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The overarching goal of this postdoctoral project is: quantitatively assess and constrain the aerosol budgets in the remote North Atlantic marine boundary layer, under a wide range of aerosol emission sources, meteorological states to improve process-level understanding of marine aerosol-cloud interactions critical to adequately link observations and climate modelling.
Clouds developing in a polluted environment have more numerous, smaller cloud droplets that can increase the cloud lifetime and liquid water content. Such changes in the cloud droplet properties may suppress low precipitation allowing development of a stronger convection and higher freezing level. Delaying the washout of the cloud water (and aerosol), and the stronger convection will result in higher clouds with longer life time and larger anvils. We show these effects by using large statistics of the new, 1km resolution data from MODIS on the Terra satellite. We isolate the aerosol effects from meteorology by regression and showing that aerosol microphysical effects increases cloud fraction by average of 30 presents for all cloud types and increases convective cloud top pressure by average of 35mb. We analyze the aerosol cloud interaction separately for high pressure trade wind cloud systems and separately for deep convective cloud systems. The resultant aerosol radiative effect on climate for the high pressure cloud system is: -10 to -13 W/sq m at the top of the atmosphere (TOA) and -11 to -14 W/sq m at the surface. For deeper convective clouds the forcing is: -4 to -5 W/sq m at the TOA and -6 to -7 W/sq m at the surface.
A Perturbed Parameter Ensemble (PPE) with the Community Atmosphere Model version 6 (CAM6) is used to better understand the sensitivity of aerosol forcing and cloud feedbacks to changes in model processes. Aerosol forcing through aerosol-cloud interactions is mostly negative (a cooling) due to shortwave radiation, while feedbacks are positive or negative in different regions due to contrasting longwave and shortwave effects. Both forcing and feedbacks are related to the mean climate state. Higher magnitude cloud radiative effects generally mean larger magnitude net negative forcing and larger magnitude net positive feedback. Aerosol forcing is broadly related to the susceptibility of clouds to drop number. Feedbacks also related to susceptibility, but to a lesser extent and in different regions to aerosol forcing. Aerosol forcing and cloud feedbacks are anti-correlated in the CAM6 PPE such that stronger negative forcing is associated with stronger positive feedbacks. Even the processes governing forcing and feedback sensitivity in the PPE are similar. These include the warm rain formation process, ice loss processes and deep convective intensity.
Aerosol-cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of an adequate knowledge of the complex microphysical and radiative processes associated with the aerosol-cloud system. The situations when aerosols and clouds are found in the same atmospheric column, for instance, when light-absorbing aerosols such as biomass burning generated carbonaceous particles or wind-blown dust overlay low-level cloud decks, are commonly found over several regional of the world. Contrary to the cloud-free scenario over dark surface, for which aerosols are known to produce a net cooling effect (negative radiative forcing) on climate, the overlapping situation of absorbing aerosols over cloud can potentially exert a significant level of atmospheric absorption and produces a positive radiative forcing at top-of-atmosphere. The magnitude of direct radiative effects of aerosols above cloud depends directly on the aerosol loading, microphysical-optical properties of the aerosol layer and the underlying cloud deck, and geometric cloud fraction. We help in addressing this problem by introducing a novel product of optical depth of absorbing aerosols above clouds retrieved from near-UV observations made by the Ozone Monitoring Instrument (OMI) on board NASA's Aura platform. The presence of absorbing aerosols above cloud reduces the upwelling radiation reflected by cloud and produces a strong 'color ratio' effect in the near-UV region, which can be unambiguously detected in the OMI measurements. Physically based on this effect, the OMACA algorithm retrieves the optical depths of aerosols and clouds simultaneously under a prescribed state of atmosphere. The algorithm architecture and results from a ten-year global record including global climatology of frequency of occurrence and above-cloud aerosol optical depth, and a discussion on related future field campaigns are presented.
