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Turbulent clouds are challenging to model and simulate due to uncertainties in microphysical processes occurring at unresolved subgrid scales (SGS). These processes include the transport of cloud particles, supersaturation fluctuations, turbulent mixing, and the resulting stochastic droplet activation and growth by condensation. In this work, we apply two different Lagrangian stochastic schemes to model SGS cloud microphysics. Collision and coalescence of droplets are not considered. Cloud droplets and unactivated cloud condensation nuclei (CCN) are described by Lagrangian particles (superdroplets). The first microphysical scheme directly models the supersaturation fluctuations experienced by each Lagrangian superdroplet as it moves with the air flow. Supersaturation fluctuations are driven by turbulent fluctuations of the droplet vertical velocity through the adiabatic cooling/warming effect. The second, more elaborate scheme uses both temperature and vapor mixing ratio as stochastic attributes attached to each superdroplet. It is based on the probability density function formalism that provides a consistent Eulerian-Lagrangian formulation of scalar transport in a turbulent flow. Both stochastic microphysical schemes are tested in a synthetic turbulent-like cloud flow that mimics a stratocumulus topped boundary layer. It is shown that SGS turbulence plays a key role in broadening the droplet-size distribution towards larger sizes. Also, the feedback on water vapor of stochastically activated droplets buffers the variations of the mean supersaturation driven the resolved transport. This extends the distance over which entrained CNN are activated inside the cloud layer and produces multimodal droplet-size distributions.

Large-eddy simulation is used to investigate the effects of cold pools driven by rain evaporation on the shallow-to-deep convection transition over land. The physically consistent methodologies are developed to obtain a time-dependent reference ensemble without cold pools and to apply interactive surface heat fluxes without modeling of surface energy and water budgets. Three different simulation ensembles are contrasted. The reference ensemble, in the spirit of one-dimensional single-column models, eliminates cold pools by horizontally homogenizing negative buoyancy production due to rain evaporation. The additional ensembles complement the reference cold-pool-free ensemble by including cold pools and by applying either interactive or prescribed surface fluxes. Contrasting these ensembles suggests possible improvements of convection parameterization in large-scale models of weather and climate. Without cold pools, the reference ensemble preserves key features of buoyancy-driven cellular convection associated with a field of convective plumes, as assumed in a typical convection parameterization. With cold pools, a significant enhancement of surface heat and moisture fluxes and about an hour delay of their daily maximum is simulated. Cold pools enhance near-surface temperature and moisture standard deviations as well as maxima of the near-surface updraft velocity. They also lead to the reduction of cloud lateral entrainment, deeper vertical development of the cloud layer, and a few-times-larger accumulated surface precipitation. Interactive surface fluxes provide a damping mechanism that noticeably suppresses all these effects. Perhaps surprisingly, cold pools do not significantly change the cloud-base convective mass flux that approximately follows the evolution of surface heat fluxes.

Influence of pollution on dynamics of deep convection continues to be a controversial topic. Arguably, only carefully designed numerical simulations can clearly separate the impact of aerosols from the effects of meteorological factors that affect moist convection. This paper argues that such a separation is virtually impossible using observations because of the insufficient accuracy of atmospheric measurements and the fundamental nature of the interaction between deep convection and its environment. To support this conjecture, results from numerical simulations are presented that apply modeling methodology previously developed by the author. The simulations consider small modifications, difficult to detect in observations, of the initial sounding, surface fluxes, and large-scale forcing tendencies. All these represent variations of meteorological conditions that affect deep convective dynamics independently of aerosols. The setup follows the case of daytime convective development over land based on observations during the Large-Scale Biosphere–Atmosphere (LBA) field project in Amazonia. The simulated observable macroscopic changes of convection, such as the surface precipitation and upper-tropospheric cloudiness, are similar to or larger than those resulting from changes of cloud condensation nuclei from pristine to polluted conditions studied previously using the same modeling case. Observations from Phase III of the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE) are also used to support the argument concerning the impact of the large-scale forcing. The simulations suggest that the aerosol impacts on dynamics of deep convection cannot be isolated from meteorological effects, at least for the daytime development of unorganized deep convection considered in this study.

This paper discusses the effects of cloud turbulence, turbulent entrainment, and entrained cloud condensation nuclei (CCN) activation on the evolution of the cloud droplet size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events modeled as a random process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet activation and growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate, CCN concentration, and the mean fraction of environmental air entrained in an event are all specified as independent external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. These are either unactivated CCN or cloud droplets that grow from activated CCN. The model accounts for the addition of environmental CCN into the cloud by entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using the classical linear relaxation to the mean model. We show that turbulence plays an important role in aiding entrained CCN to activate, and thus broadening the droplet size distribution. These findings are consistent with previous large-eddy simulations (LESs) that consider the impact of variable droplet growth histories on the droplet size spectra in small cumuli. The scheme developed in this work is ready to be used as a stochastic subgrid-scale scheme in LESs of natural clouds.

Thermodynamic soundings for pre-monsoon and monsoon seasons from the Indian subcontinent are analysed to document differences between convective environments. The pre-monsoon environment features more variability for both near-surface moisture and free-tropospheric temperature and moisture profiles. As a result, the level of neutral buoyancy (LNB) and pseudo-adiabatic convective available potential energy (CAPE) vary more for the pre-monsoon environment. Pre-monsoon soundings also feature higher lifting condensation levels (LCLs). LCL heights are shown to depend on the availability of surface moisture, with low LCLs corresponding to high surface humidity, arguably because of the availability of soil moisture. A simple theoretical argument is developed and showed to mimic the observed relationship between LCLs and surface moisture. We argue that the key element is the partitioning of surface energy flux into its sensible and latent components, that is, the surface Bowen ratio, and the way the Bowen ratio affects surface buoyancy flux. We support our argument with observations of changes in the Bowen ratio and LCL height around the monsoon onset, and with idealized simulations of cloud fields driven by surface heat fluxes with different Bowen ratios.

