Solar geoengineering may not prevent strong warming from direct effects of CO₂ on stratocumulus cloud cover

Discussions of countering global warming with solar geoengineering assume that warming owing to rising greenhouse-gas concentrations can be compensated by artificially reducing the amount of sunlight Earth absorbs. However, solar geoengineering may not be fail-safe to prevent global warming because CO₂ can directly affect cloud cover: It reduces cloud cover by modulating the longwave radiative cooling within the atmosphere. This effect is not mitigated by solar geoengineering. Here, we use idealized high-resolution simulations of clouds to show that, even under a sustained solar geoengineering scenario with initially only modest warming, subtropical stratocumulus clouds gradually thin and may eventually break up into scattered cumulus clouds, at concentrations exceeding 1,700 parts per million (ppm). Because stratocumulus clouds cover large swaths of subtropical oceans and cool Earth by reflecting incident sunlight, their loss would trigger strong (about 5 K) global warming. Thus, the results highlight that, at least in this extreme and idealized scenario, solar geoengineering may not suffice to counter greenhouse-gas-driven global warming

Arbitrarily high-order (weighted) essentially non-oscillatory finite difference schemes for anelastic flows on staggered meshes

We propose a WENO finite difference scheme to approximate anelastic flows, and scalars advected by them, on staggered grids. In contrast to existing WENO schemes on staggered grids, the proposed scheme is designed to be arbitrarily high-order accurate as it judiciously combines ENO interpolations of velocities with WENO reconstructions of spatial derivatives. A set of numerical experiments are presented to demonstrate the increase in accuracy and robustness with the proposed scheme, when compared to existing WENO schemes and state-of-the-art central finite difference schemes

Large-eddy simulation of subtropical cloud-topped boundary layers: 2. Cloud response to climate change

How subtropical marine boundary layer (MBL) clouds respond to warming is investigated using large‐eddy simulations (LES) of a wide range of warmer climates, with CO_2 concentrations elevated by factors 2–16. In LES coupled to a slab ocean with interactive sea surface temperatures (SST), the surface latent heat flux (LHF) is constrained by the surface energy balance and only strengthens modestly under warming. Consequently, the MBL in warmer climates is shallower than in corresponding fixed‐SST LES, in which LHF strengthens excessively and the MBL typically deepens. The inferred shortwave (SW) cloud feedback with a closed energy balance is weakly positive for cumulus clouds. It is more strongly positive for stratocumulus clouds, with a magnitude that increases with warming. Stratocumulus clouds generally break up above 6 K to 9 K warming, or above a four to eightfold increase in CO_2 concentrations. This occurs because the MBL mixing driven by cloud‐top longwave (LW) cooling weakens as the LW opacity of the free troposphere increases. The stratocumulus breakup triggers an abrupt and large SST increase and MBL deepening, which cannot occur in fixed‐SST experiments. SW cloud radiative effects generally weaken while the lower‐tropospheric stability increases under warming—the reverse of their empirical relation in the present climate. The MBL is deeper and stratocumulus persists into warmer climates if large‐scale subsidence decreases as the climate warms. The contrasts between experiments with interactive SST and fixed SST highlight the importance of a closed surface energy balance for obtaining realizable responses of MBL clouds to warming

Large-eddy simulation of subtropical cloud‐topped boundary layers: 1. A forcing framework with closed surface energy balance

Large‐eddy simulation (LES) of clouds has the potential to resolve a central question in climate dynamics, namely, how subtropical marine boundary layer (MBL) clouds respond to global warming. However, large‐scale processes need to be prescribed or represented parameterically in the limited‐area LES domains. It is important that the representation of large‐scale processes satisfies constraints such as a closed energy balance in a manner that is realizable under climate change. For example, LES with fixed sea surface temperatures usually do not close the surface energy balance, potentially leading to spurious surface fluxes and cloud responses to climate change. Here a framework of forcing LES of subtropical MBL clouds is presented that enforces a closed surface energy balance by coupling atmospheric LES to an ocean mixed layer with a sea surface temperature (SST) that depends on radiative fluxes and sensible and latent heat fluxes at the surface. A variety of subtropical MBL cloud regimes (stratocumulus, cumulus, and stratocumulus over cumulus) are simulated successfully within this framework. However, unlike in conventional frameworks with fixed SST, feedbacks between cloud cover and SST arise, which can lead to sudden transitions between cloud regimes (e.g., stratocumulus to cumulus) as forcing parameters are varied. The simulations validate this framework for studies of MBL clouds and establish its usefulness for studies of how the clouds respond to climate change