Aerosol distributions have a potentially large influence on climate-relevant cloud properties but can be difficult to observe over the Arctic given pervasive cloudiness, long polar nights, data paucity over remote regions, and periodic diamond dust events that satellites can misclassify as aerosol. We compared Arctic 2008–2015 mineral dust and combustion aerosol distributions from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis products, and the FLEXible PARTicle (FLEXPART) dispersion model. Based on coincident, seasonal Atmospheric Infrared Sounder (AIRS) Arctic satellite meteorological data, diamond dust may occur up to 60 % of the time in winter, but it hardly ever occurs in summer. In its absence, MERRA-2 and FLEXPART each predict the vertical and horizontal distribution of large-scale patterns in combustion aerosols with relatively high confidence (Kendall tau rank correlation > 0.6), although a sizable amount of variability is still unaccounted for. They do the same for dust, except in conditions conducive to diamond dust formation where CALIPSO is likely misclassifying diamond dust as mineral dust and near the surface (< ∼ 2 km) where FLEXPART may be overpredicting local dust emissions. Comparisons to ground data suggest that MERRA-2 Arctic dust concentrations can be improved by the addition of local dust sources. All three products predicted that wintertime dust and combustion aerosols occur most frequently over the same Siberian regions where diamond dust is most common in the winter. This suggests that dust aerosol impacts on ice phase processes may be particularly high over Siberia, although further wintertime model validation with non-CALIPSO observations is needed. This assessment paves the way for applying the model-based aerosol simulations to a range of regional-scale Arctic aerosol–cloud interaction studies with greater confidence.
NASA Langley recently developed the world's first airborne multi-wavelength high spectral resolution lidar (HSRL). This lidar employs the HSRL technique at 355 and 532 nm to make independent, unambiguous retrievals of aerosol extinction and backscatter. It also employs the standard backscatter technique at 1064 nm and is polarization-sensitive at all three wavelengths. This instrument, dubbed HSRL-2 (the secondgeneration HSRL developed by NASA Langley), is a prototype for the lidar on NASA's planned Aerosols- Clouds-Ecosystems (ACE) mission. HSRL-2 completed its first science mission in July 2012, the Two-Column Aerosol Project (TCAP) conducted by the Department of Energy (DOE) in Hyannis, MA. TCAP presents an excellent opportunity to assess some of the remote sensing concepts planned for ACE: HSRL-2 was deployed on the Langley King Air aircraft with another ACE-relevant instrument, the NASA GISS Research Scanning Polarimeter (RSP), and flights were closely coordinated with the DOE's Gulfstream-1 aircraft, which deployed a variety of in situ aerosol and trace gas instruments and the new Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR). The DOE also deployed their Atmospheric Radiation Measurement Mobile Facility and their Mobile Aerosol Observing System at a ground site located on the northeastern coast of Cape Cod for this mission. In this presentation we focus on the capabilities, data products, and applications of the new HSRL-2 instrument. Data products include aerosol extinction, backscatter, depolarization, and optical depth; aerosol type identification; mixed layer depth; and rangeresolved aerosol microphysical parameters (e.g., effective radius, index of refraction, single scatter albedo, and concentration). Applications include radiative closure studies, studies of aerosol direct and indirect effects, investigations of aerosol-cloud interactions, assessment of chemical transport models, air quality studies, present (e.g., CALIPSO) and future (e.g., EarthCARE) satellite calibration/validation, and development/assessment of advanced retrieval techniques for future satellite applications (e.g., lidar+polarimeter retrievals of aerosol and cloud properties). We will also discuss the relevance of HSRL-2 measurement capabilities to the ACE remote sensing concept.
Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of ten- uous aerosols. We conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.
Southern Ocean (SO) low-level clouds remain a challenge for Earth system models to represent accurately. This project utilized DOE ARM observations and the Community Atmosphere Model (CAM) to improve process-level understanding of aerosol-cloud interactions and cloud microphysics for SO mixed-phase clouds. Specifically, our efforts include two main topics: 1) investigate the SO aerosol, cloud condensation nuclei (CCN), and ice nucleating particle (INP) population based on observations and determine predictive skill of simulating SO INPs, and 2) assess the ice formation pathways, including ice nucleation and secondary ice production, in SO mixed phase clouds utilizing a combination of observations and modeling tools. Studies focused on SO aerosol and INP resulted four manuscripts. Ice formation pathways in SO mixed phase clouds were investigated, revealing observed evidence of SIP active across all mixed phase temperatures. However, a key finding of this project is that despite significant progress in predicting SO INPs, the role of INP variability in SO cloud phase, precipitation, and radiative properties remain unknown due to challenges in microphysics parameterizations.