We report the development of a novel Lagrangian microphysics methodology for simulations of warm ice-free clouds. The approach applies the traditional Eulerian method for the momentum and continuous thermodynamic fields such as the temperature and water vapor mixing ratio, and uses Lagrangian super-droplets to represent condensed phase such as cloud droplets and drizzle or rain drops. In other applications of the Lagrangian warm-rain microphysics, the super-droplets outside clouds represent unactivated cloud condensation nuclei (CCN) that become activated upon entering a cloud and can further grow through diffusional and collisional processes. The original methodology allows for the detailed study of not only effects of CCN on cloud microphysics and dynamics, but also CCN processing by a cloud. However, when cloud processing is not of interest, a simpler and computationally more efficient approach can be used with super-droplets forming only when CCN is activated and no super-droplet existing outside a cloud. This is possible by applying the Twomey activation scheme where the local supersaturation dictates the concentration of cloud droplets that need to be present inside a cloudy volume, as typically used in Eulerian bin microphysics schemes. Since a cloud volume is a small fraction of the computational domain volume, the Twomey super-droplets provide significant computational advantage when compared to the original super-droplet methodology. Additional advantage comes from significantly longer time steps that can be used when modeling of CCN deliquescence is avoided. Moreover, other formulation of the droplet activation can be applied in case of low vertical resolution of the host model, for instance, linking the concentration of activated cloud droplets to the local updraft speed. This paper discusses the development and testing of the Twomey super-droplet methodology, focusing on the activation and diffusional growth. Details of the activation implementation, transport of super-droplets in the physical space, and the coupling between super-droplets and the Eulerian temperature and water vapor field are discussed in detail. Some of these are relevant to the original super-droplet methodology as well and to the ice phase modeling using the Lagrangian approach. As a computational example, the scheme is applied to an idealized moist thermal rising in a stratified environment, with the original super-droplet methodology providing a benchmark to which the new scheme is compared.

The squall-line event on 20 May 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) Model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the preconvection environment at 1200 UTC in Morris, Oklahoma, show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study shows that different bin microphysics schemes, designed to be conceptually more realistic and thus arguably more accurate than bulk microphysics schemes, still simulate a wide spread of microphysical, thermodynamic, and dynamic characteristics of a squall line, qualitatively similar to the spread of squall-line characteristics using various bulk schemes. Future work may focus on improving the representation of ice particle properties in bin schemes to reduce this uncertainty and using the similar assumptions for all schemes to isolate the impact of physics from numerics.

A direct numerical simulation (DNS) with the decaying turbulence setup has been carried out to study cloud-edge mixing and its impact on the droplet size distribution (DSD) applying thermodynamic conditions observed in monsoon convective clouds over Indian subcontinent during the Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX). Evaporation at the cloud-edges initiates mixing at small scale and gradually introduces larger-scale fluctuations of the temperature, moisture, and vertical velocity due to droplet evaporation. Our focus is on early evolution of simulated fields that show intriguing similarities to the CAIPEEX cloud observations. A strong dilution at the cloud edge, accompanied by significant spatial variations of the droplet concentration, mean radius, and spectral width, are found in both the DNS and in observations. In DNS, fluctuations of the mean radius and spectral width come from the impact of small-scale turbulence on the motion and evaporation of inertial droplets. These fluctuations decrease with the increase of the volume over which DNS data are averaged, as one might expect. In cloud observations, these fluctuations also come from other processes, such as entrainment/mixing below the observation level, secondary CCN activation, or variations of CCN activation at the cloud base. Despite large differences in the spatial and temporal scales, the mixing diagram often used in entrainment/mixing studies with aircraft data is remarkably similar for both DNS and cloud observations. We argue that the similarity questions applicability of heuristic ideas based on mixing between two air parcels (that the mixing diagram is designed to properly represent) to the evolution of microphysical properties during turbulent mixing between a cloud and its environment.

Nature photonics 14(6), 391 - 397 (2020). doi:10.1038/s41566-020-0607-z, The European XFEL is a hard X-ray free-electron laser (FEL) based on a high-electron-energy superconducting linear accelerator. The superconducting technology allows for the acceleration of many electron bunches within one radio-frequency pulse of the accelerating voltage and, in turn, for the generation of a large number of hard X-ray pulses. We report on the performance of the European XFEL accelerator with up to 5,000 electron bunches per second and demonstrating a full energy of 17.5 GeV. Feedback mechanisms enable stabilization of the electron beam delivery at the FEL undulator in space and time. The measured FEL gain curve at 9.3 keV is in good agreement with predictions for saturated FEL radiation. Hard X-ray lasing was achieved between 7 keV and 14 keV with pulse energies of up to 2.0 mJ. Using the high repetition rate, an FEL beam with 6 W average power was created., Published by Nature Publ. Group, London [u.a.]

The suggested impact of pollution on deep convection dynamics, referred to as the convective invigoration, is investigated in simulations applying microphysical piggybacking and a comprehensive double-moment bulk microphysics scheme. The setup follows the case of daytime convective development over land based on observations during the Large-Scale Biosphere–Atmosphere (LBA) experiment in Amazonia. In contrast to previous simulations with single-moment microphysics schemes and in agreement with results from bin microphysics simulations by others, the impact of pollution simulated by the double-moment scheme is large for the upper-tropospheric convective anvils that feature higher cloud fractions in polluted conditions. The increase comes from purely microphysical considerations: namely, the increased cloud droplet concentrations in polluted conditions leading to the increased ice crystal concentrations and, consequently, smaller fall velocities and longer residence times. There is no impact on convective dynamics above the freezing level and thus no convective invigoration. Polluted deep convective clouds precipitate about 10% more than their pristine counterparts. The small enhancement comes from smaller supersaturations below the freezing level and higher buoyancies inside polluted convective updrafts with velocities between 5 and 10 m s−1. The simulated supersaturations are large, up to several percent in both pristine and polluted conditions, and they call into question results from deep convection simulations applying microphysical schemes with saturation adjustment. Sensitivity simulations show that the maximum supersaturations and the upper-tropospheric anvil cloud fractions strongly depend on the details of small cloud condensation nuclei (CCN) that can be activated in strong updrafts above the cloud base.

As a complement to measurements, numerical modeling facilitates improved understanding of the complex turbulent processes in the stratocumulus-topped boundary layer (STBL). Due to limited computational resources simulations are often run at too coarse resolutions to resolve details of cloud-top turbulence and potentially in computational domains too small to account for the largest scales of boundary layer circulations. The effects of such deficiencies are not fully understood. Here the influence of resolution/anisotropy of the computational grid and domain size in under-resolved implicit large-eddy simulation of the STBL is investigated. The performed simulations are based on data from the first research flight of the DYCOMS-II campaign. Regarding cloud cover and domain-averaged liquid water path, simulations with horizontal/vertical grid spacing of 35/5 m, 70/10 m, and 105/15 m are found to agree better with measurements than more computationally expensive simulations with isotropic grid boxes, e.g., with 10/10 m or 15/15 m grid spacing. While decreasing the vertical grid spacing allows more representative simulation of the thin, turbulent, stably stratified interfacial layer between the STBL and the free troposphere, coarsening the horizontal resolution dampens vertical velocity fluctuations in this region and mimics the observed anisotropy of stably stratified small-scale turbulence near the cloud top. The size of the computational domain is found to have almost no impact on mean cloud properties. However, increasing it from 3.5×3.5 km2 to 14×14 km2 does lead to the occurrence of larger coherent updraft structures. Increasing it further to 21×21 km2 shows little or no increase in the updraft size.

