Shallow Cumulus Cloud Fields Are Optically Thicker When They Are More Clustered

Shallow trade cumuli over subtropical oceans are a persistent source of uncertainty in climate projections. Mesoscale organization of trade cumulus clouds has been shown to influence their cloud radiative effect (CRE) through cloud cover. We investigate whether organization can explain CRE variability independently of cloud cover variability. By analyzing satellite observations and high-resolution simulations, we show that increased clustering leads to geometrically thicker clouds with larger domain-averaged liquid water paths, smaller cloud droplets, and consequently, larger cloud optical depths. The relationships between these variables are shaped by the mixture of deep cloud cores and shallower interstitial clouds or anvils that characterize cloud organization. Eliminating cloud cover effects, more clustered clouds reflect up to 20 W/m$^2$ more instantaneous shortwave radiation back to space

Opportunistic experiments to constrain aerosol effective radiative forcing

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity 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 spatiotemporal 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 datasets 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

Opportunistic experiments to constrain aerosol effective radiative forcing

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity 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 spatiotemporal 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 datasets 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

Liquid water path steady states in stratocumulus : Insights from process-level emulation and mixed-layer theory

Stratocumulus clouds constitute one of the largest negative climate forcings in the global radiation budget. This forcing is determined, inter alia, by the cloud liquid water path (LWP), which we analyze using a combination of Gaussian process emulation and mixed-layer theory. For nocturnal, nonprecipitating stratocumuli, we show that LWP steady states constitute an equilibrium primarily between radiative cooling and entrainment warming and drying. These steady states are approached from lower LWPs due to reduced entrainment, while higher LWPs are depleted by stronger entrainment. An analytical solution for the LWP steady state reveals not only the environmental conditions in which a stratocumulus cloud can be maintained, but also distinct analytical properties of the entrainment velocity that are required for a stable LWP steady state that opposes perturbations. In particular, the results highlight the importance of an entrainment velocity that increases strictly monotonically with theLWPif stratocumuli are to attain a stableLWPsteady state. This is demonstrated through analysis of two commonly used mixed-layer entrainment parameterizations

Deconvolution of boundary layer depth and aerosol constraints on cloud water path in subtropical stratocumulus decks

The liquid water path (LWP) adjustment due to aerosol-cloud interactions in marine stratocumulus remains a considerable source of uncertainty for climate sensitivity estimates. An unequivocal attribution of LWP adjustments to changes in aerosol concentration from climatology remains difficult due to the considerable covariance between meteorological conditions alongside changes in aerosol concentrations. We utilise the susceptibility framework to quantify the potential change in LWP adjustment with boundary layer (BL) depth in subtropical marine stratocumulus. We show that the LWP susceptibility, i.e. the relative change in LWP scaled by the relative change in cloud droplet number concentration, in marine BLs triples in magnitude from -0.1 to -0.31 as the BL deepens from 300 to 1200 m and deeper. We further find deep BLs to be underrepresented in pollution tracks, process modelling, and in situ studies of aerosol-cloud interactions in marine stratocumulus. Susceptibility estimates based on these approaches are skewed towards shallow BLs of moderate LWP susceptibility. Therefore, extrapolating LWP susceptibility estimates from shallow BLs to the entire cloud climatology may underestimate the true LWP adjustment within subtropical stratocumulus and thus overestimate the effective aerosol radiative forcing in this region. Meanwhile, LWP susceptibility estimates in deep BLs remain poorly constrained. While susceptibility estimates in shallow BLs are found to be consistent with process modelling studies, they overestimate pollution track estimates

A comparison of two chemistry and aerosol schemes on the regional scale and the resulting impact on radiative properties and liquid- and ice-phase aerosol-cloud interactions

The complexity of atmospheric aerosol causes large uncertainties in its parameterization in atmospheric models. In a process-based comparison of two aerosol and chemistry schemes within the regional atmospheric modeling framework COSMO-ART (Consortium for Small-Scale Modelling, Aersosol and Reactive Trace gases extension), we identify key sensitivities of aerosol parameterizations. We consider the aerosol module MADE (Modal Aerosol Dynamics model for Europe) in combination with full gas-phase chemistry and the aerosol module M7 in combination with a constant-oxidant-field-based sulfur cycle. For a Saharan dust outbreak reaching Europe, modeled aerosol populations are more sensitive to structural differences between the schemes, in particular the consideration of aqueous-phase sulfate production, the selection of aerosol species and modes, and modal composition, than to parametric choices like modal standard deviation and the parameterization of aerosol dynamics. The same observation applies to aerosol optical depth (AOD) and the concentrations of cloud condensation nuclei (CCN). Differences in the concentrations of ice-nucleating particles (INPs) are masked by uncertainties between two ice-nucleation parameterizations and their coupling to the aerosol scheme. Differences in cloud droplet and ice crystal number concentrations are buffered by cloud microphysics as we show in a susceptibility analysis.ISSN:1680-7375ISSN:1680-736

A Modeling Study on the Sensitivities of Atmospheric Charge Separation According to the Relative Diffusional Growth Rate Theory to Nonspherical Hydrometeors and Cloud Microphysics

Collisional charge transfer between graupel and ice crystals in the presence of cloud droplets is considered the dominant mechanism for charge separation in thunderclouds. According to the relative diffusional growth rate (RDGR) theory, the hydrometeor with the faster diffusional radius growth is charged positively in such collisions. We explore sensitivities of the RDGR theory to nonspherical hydrometeors and six parameters (pressure, temperature, liquid water content, sizes of ice crystals, graupel, and cloud droplets). Idealized simulations of a thundercloud with two‐moment cloud microphysics provide a realistic sampling of the parameter space. Nonsphericity and anisotropic diffusional growth strongly control the extent of positive graupel charging. We suggest a tuning parameter to account for anisotropic effects not represented in bulk microphysics schemes. In a susceptibility analysis that uses automated differentiation, we identify ice crystal size as most important RDGR parameter, followed by graupel size. Simulated average ice crystal size varies with temperature due to ice multiplication and heterogeneous freezing of droplets. Cloud microphysics and ice crystal size thus indirectly determine the structure of charge reversal lines in the traditional temperature‐water‐content representation. Accounting for the variability of ice crystal size and potentially habit with temperature may help to explain laboratory results and seems crucial for RDGR parameterizations in numerical models. We find that the contribution of local water vapor from evaporating rime droplets to diffusional graupel growth is only important for high effective water content. In this regime, droplet size and pressure are the dominant RDGR parameters. Otherwise, the effect of local graupel growth is masked by small ice crystal sizes that result from ice multiplication.ISSN:0148-0227ISSN:2169-897