By modulating the Earth-atmosphere energy, hydrological and biogeochemical cycles, and affecting regional-to-global weather and climate, biomass burning is recognized as one of the major factors affecting the global carbon cycle. However, few comprehensive and wide-ranging experiments have been conducted to characterize biomass-burning pollutants in Southeast Asia (SEA) or assess their regional impact on meteorology, the hydrological cycle, the radiative budget, or climate change. Recently, BASEASIA (Biomass-burning Aerosols in South-East Asia: Smoke Impact Assessment) and the 7-SEAS (7- South-East Asian Studies) Dongsha Experiment were conducted during the spring seasons of 2006 and 2010 in northern SEA, respectively, to characterize the chemical, physical, and radiative properties of biomass-burning emissions near the source regions, and assess their effects. This paper provides an overview of results from these two campaigns and related studies collected in this special issue, entitled Observation, modeling and impact studies of biomass burning and pollution in the SE Asian Environment. This volume includes 28 papers, which provide a synopsis of the experiments, regional weatherclimate, chemical characterization of biomass-burning aerosols and related pollutants in source and sink regions, the spatial distribution of air toxics (atmospheric mercury and dioxins) in source and remote areas, a characterization of aerosol physical, optical, and radiative properties, as well as modeling and impact studies. These studies, taken together, provide the first relatively complete dataset of aerosol chemistry and physical observations conducted in the sourcesink region in the northern SEA, with particular emphasis on the marine boundary layer and lower free troposphere (LFT). The data, analysis and modeling included in these papers advance our present knowledge of source characterization of biomass-burning pollutants near the source regions as well as the physical and chemical processes along transport pathways. In addition, we raise key questions to be addressed by a coming deployment during springtime 2013 in northern SEA, named 7-SEASBASELInE (Biomass-burning Aerosols Stratocumulus Environment: Lifecycles and Interactions Experiment). This campaign will include a synergistic approach for further exploring many key atmospheric processes (e.g., complex aerosol-cloud interactions) and impacts of biomass burning on the surface-atmosphere energy budgets during the lifecycles of biomass burning emissions.
Sea salt aerosol (SSaer) significantly impacts aerosol-radiation and aerosol-cloud interactions, and sublimated blowing snow is hypothesized to be an important SSaer source in polar regions. Understanding blowing snow and other wind-sourced aerosols’ climate relevant properties is needed, especially during winter when Arctic amplification is greatest. However, most of our understanding of blowing snow SSaer comes from modeling studies, and direct observations are sparse. Additionally, SSaer can originate from multiple sources, making it difficult to disentangle emission processes. Here, we present comprehensive observations of wind-sourced aerosol during blowing snow events from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic. High wind speed strongly enhances total aerosol number, submicron sodium chloride mass, cloud condensation nuclei concentrations, and scattering coefficients. Generally, the relative response of aerosol properties to wind speed enhancement is strongest in fall when Arctic aerosol concentrations are lowest. Blowing snow events showed similar aerosol and environmental properties across events, apart from occasions with high snow age (>6 days since last snowfall). Coarse-mode number concentrations (>1 μm) are better explained by variability in wind speed averaged over 12-h air mass back trajectories arriving at the MOSAiC site compared to local, instantaneous wind speed, suggesting the importance of regional transport and consideration of air mass history for wind-driven aerosol production. These MOSAiC observations provide new insights into wind-driven aerosol in the central Arctic and may help validate modeling studies and improve model parameterizations particularly for aerosol direct and indirect radiative forcing.
Aerosols, or atmospheric particulates, are long known to be able to seed clouds and modify their characteristics (e.g., cloud brightness, coverage, lifetime). However, the impact of aerosols on clouds is highly complex and non-linear. As a result, aerosol-cloud interaction remains the largest uncertainty in our understanding of the Earth’s radiative balance and in any future climate projections. Aerosols are also a principal component of air pollution and are known to adversely affect respiratory and cardiovascular health.
Atmospheric aerosols and their impact on cloud properties remain the largest uncertainty in the human forcing of the climate system. By increasing the concentration of cloud droplets (Nd), aerosols reduce droplet size and increase the reflectivity of clouds (a negative radiative forcing). Central to this climate impact is the susceptibility of cloud droplet number to aerosol (β), the diversity of which explains much of the variation in the radiative forcing from aerosol–cloud interactions (RFaci) in global climate models. This has made measuring β a key target for developing observational constraints of the aerosol forcing.
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.
Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.