A new approach for analyzing multiscale properties of the atmospheric flow is proposed in this study. For that, the recently introduced isentropic streamfunctions are employed here for scale decomposition with Haar wavelets. This method is applied subsequently to a cloud-resolving simulation of a planetary Walker cell characterized by pronounced multiscale flow. The resulting set of isentropic streamfunctions—obtained at the convective, meso-, synoptic, and planetary scales—capture many important features of the across-scale interactions within an idealized Walker circulation. The convective scale is associated with the shallow, congestus, and deep clouds, which jointly dominate the upward mass flux in the lower troposphere. The synoptic and planetary scales play important roles in extending mass transport to the upper troposphere, where the corresponding streamfunctions mainly capture the first baroclinic mode associated with large-scale overturning circulation. The intermediate-scale features of the flow, such as anvil clouds associated with organized convective systems, are extracted with the mesoscale and synoptic-scale isentropic streamfunctions. Multiscale isentropic streamfunctions are also used to extract salient mechanisms that underlie the low-frequency variability of the Walker cell. In particular, the lag of a few days of the planetary scale behind the convective scale indicates the importance of the convective scale in moistening the atmosphere and strengthening the planetary-scale overturning circulation. Furthermore, the mesoscale and synoptic scale lags behind the planetary scale reflect the strong dependence of convective organization on the background shear.

In this study, we examine the diurnal cycle of rainfall over New Guinea using a series of convection-permitting numerical simulations with the Weather Research and Forecasting (WRF) model. We focus our simulations on a period of suppressed regional-scale conditions (February 2010) during which local diurnal forcings are maximised. Additionally, we focus our study on the occurrence and dynamics of offshore-propagating convective systems that contribute to the observed early-morning rainfall maximum north-east of New Guinea.In general, modelled diurnal precipitation shows good agreement with satellite-observed rainfall, albeit with some timing and intensity differences. The simulations also reproduce the occurrence and variability of overnight convection that propagate offshore as organised squall lines north-east of New Guinea. The occurrence of these offshore systems is largely controlled by background conditions. Days with offshore-propagating convection have more middle tropospheric moisture, larger convective available potential energy, and greater low-level moisture convergence. Convection has similar characteristics over the terrain on days with and without offshore propagation.The offshore-propagating convection manifests via a multi-stage evolutionary process. First, scattered convection over land, which is remnant of the daytime maximum, moves towards the coast and becomes reorganised near the region of coastal convergence associated with the land breeze. The convection then moves offshore in the form of a squall line at ∼ 5 ms−1. In addition, cool anomalies associated with gravity waves generated by precipitating land convection propagate offshore at a dry hydrostatic gravity wave speed (of ∼ 15 ms−1) and act to destabilise the coastal/offshore environment prior to the arrival of the squall line. Although the gravity wave does not appear to initiate the convection or control its propagation, it should contribute to its longevity and maintenance. The results highlight the importance of terrain and coastal effects along with gravity waves in contributing to the diurnal cycle over the Maritime Continent, especially the offshore precipitation maxima adjacent to quasi-linear coastlines.

Two schemes for modeling condensation in warm nonprecipitating clouds are compared. The first one is the efficient bulk condensation scheme where cloudy volumes are always at saturation and cloud water evaporates instantaneously to maintain saturation. The second one is the comprehensive bin condensation scheme that predicts the evolution of the cloud droplet spectrum and allows sub- and supersaturations in cloudy volumes. The emphasis is on the impact of the two schemes on cloud dynamics. Theoretical considerations show that the bulk condensation scheme provides more buoyancy than the bin scheme, but the effect is small, with the potential density temperature difference around 0.1 K for 1% supersaturation. The 1D advection–condensation tests document the high-vertical-resolution requirement for the bin scheme to resolve the cloud-base supersaturation maximum and CCN activation, which is difficult to employ in 3D cloud simulations. Simulations of shallow convection cloud fields are executed applying bulk and bin schemes, with the mean droplet concentrations in the bin scheme covering a wide range, from about 5 to over 4000 cm−3. Simulations employ the microphysical piggybacking methodology to extract impacts with high confidence. They show that the differences in cloud fields simulated with bulk and bin schemes come not from small differences in the condensation but from more significant differences in the evaporation of cloud water near cloud edges as a result of entrainment and mixing with the environment. The latter makes the impact of cloud microphysics on simulated macroscopic cloud field properties even more difficult to assess because of highly uncertain subgrid-scale parameterizations.

Moist anelastic and compressible numerical solutions to the planetary baroclinic instability and climate benchmarks are compared. The solutions are obtained by applying a consistent numerical framework for discrete integrations of the various nonhydrostatic flow equations. Moist extension of the baroclinic instability benchmark is formulated as an analog of the dry case. Flow patterns, surface vertical vorticity and pressure, total kinetic energy, power spectra, and total amount of condensed water are analyzed. The climate benchmark extends the baroclinic instability study by addressing long-term statistics of an idealized planetary equilibrium and associated meridional transports. Short-term deterministic anelastic and compressible solutions differ significantly. In particular, anelastic baroclinic eddies propagate faster and develop slower owing to, respectively, modified dispersion relation and abbreviated baroclinic vorticity production. These eddies also carry less kinetic energy, and the onset of their rapid growth occurs later than for the compressible solutions. The observed differences between the two solutions are sensitive to initial conditions as they diminish for large-amplitude excitations of the instability. In particular, on the climatic time scales, the anelastic and compressible solutions evince similar zonally averaged flow patterns with the matching meridional transports of entropy, momentum, and moisture.

