Zhihong Tan

Shallowness of tropical low clouds as a predictor of climate models’ response to warming

How tropical low clouds change with climate remains the dominant source of uncertainty in global warming projections. An analysis of an ensemble of CMIP5 climate models reveals that a significant part of the spread in the models’ climate sensitivity can be accounted by differences in the climatological shallowness of tropical low clouds in weak-subsidence regimes: models with shallower low clouds in weak-subsidence regimes tend to have a higher climate sensitivity than models with deeper low clouds. The dynamical mechanisms responsible for the model differences are analyzed. Competing effects of parameterized boundary-layer turbulence and shallow convection are found to be essential. Boundary-layer turbulence and shallow convection are typically represented by distinct parameterization schemes in current models—parameterization schemes that often produce opposing effects on low clouds. Convective drying of the boundary layer tends to deepen low clouds and reduce the cloud fraction at the lowest levels; turbulent moistening tends to make low clouds more shallow but affects the low-cloud fraction less. The relative importance different models assign to these opposing mechanisms contributes to the spread of the climatological shallowness of low clouds and thus to the spread of low-cloud changes under global warming.

Large‐eddy simulation in an anelastic framework with closed water and entropy balances

A large-eddy simulation (LES) framework is developed for simulating the dynamics of clouds and boundary layers with closed water and entropy balances. The framework is based on the anelastic equations in a formulation that remains accurate for deep convection. As prognostic variables, it uses total water and entropy, which are conserved in adiabatic and reversible processes, including reversible phase changes of water. This has numerical advantages for modeling clouds, in which reversible phase changes of water occur frequently. The equations of motion are discretized using higher-order weighted essentially nonoscillatory (WENO) discretization schemes with strong stability preserving time stepping. Numerical tests demonstrate that the WENO schemes yield simulations superior to centered schemes, even when the WENO schemes are used at coarser resolution. The framework is implemented in a new LES code written in Python and Cython, which makes the code transparent and easy to use for a wide user group.

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

Abstract 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.

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.

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 CO2 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 CO2 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.

An Extended Eddy-Diffusivity Mass-Flux Scheme for Unified Representation of Subgrid-Scale Turbulence and Convection

Abstract Large‐scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid‐scale turbulence and convection—such as that they adjust instantaneously to changes in resolved‐scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary‐layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large‐scale models. Here we lay the theoretical foundations for an extended eddy‐diffusivity mass‐flux (EDMF) scheme that has explicit time‐dependence and memory of subgrid‐scale variables and is designed to represent all subgrid‐scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross‐sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large‐scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time‐dependent life cycle.