Statistically Steady State Large‐Eddy Simulations Forced by an Idealized GCM: 1. Forcing Framework and Simulation Characteristics

Using large‐eddy simulations (LES) systematically has the potential to inform parameterizations of subgrid‐scale processes in general circulation models (GCMs), such as turbulence, convection, and clouds. Here we show how LES can be run to simulate grid columns of GCMs to generate LES across a cross section of dynamical regimes. The LES setup approximately replicates the thermodynamic and water budgets in GCM grid columns. Resolved horizontal and vertical transports of heat and water and large‐scale pressure gradients from the GCM are prescribed as forcing in the LES. The LES are forced with prescribed surface temperatures, but atmospheric temperature and moisture are free to adjust, reducing the imprinting of GCM fields on the LES. In both the GCM and LES, radiative transfer is treated in a unified but idealized manner (semigray atmosphere without water vapor feedback or cloud radiative effects). We show that the LES in this setup reaches statistically steady states without nudging to thermodynamic GCM profiles. The steady states provide training data for developing GCM parameterizations. The same LES setup also provides a good basis for studying the cloud response to global warming

Seasonal cycle of idealized polar clouds: large eddy simulations driven by a GCM

The uncertainty in polar cloud feedbacks calls for process understanding of the cloud response to climate warming. As an initial step, we investigate the seasonal cycle of polar clouds in the current climate by adopting a novel modeling framework using large eddy simulations (LES), which explicitly resolve cloud dynamics. Resolved horizontal and vertical advection of heat and moisture from an idealized GCM are prescribed as forcing in the LES. The LES are also forced with prescribed sea ice thickness, but surface temperature, atmospheric temperature, and moisture evolve freely without nudging. A semigray radiative transfer scheme, without water vapor or cloud feedbacks, allows the GCM and LES to achieve closed energy budgets more easily than would be possible with more complex schemes; this allows the mean states in the two models to be consistently compared, without the added complications from interaction with more comprehensive radiation. We show that the LES closely follow the GCM seasonal cycle, and the seasonal cycle of low clouds in the LES resembles observations: maximum cloud liquid occurs in late summer and early autumn, and winter clouds are dominated by ice in the upper troposphere. Large-scale advection of moisture provides the main source of water vapor for the liquid clouds in summer, while a temperature advection peak in winter makes the atmosphere relatively dry and reduces cloud condensate. The framework we develop and employ can be used broadly for studying cloud processes and the response of polar clouds to climate warming

Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus clouds

Stratocumulus clouds are the most common type of boundary layer cloud; their radiative effects strongly modulate climate. Large eddy simulations (LES) of stratocumulus clouds often struggle to maintain fidelity to observations because of the sharp gradients occurring at the entrainment interfacial layer at the cloud top. The challenge posed to LES by stratocumulus clouds is evident in the wide range of solutions found in the LES intercomparison based on the DYCOMS-II field campaign, where simulated liquid water paths for identical initial and boundary conditions varied by a factor of nearly 12. Here we revisit the DYCOMS-II RF01 case and show that the wide range of previous LES results can be realized in a single LES code by varying only the numerical treatment of the equations of motion and the nature of subgrid-scale (SGS) closures. The simulations that maintain the greatest fidelity to DYCOMS-II observations are identified. The results show that using weighted essentially non-oscillatory (WENO) numerics for all resolved advective terms and no explicit SGS closure consistently produces the highest-fidelity simulations. This suggests that the numerical dissipation inherent in WENO schemes functions as a high-quality, implicit SGS closure for this stratocumulus case. Conversely, using oscillatory centered difference numerical schemes for momentum advection, WENO numerics for scalars, and explicitly modeled SGS fluxes consistently produces the lowest-fidelity simulations. We attribute this to the production of anomalously large SGS fluxes near the cloud tops through the interaction of numerical error in the momentum field with the scalar SGS model