Microphysical piggybacking applied previously in shallow convection simulations is employed to highlight microphysical impacts on deep convection. The main idea is to apply two sets of thermodynamic variables, one coupled to the dynamics and driving the simulation and the second one piggybacking the simulation: that is, responding to the simulated flow but not affecting it. The two sets can be driven either by different microphysical schemes or by the same scheme with different scheme parameters. For illustration, two single-moment bulk microphysical schemes are implemented, one with a simple representation of ice processes and the second one with a more comprehensive approach. Each scheme is applied assuming contrasting cloud droplet concentrations, pristine versus polluted, with simulations mimicking dynamical effects of pollution on deep convection. The modeling setup follows the case of daytime convective development over land based on observations during the Large-Scale Biosphere–Atmosphere (LBA) experiment in Amazonia. Microphysical piggybacking with small ensembles of simulations allows for separating dynamical and microphysical impacts on deep convection with high confidence and enables extracting small differences in the surface precipitation, cloud cover, and liquid and ice water paths with unprecedented accuracy. It also shows that the cloud buoyancy above the freezing level is only weakly affected by contrasting cloud droplet concentrations. The latter casts doubt on the convective invigoration hypothesis for the case of unorganized deep convection considered in this study, at least when investigated with a single-moment microphysical scheme.

This paper discusses the sparse space–time superparameterization (SSTSP) algorithm and evaluates its ability to represent interactions between moist convection and the large-scale circulation in the context of a Walker cell flow over a planetary scale two-dimensional domain. The SSTSP represents convective motions in each column of the large-scale model by embedding a cloud-resolving model, and relies on a sparse sampling in both space and time to reduce computational cost of explicit simulation of convective processes. Simulations are performed varying the spatial compression and/or temporal acceleration, and results are compared to the cloud-resolving simulation reported previously. The algorithm is able to reproduce a broad range of circulation features for all temporal accelerations and spatial compressions, but significant biases are identified. Precipitation tends to be too intense and too localized over warm waters when compared to the cloud-resolving simulations. It is argued that this is because coherent propagation of organized convective systems from one large-scale model column to another is difficult when superparameterization is used, as noted in previous studies. The Walker cell in all simulations exhibits low-frequency variability on a time scale of about 20 days, characterized by four distinctive stages: suppressed, intensification, active, and weakening. The SSTSP algorithm captures spatial structure and temporal evolution of the variability. This reinforces the confidence that SSTSP preserves fundamental interactions between convection and the large-scale flow, and offers a computationally efficient alternative to traditional convective parameterizations.

Anisotropy of turbulence near the top of the stratocumulus‐topped boundary layer (STBL) is studied using large‐eddy simulation (LES) and measurements from the POST and DYCOMS‐II field campaigns. Focusing on turbulence ∼100 m below the cloud top, we see remarkable similarity between daytime and nocturnal flight data covering different inversion strengths and free‐tropospheric conditions. With λ denoting wavelength and zt cloud‐top height, we find that turbulence at λ/zt≃0.01 is weakly dominated by horizontal fluctuations, while turbulence at λ/zt>1 becomes strongly dominated by horizontal fluctuations. Between are scales at which vertical fluctuations dominate. Typical‐resolution LES of the STBL (based on POST flight 13 and DYCOMS‐II flight 1) captures observed characteristics of below‐cloud‐top turbulence reasonably well. However, using a fixed vertical grid spacing of 5 m, decreasing the horizontal grid spacing and increasing the subgrid‐scale mixing length leads to increased dominance of vertical fluctuations, increased entrainment velocity, and decreased liquid water path. Our analysis supports the notion that entrainment parameterizations (e.g., in climate models) could potentially be improved by accounting more accurately for anisotropic deformation of turbulence in the cloud‐top region. While LES has the potential to facilitate improved understanding of anisotropic cloud‐top turbulence, sensitivity to grid spacing, grid‐box aspect ratio, and subgrid‐scale model needs to be addressed.

A simple methodology is proposed to extract impacts of cloud microphysics on macrophysical cloud-field properties in large-eddy simulations of shallow convection. These impacts are typically difficult to assess because of natural variability of the simulated cloud field. The idea is to use two sets of thermodynamic variables driven by different microphysical schemes or by a single scheme with different parameters as applied here. The first set is coupled to the dynamics as in the standard model, and the second set is applied diagnostically—that is, driven by the flow but without the feedback on the flow dynamics. Having the two schemes operating in the same flow pattern allows for extracting the impact with high confidence. For illustration, the method is applied to simulations of precipitating shallow convection applying a simple bulk representation of warm-rain processes. Because of natural variability, the traditional approach provides an uncertain estimate of the impact of cloud droplet concentration on the mean cloud-field rainfall even with an ensemble of simulations. In contrast, the impact is well constrained while applying the new methodology. The method can even detect minuscule changes of the mean cloud cover and liquid water path despite their large temporal fluctuations and different evolutions within the ensemble.

A high-resolution cloud-resolving model (CRM) simulation is developed here for a two-dimensional Walker circulation over a planetary-scale domain of 40 000 km for an extended period of several hundred days. The Walker cell emerges as the time-averaged statistical steady state with a prescribed sinusoidal sea surface temperature (SST) pattern with a mean temperature of 301.15 K and a horizontal variation of 4 K. The circulation exhibits intraseasonal variability on a time scale of about 20 days with quasi-periodic intensification of the circulation and broadening of the convective regime. This variability is closely tied to synoptic-scale systems associated with expansion and contraction of the Walker circulation. An index for the low-frequency variability is developed using an empirical orthogonal function (EOF) analysis and by regressing various dynamic fields on this index. The low-frequency oscillation has four main stages: a suppressed stage with strengthened midlevel circulation, an intensification phase, an active phase with strong upper-level circulation, and a weakening phase. Various physical processes occurring at these stages are discussed as well as the impact of organized convective systems on the large-scale flow.

A cloud-system-resolving model is used to investigate the effects of localized heating/cooling perturbations on tropical deep convection, in the context of the aerosol “invigoration effect.” This effect supposes that a reduction of droplet collision–coalescence in polluted conditions leads to lofting of cloud water in convective updrafts and enhanced freezing, latent heating, and buoyancy. To specifically isolate and test this mechanism, heating perturbations were applied to updrafts with corresponding cooling applied in downdrafts. Ensemble simulations were run with either perturbed or unperturbed conditions and large-scale forcing from a 7.5-day period of active monsoon conditions during the 2006 Tropical Warm Pool–International Cloud Experiment. In the perturbed simulations there was an initial invigoration of convective updrafts and surface precipitation, but convection returned to its unperturbed state after about 24 h because of feedback with the larger-scale environment. This feedback led to an increase in the horizontally averaged mid-/upper-tropospheric temperature of about 1 K relative to unperturbed simulations. When perturbed conditions were applied to only part of the domain, gravity waves rapidly dispersed buoyancy anomalies in the perturbed region to the rest of the domain, allowing convective invigoration from the heating perturbations to be sustained over the entire simulation period. This was associated with a mean mesoscale circulation consisting of ascent (descent) at mid-/upper levels in the perturbed (unperturbed) region. In contrast to recent studies, it is concluded that the invigoration effect is intimately coupled with larger-scale dynamics through a two-way feedback, and in the absence of alterations in the larger-scale circulation there is limited invigoration beyond the convective adjustment time scale.

