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Physical parameterizations in global atmospheric and ocean models typically include free parameters that are not theoretically or empirically constrained. New methods are required to determine the optimal parameter combinations for such models in an objective, exhaustive, yet computationally feasible manner. Here we propose to apply computationally inexpensive radial basis function (RBF) surrogate models to minimize a “cost,” or error, function of an atmospheric model or a physical parameterization. The RBF is iteratively updated as more input-output pairs are obtained during the optimization. The approach is used to optimize the eddy-diffusivity/mass-flux boundary-layer parameterization of the convective boundary-layer in a single-column model framework. The optimization based on surrogate models is able to identify parameter combinations that reduce the error of the untuned default setting by 41%. The probability to detect a low-error solution increases rapidly especially over the first tens of single-column model evaluations. In comparison, a quadratic polynomial model only yields an error reduction of 17% since (a) high-order parameter interactions are not accounted for and (b) the construction of the polynomial is not based on an iterative sampling approach. The RBF surrogate models achieve this 17% error reduction for 40% of the polynomial model's cost. Interestingly, one of the emerging optimal settings describes a pure mass flux parameterization without eddy-diffusivity component. A second optimal solution is characterized by a plume fractional area of 20–30% and an eddy-mixing time scale of ∼700 s.

Tropical anvil clouds play a large role in the Earth's radiation balance, but their effect on global warming is uncertain. The conventional paradigm for these clouds attributes their existence to the rapidly declining convective mass flux below the tropopause, which implies a large source of detraining cloudy air there. Here we test this paradigm by manipulating the sources and sinks of cloudy air in cloud-resolving simulations. We find that anvils form in our simulations because of the long lifetime of upper-tropospheric cloud condensates, not because of an enhanced source of cloudy air below the tropopause. We further show that cloud lifetimes are long in the cold upper troposphere because the saturation specific humidity is much smaller there than the condensed water loading of cloudy updrafts, which causes evaporative cloud decay to act very slowly. Our results highlight the need for novel cloud-fraction schemes that align with this decay-centric framework for anvil clouds.

The impact of an isolated mesoscale mountain on the diurnal cycle of moist convection and its spatial variation is investigated. Convection-resolving simulations of flow over 3D Gaussian-shaped mountains are performed for a conditionally unstable atmosphere under diurnal radiative forcing. The results show considerable spatial variability in terms of timing and amount of convective precipitation. This variability relates to different physical mechanisms responsible for convection initiation in different parts of the domain. During the late morning, the mass convergence from the radiatively driven diurnal upslope flow confronting the large-scale incident background flow triggers strong convective precipitation over the mountain lee slope. As a consequence, instabilities in the boundary layer are swept out by the emerging cold pool in the vicinity of the mountain, and some parts over the mountain near-field receive less rainfall than the far-field. Over the latter, an unperturbed boundary-layer growth allows for sporadic convective initiation. Still, secondary convection triggered over the leading edge of the cold pool spreads some precipitation over the downstream near-field. Detailed analysis of our control simulation provides further explanation of this frequently observed precipitation pattern over mountains and adjacent plains. Sensitivity experiments indicate a significant influence of the mountain height on the precipitation pattern over the domain.

Tropical deep convection over the ocean is found to grow preferentially from thermodynamically preconditioned regions of high specific humidity and, thus, high moist static energy. For this reason, rings of enhanced specific humidity at the leading edges of evaporatively driven cold pools have recently received considerable attention. The prevailing theory explains these rings by the water vapor source from the evaporation of rain drops below cloud base. Their origin is studied in this letter using large-eddy simulations of individual cumulus clouds that rise into a tropical atmosphere over ocean. It is demonstrated that - in contrast to this theory - water vapor rings are primarily explained by surface latent heat fluxes rather than by the evaporation of rain. This finding implies that conceptual models used in subgrid-scale parameterizations of deep convection should consider the formation of rings of increased specific humidity by the cold-pool-induced enhancement of surface fluxes.

The precipitation efficiency of cumulus congestus clouds is investigated with a new Lagrangian particle framework for large-eddy simulations. The framework is designed to track particles representative of individual water molecules. A Monte Carlo approach facilitates the transition of particles between the different water classes (e.g., vapor, rain, or graupel). With this framework, it is possible to reconstruct the pathways of water as it moves from vapor at a particular altitude to rain at the surface. By tracking water molecules through both physical and microphysical space, the precipitation efficiency can be studied in detail as a function of height. Large-eddy simulations of individual cumulus congestus clouds show that the clouds convert entrained vapor to surface precipitation with an efficiency of around 10%. About two-thirds of all vapor that enters the cloud does so by entrainment in the free troposphere, but free-tropospheric vapor accounts for only one-third to one-half of the surface rainfall, with the remaining surface rainfall originating as vapor entrained through the cloud base. The smaller efficiency with which that laterally entrained water is converted into surface precipitation results from the smaller efficiencies with which it condenses, forms precipitating hydrometeors, and reaches the surface.