining the role of aerosols. Using joint probability histograms to account for the non-linear relationship, this work finds a relationship that is broadly consistent with previous studies. There is significant geographical variation in the relationship, partly due to role of meteorological factors (particularly relative humidity) in the relationship. However, the Nd-LWP relationship is negative in the majority of regions, suggesting that aerosol induced LWP reductions could offset a significant fraction of the radiative forcing from aerosol-cloud interactions (RFaci). However, variations in the Nd-LWP relationship in response to volcanic and shipping aerosol perturbations indicate that the Nd-LWP relationship overestimates the Nd impact on LWP. As such, the estimate of LWP changes due to aerosol in this work provides an upper bound to the radiative forcing from aerosol-induced changes in the LWP. [ABSTRACT FROM AUTHOR]

Radiation management (RM) has been recognized as one of the climate engineering (CE) interventions to miti- gate the global warming. Here we investigated the feasibility of CE at a local scale in space and time (Limited-area climate engineering, LCE) with the presumption that cloud modification is technically possible and is suitable for local mitigation, using a climate model (MPI-ESM). RM is implemented locally in the climate model by the brightening of low-level clouds (solar radiation management, SRM) and thinning or dissipation of cirrus (terrestrial radiation management, TRM) to a period of 30 years (1850 - 1879). It resulted in a net local radiative forcing of -12.26 Wm−2 and a local cooling of -0.91K, with residual changes in some regions outside the target area. Surface temperature (SAT) extremes (90th and 10th percentile) show negative anomalies in the experimental region, as expected. However, substantial climate impacts are also simulated outside the target area. As a prominent example, the lower percentile of the SAT demonstrates an Arctic warming. This warming is found to be due to an anomalous intrusion of warm mid-latitude air mass to higher latitude by the weakening of westerly due to enhanced local cooling through LCE. Further, pronounced precipitation is also noticeable across the globe, especially in the eastern Pacific, which is associated with the intensity of the local LCE cooling. The dominant extreme cooling episode leads to the equatorial wind convergence and warming in the central Pacific which enhances the convection, thus the precipitation. [ABSTRACT FROM AUTHOR]