This paper presents an approach to locally predict homogeneity of the subgrid-scale turbulent mixing in large-eddy simulation of shallow clouds applying double-moment warm-rain microphysics. The homogeneity of subgrid-scale mixing refers to the partitioning of the cloud water evaporation due to parameterized entrainment between changes of the mean droplet radius and changes of the mean droplet concentration. Homogeneous and extremely inhomogeneous mixing represent two limits of possible scenarios, where the droplet concentration and the mean droplet radius remains unchanged during the microphysical adjustment, respectively. To predict the subgrid-scale mixing scenario, the double-moment microphysics scheme is merged with the approach to delay droplet evaporation resulting from entrainment. Details of the new scheme and its application in the Barbados Oceanographic and Meteorological Experiment (BOMEX) shallow convection case are discussed. The simulated homogeneity of mixing varies significantly inside small convective clouds, from close to homogeneous to close to extremely inhomogeneous. The mean mixing characteristics become more homogeneous with height, reflecting increases of the mean droplet size and the mean turbulence intensity, both favoring homogeneous mixing. Model results are consistent with microphysical effects of entrainment and mixing deduced from field observations. Mixing close to homogeneous is predicted in volumes with the highest liquid water content (LWC) and strongest updraft at a given height, whereas mixing in strongly diluted volumes is typically close to extremely inhomogeneous. The simulated homogeneity of mixing has a small impact on mean microphysical characteristics. This result agrees with the previous study applying prescribed mixing scenarios and can be explained by the high humidity of the clear air involved in the subgrid-scale mixing.

Motivated by the need to resolve the condensation-coalescence bottleneck in warm rain formation, a significant number of studies have emerged in the past 15 years concerning the growth of cloud droplets by water-vapor diffusion and by collision-coalescence in a turbulent environment. With regard to condensation, recent studies suggest that small-scale turbulence alone does not produce a significant broadening of the cloud-droplet spectrum because of the smearing of droplet-scale fluctuations by rapid turbulent and gravitational mixing. However, different diffusional-growth histories associated with large-eddy hopping could lead to a significant spectral broadening. In contrast, small-scale turbulence in cumulus clouds makes a significant contribution to the collision-coalescence of droplets, enhancing the collection kernel up to a factor of 5, especially for droplet pairs with a low gravitational collision rate. This moderate level of enhancement has a significant impact on warm rain initiation. The multiscale nature of turbulent cloud microphysical processes and open research issues are delineated throughout.

Lagrangian Cloud Model (LCM) is a mixed Eulerian/Lagrangian approach to atmospheric large eddy simulation (LES), with two-way coupling between Eulerian dynamics and thermodynamics and Lagrangian microphysics. Since Lagrangian representation of microphysics does not suffer from numerical diffusion in the radius space and solves full droplet growth equations, it may be considered an alternative for the bin approach. This paper documents the development of LCM to include collision/coalescence processes. The proposed algorithm maps Lagrangian parcels collision/coalescence events on the specified two-dimensional grid, with the first dimension spanning aerosol radius and the second dimension spanning the cloud droplet radius. The proposed approach is capable of representation of aerosol activation, deactivation, transport inside the droplets, and processing by clouds and in the future may be used to investigate details of these processes. As an illustration, LCM with collision/coalescence is used to investigate effects of aerosols on cloud microphysics and dynamics for a marine stratocumulus cloud. Two extreme cases are considered that represent low and high aerosol concentrations. It is shown that the aerosol type significantly affects cloud microphysics as well as cloud dynamics. In agreement with previous studies, a larger entrainment rate is simulated for the high aerosol concentration. For the low aerosol concentration, intense collision/coalescence and drizzle modify the aerosol size distribution, reducing the concentration in the dry radius range of 0.02 to 0.2 m and increasing the concentration for dry radii larger than 0.3 m. © Copyright 2010 by the American Geophysical Union.

Small-scale mixing between cloudy air and unsaturated clear air is investigated in numerical simulations and in a laboratory cloud chamber. Despite substantial differences in physical conditions and some differences in resolved scales of motion, results of both studies indicate that small-scale turbulence generated through cloud-clear air interfacial mixing is highly anisotropic. For velocity fluctuations, numerical simulations and cloud chamber observations demonstrate that the vertical velocity variance is up to a factor of two larger than the horizontal velocity variance. The Taylor microscales calculated separately for the horizontal and vertical directions also indicate anisotropy of turbulent eddies. This anisotropy is attributed to production of turbulent kinetic energy (TKE) by buoyancy forces due to evaporative cooling of cloud droplets at the cloud-clear air interface. Numerical simulations quantify the effects of buoyancy oscillations relative to the values expected from adiabatic and isobaric mixing, standardly assumed in cloud physics. The buoyancy oscillations result from microscale transport of liquid water due to the gravitational sedimentation of cloud droplets. In the particular modeling setup considered here, these oscillations contribute to about a fifth of the total TKE production. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.

We examine the impact of assumed cloud droplet concentration on the simulated diurnal cycle of rainfall over New Guinea and surrounding seas using convection-permitting numerical simulations with the Weather Research and Forecasting (WRF) model. The simulations mimic effects of cloud condensation nuclei on cloud and precipitation processes. They follow simulations reported in Hassim et al (ACP 2016) that focused on dynamical aspects, namely the topographic forcing and the off-shore propagation of convective systems that contribute to the observed early-morning rainfall maximum north-east of New Guinea. Simulations reported in this current study apply the bulk cloud microphysics of Thompson et al. with contrasting cloud droplet concentrations of 100 and 1,000 per cc, referred to as pristine and polluted conditions, respectively. Overall, the assumed cloud droplet concentration has a small impact on the simulated convection. This emphasizes the predominant control from the diurnal cycle and the large-scale conditions. Pristine convection results in a 15–20 % larger surface accumulated rainfall over both land and ocean, and a noticeable shift of the cloud top height distribution, a reduction of the contribution of shallow cloudiness (cloud tops below 3 km) and an increase of the population of deep clouds (cloud tops above 9 km). The simulated impact on precipitation and cloud fields is in stark contrast to previous modelling studies that document small enhancement of surface precipitation and significant increase of the cloud top height in polluted conditions. Analysis of microphysical fields suggests that the simulated small enhancement of precipitation in pristine conditions comes from more efficient rain processes below the freezing level and enhanced graupel initiation and growth aloft. The increase of the cloud top height is arguably due to precipitation off-loading increasing cloud buoyancy aloft that has been shown to operate in shallow warm convection. However, the relatively low horizontal resolution and application of the bulk cloud microphysics warrants follow-up studies to assess validity of the impacts documented in the current study.