Initial droplet spectra produced upon activation impact the ensuing chain of microphysical processes andtherefore play a crucial role in cloud evolution. This work re-examines dependencies of newly formed clouddroplet size distribution (CDSD) characteristics on environmental and aerosol properties via parcel model simulationsthat serve as the basis for a multi-moment bulk microphysics droplet activation scheme suitable for acloud-resolving model (CRM). It is found that applying a fixed size threshold to define activated droplets versusemploying physical considerations can lead to erroneous activation and overly broad CDSDs for high aerosolconcentration and weak updraft conditions. Aerosol distributions characterized by larger median sizes and/orincreased solubility can result in greater activated droplet numbers, whereas impacts of these parameters onCDSD spectral width depend on both aerosol number concentration and updraft velocity. An expansion of theactivation scheme to include CDSD spectral width is proposed to aid efforts to extend high-order momentprediction to cloud droplet categories in CRMs as well as better represent variability in the activation process onthe cloud scale.simulations to investigate the regime dependence of the relative dispersion(d)1 of newly activated CDSDs, where d is the ratio of dropletradius standard deviation (σ) to the mean radius (r ). C16 demonstratedthat increasing Na resulted in increasing (decreasing) d values via reducedcondensational narrowing (spectral broadening) rates within theAL (UL) regime, with d values peaking in the TR regime. Their findingssuggest a similar regime dependence for d as R09 noted for Nc and helpexplain reportedly conflicting relationships between Na and CDSDspectral characteristics (cf. Hudson and Noble, 2014; Liu et al., 2014),although the applicability of these results within bulk microphysicalschemes was not addressed.Simulating aerosol-cloud interactions with CRMs employing bulkmicrophysics requires that the scheme minimally predict two CDSDparameters, namely mass and number concentrations, and represent thedroplet activation process. Various activation schemes aim to determineNc from aerosol and environmental properties and include analyticalexpressions (e.g., Abdul-Razzak et al., 1998; Morrison et al., 2005) aswell as lookup tables (LUTs) based on detailed parcel model calculations(e.g., Saleeby and Cotton, 2004, hereafter SC04; Segal and Khain,2006; Thompson and Eidhammer, 2014). Expressions to diagnose CDSDspectral width from Nc (Grabowski, 1998; Liu et al., 2006; Morrison andGrabowski, 2007) or cloud water content (Geoffroy et al., 2010) havealso been developed, although more robust methods to obtain CDSDspectral width upon activation are presently lacking. This latter point isrelevant for triple-moment (3 M) bulk microphysics that aim to predictdistribution spectral width alongside number and mass concentrations(e.g., Loftus et al., 2014; Milbrandt and Yau, 2005).The current work extends the findings of C16 to the current LUTbasedaerosol activation scheme used in the Regional AtmosphericModeling System (RAMS) (Cotton et al., 2003; SC04; Saleeby and vanden Heever, 2013, hereafter SvdH13) and additionally examinesaerosol size and solubility impacts on newly activated CDSD properties.Because early cloud development processes such as condensationalgrowth, evaporation, and droplet self-collection depend on and impactCDSD spectral width (Hudson and Yum, 1997; Seifert and Beheng 2001;Lu and Seinfeld, 2006; Igel and van den Heever, 2017), an expansion ofthe activation LUTs to include CDSD spectral width is proposed as apreliminary step for extending 3M prediction to CDSDs in CRMs forimproved simulations of aerosol-cloud interactions.2. MethodologyThe current RAMS two-moment microphysics module determinesthe fractional number of aerosol particles that activate to cloud dropletsfrom five-dimensional LUTs based on model predicted air temperature(T), w, Na, and the geometric median radius (rg) and soluble fraction (ε)of the aerosol size distribution (SvdH13). These LUTs are created offlineusing a one-dimensional Lagrangian adiabatic parcel model (Feingoldand Heymsfield, 1992; Heymsfield and Sabin, 1989; SC04) to simulateexplicit droplet activation and initial CDSD growth for a range of ambientatmospheric conditions [T, w] and binned lognormal aerosol sizedistributions given by= ⎡⎣ ⎢− ⎤⎦ ⎥N r Nr π σr rσ( )2 lnexp[ln( / )]2(ln )aggg22 (1)where r is the dry aerosol particle bin radius and σg is the geometricstandard deviation of the distribution. As the parcel model simulationsfocus on the activation process, other processes such as coalescence,sedimentation, and mixing are not considered. Details of the parcelmodel can be found in SC04 and SvdH13, and only a brief description isprovided here. At the onset of parcel model calculations, the initiallydry aerosol particles in all bins first deliquesce and reach theirequilibrium diameters in a sub-saturated environment based on theKöhler equation for solution droplets. The parcel is then lifted at a fixedupward velocity w, and particle growth by vapor diffusion, along withconcurrent changes in the ambient environment, are iteratively computedusing the Variable-coefficient Ordinary Differential Equation(VODE) solver (Brown et al., 1989). The time resolution of these calculationsis determined within the VODE solver, and the frequency atwhich the solver is called is controlled by a longer model time stepbased on fixed upward parcel displacement increments (Δz) at thespecified w (Δt=Δz/w). Model calculations proceed until the parcelreaches a height 50m beyond the level of maximum saturation ratio(Smax) or total parcel