The rapid transition from shallow to deep convection is investigated using large-eddy simulations. The role of cold pools, which occur due to the evaporation of rainfall, is explored using a series of experiments in which their formation is suppressed. A positive feedback occurs: the presence of cold pools promotes deeper, wider, and more buoyant clouds with higher precipitation rates, which in turn lead to stronger cold pools. To assess the influence of the subcloud layer on the development of deep convection, the coupling between the cloud layer and the subcloud layer is explored using Lagrangian particle trajectories. As shown in previous studies, particles that enter clouds have properties that deviate significantly from the mean state. However, the differences between particles that enter shallow and deep clouds are remarkably small in the subcloud layer, and become larger in the cloud layer, indicating different entrainment rates. The particles that enter the deepest clouds also correspond to the widest cloud bases, which points to the importance of convective organization within the subcloud layer.

This paper presents application of the Weather Research and Forecasting (WRF) model to limited-area modeling of atmospheric processes over the subtropical south-eastern Pacific, with the emphasis on the stratocumulus-topped boundary layer. The simulations cover a domain from the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) field project conducted in the subtropical south-eastern Pacific in October and November 2008. We focus on a day where the UK's BAe-146 research aircraft encountered Pockets of Open Cells (POCs) at the very western edge of its flight track, rather than on the entire campaign as investigated in previous limited-area modeling studies. Model results are compared to aircraft observations with the main conclusion that the simulated stratocumulus-topped boundary layer is significantly too shallow. This appears to be a combination of an already too shallow boundary layer in the dataset used to provide initial and lateral boundary conditions, and the inability of the WRF model to increase the boundary-layer height. Several sensitivity simulations, applying different subgrid-scale parameterizations available in the model, a larger computational domain and longer simulations, as well as a different dataset providing initial and lateral boundary conditions were all tried to improve the simulation. These changes appeared to have a rather small effect on the results. The model does simulate the formation of mesoscale cloud-free regions that one might consider similar to Pockets of Open Cells observed in nature. However, formation of these regions does not seem to be related to drizzle-induced transition from open- to closed-cell circulations as simulated by LES models. Instead, the cloud-free regions appear to result from mesoscale variations of the lower-tropspheric vertical velocity. Areas of negative vertical velocity with minima (a few cm s−1) near the boundary layer top seem to induce direct evaporation of the cloud layer. It remains to be seen in LES studies whether the mechanism seen in the model is realistic or if it is simply an artifact of interactions between resolved and parameterized processes.

In this survey we consider the impact of turbulence on cloud formation from the cloud scale to the droplet scale. We assess progress in understanding the effect of turbulence on the condensational and collisional growth of droplets and the effect of entrainment and mixing on the droplet spectrum. The increasing power of computers and better experimental and observational techniques allow for a much more detailed study of these processes than was hitherto possible. However, much of the research necessarily remains idealized and we argue that it is those studies which include such fundamental characteristics of clouds as droplet sedimentation and latent heating that are most relevant to clouds. Nevertheless, the large body of research over the last decade is beginning to allow tentative conclusions to be made. For example, it is unlikely that small-scale turbulent eddies (i.e. not the energy-containing eddies) alone are responsible for broadening the droplet size spectrum during the initial stage of droplet growth due to condensation. It is likely, though, that small-scale turbulence plays a significant role in the growth of droplets through collisions and coalescence. Moreover, it has been possible through detailed numerical simulations to assess the relative importance of different processes to the turbulent collision kernel and how this varies in the parameter space that is important to clouds. The focus of research on the role of turbulence in condensational and collisional growth has tended to ignore the effect of entrainment and mixing and it is arguable that they play at least as important a role in the evolution of the droplet spectrum. We consider the role of turbulence in the mixing of dry and cloudy air, methods of quantifying this mixing and the effect that it has on the droplet spectrum. Copyright © 2012 Royal Meteorological Society and British Crown Copyright, the Met Office

This paper presents the application of a double-moment bulk warm-rain microphysics scheme to the simulation of a field of shallow convective clouds based on Barbados Oceanographic and Meteorological Experiment (BOMEX) observations. The scheme predicts the supersaturation field and allows secondary in-cloud activation of cloud droplets above the cloud base. Pristine and polluted cloud condensation nuclei (CCN) environments, as well as opposing subgrid-scale mixing scenarios, are contrasted. Numerical simulations show that about 40% of cloud droplets originate from CCN activated above the cloud base. Significant in-cloud activation leads to the mean cloud droplet concentration that is approximately constant with height, in agreement with aircraft observations. The in-cloud activation affects the spatial distribution of the effective radius and the mean albedo of the cloud field. Differences between pristine and polluted conditions are consistent with the authors’ previous study, but the impact of the subgrid-scale mixing is significantly reduced. Possible explanations of the latter involve physical and numerical aspects. The physical aspects include (i) the counteracting impacts of the subgrid-scale mixing and in-cloud activation and (ii) the mean characteristics of the environmental cloud-free air entrained into a cloud. A simple analysis suggests that the entrained cloud-free air is on average close to saturation, which leads to a small difference between various mixing scenarios. The numerical aspect concerns the relatively small role of the parameterized subgrid-scale mixing when compared to mixing and evaporation due to numerical diffusion. Although the results are consistent with aircraft observations, limitations of the numerical model due to low spatial resolution call for higher-resolution simulations where entrainment processes are resolved rather than mostly parameterized as in the current study.

This paper presents observations and simple numerical modeling of drizzle processes in subtropical marine stratocumulus. Flight-long statistics from DYCOMS-II flights are derived and examples of small-scale cloud and drizzle observations are presented. The small-scale observations highlight the complexity of the natural system and the deficiency of an approach where single values of relevant parameters are used to describe the entire cloud system. Together with previously published analysis of ACE-2 flights, DYCOMS-II statistics are compared to the output of a kinematic (prescribed flow) model of drizzle processes in stratocumulus. Such a model has previously been used to validate simplified approaches to cloud microphysics, and it can be used in the future as a “superparameterization” of microphysical processes within stratocumulus-topped marine boundary layer. The focus is on separating the impact of the cloud depth from the impact of the cloud droplet concentration, with deeper and lower-droplet-concentration clouds both leading to more drizzle. The kinematic model reduces the stratocumulus-topped marine boundary layer dynamics to a single circulation cell that spans the entire boundary-layer depth. The model produces significantly less drizzle than estimated from the observations, and possible reasons for such a discrepancy are discussed. However, the model does reproduce observationally-based relationships between drizzle and such cloud parameters as cloud depth, droplet concentration, or maximum droplet size near the cloud top. To quantify the observed reductions of the cloud water and droplet concentration, a twin experiment approach is used, with and without collision/coalescence. The results show that observed reduction of cloud water content and droplet concentration may result from scavenging of cloud droplets by drizzle drops, in addition to processes by design excluded from the model, such as entrainment.

This paper presents application of the EULAG model combined with a sophisticated double-moment warm-rain microphysics scheme to the model intercomparison case based on RICO (Rain in Cumulus over Ocean) field observations. As the simulations progress, the cloud field gradually deepens and a relatively sharp temperature and moisture inversions develop in the lower troposphere. Two contrasting aerosol environments are considered, referred to as pristine and polluted, together with two contrasting subgridscale mixing scenarios, the homogeneous and the extremely inhomogeneous mixing. Pristine and polluted environments feature mean cloud droplet concentrations around 40 and 150 mg−1, respectively, and large differences in the rain characteristics. Various measures are used to contrast evolution of macroscopic cloud field characteristics, such as the mean cloud fraction, the mean cloud width, or the height of the center of mass of the cloud field, among others. Macroscopic characteristics appear similar regardless of the aerosol characteristics or the homogeneity of the subgrid-scale mixing.

A b s t r a c t This paper describes implementation of the warm-rain bin microphysics in a LES model based on the EULAG fluid flow solver. The binmicrophysics EULAG is applied to the case of shallow nonprecipitating tropical convection to investigate the impact of the secondary activation of cloud droplets above the cloud base. In a previous study applying the EULAG model with the double-moment bulk warm-rain microphysics scheme, the in-cloud activation was shown to have significant implications for the mean microphysical and optical characteristics of the cloud field. By contrasting the simulations with and without in-cloud activation as in the previous study, we show that the in-cloud activation has qualitatively similar but quantitatively smaller eect. In particular, the concentration of cloud droplets in the bin simulation without in-cloud activation decreases with height not as strongly as in corresponding simulations applying the double-moment bulk scheme.

This paper extends the previous cloud-resolving modeling study concerning the impact of cloud microphysics on convective–radiative quasi equilibrium (CRQE) over a surface with fixed characteristics and prescribed solar input, both mimicking the mean conditions on earth. The current study applies sophisticated double-moment warm-rain and ice microphysics schemes, which allow for a significantly more realistic representation of the impact of aerosols on precipitation processes and on the coupling between clouds and radiative transfer. Two contrasting cloud condensation nuclei (CCN) characteristics are assumed, representing pristine and polluted conditions, as well as contrasting representations of the effects of entrainment and mixing on the mean cloud droplet size. In addition, four sets of sensitivity simulations are also performed with changes that provide a reference for the main simulation set. As in the previous study, the CRQE mimics the estimates of globally and annually averaged water and energy fluxes across the earth’s atmosphere. There are some differences from the previous study, however, consistent with the slightly lower water vapor content in the troposphere and significantly reduced lower-tropospheric cloud fraction in current simulations. There is also a significant reduction of the difference between the pristine and polluted cases, from ∼20 to ∼4 W m−2 at the surface from ∼20 to ∼9 W m−2 at the top of the atmosphere (TOA). The difference between the homogeneous and extremely inhomogeneous mixing scenarios, ∼20 W m−2 in the previous study, is reduced to a mere 2 (1) W m−2 at the surface (TOA). An unexpected difference between the previous and current simulations is the lower Bowen ratio of the surface heat flux, the partitioning of the total flux into sensible and latent components. It is shown that most of the change comes from the difference in the representation of rain evaporation in the subcloud layer in the single- and double-moment microphysics schemes. The difference affects the mean air temperature and humidity near the surface, and thus the Bowen ratio. The differences between the various simulations are discussed, contrasting the process-level approach with the impact of cloud microphysics on the quasi-equilibrium state with a more appropriate system dynamics approach. The key distinction is that the latter includes the interactions among all the processes in the modeled system.

The physical principle of convective quasi-equilibrium proposed by Arakawa and Schubert states that the atmosphere is effectively adjusted to equilibrium by an active role of convective heating against large-scale forcing (physical convective quasi-equilibrium, or PCQ). A simple consequence of this principle is that the rate of change of the thermodynamic field (typically measured by the convective available potential energy (CAPE)) is much smaller than the rate of change of the large-scale forcing (diagnostic convective quasi-equilibrium, or DCQ). Such a diagnostic state is generally observed in the tropical atmosphere at the synoptic-scale, and this is often taken as a proof for the physical mechanisms behind Arakawa and Schubert's convective quasi-equilibrium: however, theoretically, there are several alternative physical mechanisms that are also able to establish this diagnostic state. The paper examines the approach of the tropical atmospheric system to DCQ with increasing time-scale in order to distinguish various alternatives to PCQ. The latter predicts that the system approaches DCQ exponentially with a time-scale characteristic of convection. However, the alternatives considered in the paper predict algebraic asymptotes to DCQ with increasing time-scale. First it is demonstrated that PCQ is not required to achieve DCQ by considering a linear primitive-equation system with arbitrary convective heating, in which the roles of convective heating and large-scale forcing are completely reversed; algebraic asymptotes are achieved. An even simpler analogue is to assume that the rate of generating CAPE is controlled by white-noise forcing. More generally, such an algebraic asymptote is obtained by any system with a power-law spectrum both for CAPE and large-scale forcing, although a restriction must be applied to ensure a decreasing asymptote with increasing time-scale. The approach to DCQ is examined for both the Maritime Continent Thunderstorm Experiment data and cloud-resolving model simulation data, and both indicate no tendency for exponential adjustments in the short time limit.