displacement exceeds 2 km. Upon model termination,Smax and the fractional number of aerosols (factv) resulting innewly formed cloud droplets, defined as particles having diameters of atleast 2 μm, are cataloged in the LUTs according to the specified T, w, Na,rg, and ε parameter values.A critical point regarding the creation of these LUTs is the use of afixed minimum diameter (Dmin) to define cloud droplets in the parcelmodel, which can produce erroneous CDSD characteristics, particularlywithin the UL regime. For aerosol distributions with large rg valuesunder low SS conditions, for example, deliquesced aerosols within thelarge tail of the distribution can exceed 2 μm in diameter yet remainunactivated as ‘haze’ particles (Levin and Cotton, 2009; McFigganset al., 2006). For this study, aerosol particles activate to cloud dropletsbased on the critical diameter Dcrit as a function of parcel supersaturationratio (Sr) as in R09:D = σ MS RTρ83 ln( ) critsol wr w (2)where σsol is the surface tension of a solution droplet, Mw and ρw are themolar mass and density of liquid water, respectively, and R is theuniversal gas constant. Additionally, at relatively large w values withinthe AL regime, Nc stabilizes shortly after reaching supersaturation.However, parcel ascent and condensational growth continue beyondthe level of Smax, potentially causing additional narrowing of the CDSD.In the current work, model calculations terminate upon reaching Smaxas changes in Nc are negligible with continued ascent (Peng et al., 2007;R09).Parcel model simulations are performed to examine the sensitivitiesof CDSD characteristics to w, Na, rg, and ε, with the ranges for theseparameters listed in Table 1. Aerosols are assumed to be a mix of solubleand insoluble material of equal density, specified by ε, where fullysoluble aerosols correspond to ammonium sulfate with hygroscopicityparameter κ=0.61 (Petters and Kreidenweis, 2007). FollowingSvdH13, aerosol geometric standard deviation is fixed at σg=1.8, andaerosol distributions (Eq. 1) are partitioned into 100 logarithmicallyspacedbins spanning a size range specific to each rg value. For all simulations,Δz=1 m, and initial values of relative humidity, air temperatureand pressure are set to RH=0.99, T=10 °C and p=900 hPa,respectively.
Aerosol forcing uncertainty represents the largest climate forcing uncertainty overall. Its magnitude has remained virtually undiminished over the past 20 years despite considerable advances in understanding most of the key contributing elements. Recent work has produced modest increases only in the confidence of the uncertainty estimate itself. This review summarizes the contributions toward reducing the uncertainty in the aerosol forcing of climate made by satellite observations, measurements taken within the atmosphere, as well as modeling and data assimilation. We adopt a more measurement-oriented perspective than most reviews of the subject in assessing the strengths and limitations of each; gaps and possible ways to fill them are considered. Currently planned programs supporting advanced, global-scale satellite and surface-based aerosol, cloud, and precursor gas observations, climate modeling, and intensive field campaigns aimed at characterizing the underlying physical and chemical processes involved, are all essential. But in addition, new efforts are needed: (a) to obtain systematic aircraft in situ measurements capturing the multi-variate probability distribution functions of particle optical, microphysical, and chemical properties (and associated uncertainty estimates), as well as co-variability with meteorology, for the major aerosol airmass types; (b) to conceive, develop, and implement a suborbital (aircraft plus surface-based) program aimed at systematically quantifying the cloud-scale microphysics, cloud optical properties, and cloud-related vertical velocities associated with aerosol-cloud interactions; and (c) to focus much more research on integrating the unique contributions of satellite observations, suborbital measurements, and modeling, to reduce the persistent uncertainty in aerosol climate forcing.
Aerosol-cloud interactions (ACI) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The non-linearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well defined sources provide ‘opportunistic experiments’ (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatio-temporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors.We review the different experimental conditions and conduct a synthesis of the available satellite data sets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.
Aerosol effective radiative forcing critically influences climate projections but remains poorly constrained. Using the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) v1 configuration, we assess the sensitivity of the radiative forcing due to anthropogenic aerosol changes using a simplified prescribed aerosol scheme (SPA) derived from E3SM v3. Nudged simulations at 3 and 12 km horizontal grid spacings reveal a more negative aerosol forcing than the reference 100 km E3SM v3 whence the SPA properties are derived. The resulting globally averaged aerosol forcing signal is largely due to aerosol–cloud interactions and exhibits little overall resolution sensitivity, while hints of resolution sensitivity appear regionally between the 3 and 12 km runs. While the default SPA scheme overestimates cloud droplet dependence on aerosols, parameterization adjustments in the activation process reconcile forcing estimates with the reference model. Our results demonstrate the ability to use a prescribed aerosol scheme to hold aerosol forcing to a desired strength across resolutions.