This paper describes the development of a new multicomponent detailed bin ice microphysics scheme that predicts the number concentration of ice as well as the rime mass mixing ratio in each mass bin. This allows for local prediction of the rime mass fraction. In this approach, the ice particle mass size, projected area size, and terminal velocity–size relationships vary as a function of particle mass and rimed mass fraction, based on a simple conceptual model of rime accumulation in the crystal interstices that leads to an increase in particle mass, but not in its maximum size, until a complete “filling in” with rime and conversion to graupel occurs. This approach allows a natural representation of the gradual transition from unrimed crystals to rimed crystals and graupel during riming. The new ice scheme is coupled with a detailed bin representation of the liquid hydrometeors and applied in an idealized 2D kinematic flow model representing the evolution of a mixed-phase precipitating cumulus. Results using the bin scheme are compared with simulations using a two-moment bulk scheme employing the same approach (i.e., separate prediction of bulk ice mixing ratio from vapor deposition and riming, allowing for local prediction of bulk rime mass fraction). The bin and bulk schemes produce similar results in terms of ice and liquid water paths and optical depths, as well as the timing of the onset and peak surface precipitation rate. However, the peak domain-average surface precipitation rate produced by the bulk scheme is about 4 times that in the bin simulation. The bin scheme is also compared with simulations that assume the ice particles consist entirely of either unrimed snow or graupel. While overall results are fairly similar, the onset and timing of the peak domain-average surface precipitation rate are substantially delayed in the simulations that treat the ice particles as either unrimed snow or graupel. These results suggest the importance of representing different ice types, including partially rimed crystals, for this case.

This paper presents a hybrid approach to model warm-rain processes, merging the diverse schemes of bulk and detailed (bin) microphysics. In the bulk scheme, the key assumption is that the exact saturation is maintained inside a cloud. In contrast, the supersaturation inside a cloud is predicted in the bin scheme and is applied to calculate the diffusional growth of cloud droplets. Predicting the supersaturation is numerically cumbersome, however, and typically requires spatial and temporal resolutions that are significantly higher than those that can be applied in the bulk scheme. At the same time, supersaturations inside clouds are small, and the condensate amounts in bulk and bin schemes differ insignificantly. This critical observation forms a starting point for the hybrid bulk–bin approach. In this approach, when the cloud water first appears, the activation scheme inserts cloud droplets at the low end of the bin representation. Subsequent diffusional and eventually accretional growth shift the spectrum toward larger sizes so that the saturation inside a cloud is maintained. Details of the hybrid approach are discussed in this paper, and the validation against the traditional bin scheme in a framework of the adiabatic rising parcel is presented. Before the scheme can be applied to the multidimensional cloud model, a 1D advection–condensation problem of Grabowski and Smolarkiewicz is used to address the issue of the numerical difficulties that finite-difference schemes experience near cloud edges. In the bulk case, these are in the form of condensation rate overshoots and undershoots; and this aspect requires special attention in the hybrid scheme. A novel approach is developed that provides a physically consistent solution near cloud edges using the hybrid bulk–bin scheme. The key is to allow grid boxes near the edges to be partly cloudy and to include spectral changes of cloud droplets that take this into account. Application of the hybrid scheme to an idealized 2D problem of moist thermal rising from rest and producing rain illustrates the application of the scheme to practical problems of cloud dynamics and warm-rain microphysics.

Superparameterization (SP) is a large-scale modeling system with explicit representation of small-scale and mesoscale processes provided by a cloud-resolving model (CRM) embedded in each column of a large-scale model. New efficient sparse space–time algorithms based on the original idea of SP are presented. The large-scale dynamics are unchanged, but the small-scale model is solved in a reduced spatially periodic domain to save the computation cost following a similar idea applied by one of the authors for aquaplanet simulations. In addition, the time interval of integration of the small-scale model is reduced systematically for the same purpose, which results in a different coupling mechanism between the small- and large-scale models. The new algorithms have been applied to a stringent two-dimensional test suite involving moist convection interacting with shear with regimes ranging from strong free and forced squall lines to dying scattered convection as the shear strength varies. The numerical results are compared with the CRM and original SP. It is shown here that for all of the regimes of propagation and dying scattered convection, the large-scale variables such as horizontal velocity and specific humidity are captured in a statistically accurate way (pattern correlations above 0.75) based on space–time reduction of the small-scale models by a factor of ⅓; thus, the new efficient algorithms for SP result in a gain of roughly a factor of 10 in efficiency while retaining a statistical accuracy on the large-scale variables. Even the models with ⅙ reduction in space–time with a gain of 36 in efficiency are able to distinguish between propagating squall lines and dying scattered convection with a pattern correlation above 0.6 for horizontal velocity and specific humidity. These encouraging results suggest the possibility of using these efficient new algorithms for limited-area mesoscale ensemble forecasting.

This note discusses the results of numerical simulations in which a prescribed-flow model is merged with a double-moment warm-rain and ice microphysics scheme to investigate the impact of microphysical processes on precipitation from deep organized convection. The prescribed two-dimensional flow mimics an idealized squall line, with a narrow region of strong convective updraft and much wider region of weak stratiform updraft overlaying a stratiform downdraft. To cover the broad range of conditions that are possible for a squall line as well as to explore precipitation dependence on different parameters, 25 pairs of simulations are performed. Simulated cases differ in the dynamics (e.g. changing the updraft strength or large-scale shear), thermodynamics (e.g. changing the inflow sounding) or microphysics (e.g. changing the collision efficiencies). Each pair features cloud condensation nuclei (CCN) in either a pristine or polluted environment. Total surface precipitation and partitioning between convective and stratiform precipitation in each pair appears to be almost the same, with the difference being typically a few tenths of 1%. However, the dynamical and thermodynamical parameters do affect the precipitation significantly. It follows that the surface precipitation from organized convection can differ between pristine and polluted environments only through the feedback of CCN on cloud dynamics. In this feedback, small differences in the latent heating for the same flow pattern lead to different flow patterns in subsequent squall-line evolution. Details of this feedback need to be investigated using a dynamical model. Copyright © 2009 Royal Meteorological Society

This note presents an analysis of several dozens of direct numerical simulations of the cloud–clear air mixing in a setup of decaying moist turbulence with bin microphysics. The goal is to assess the instantaneous relationship between the homogeneity of mixing and the ratio of the time scales of droplet evaporation and turbulent homogenization. Such a relationship is important for developing improved microphysical parameterizations for large-eddy simulation of clouds. The analysis suggests a robust relationship for the range of time scale ratios between 0.5 and 10. Outside this range, the scatter of numerical data is significant, with smaller and larger time scale ratios corresponding to mixing scenarios that approach the extremely inhomogeneous and homogeneous limits, respectively. This is consistent with the heuristic argument relating the homogeneity of mixing to the time scale ratio.

This paper discusses an extension of the approach proposed previously to represent the delay of cloud water evaporation and buoyancy reversal due to the cloud–environment mixing in bulk microphysics large-eddy simulation of clouds. In the original approach, an additional equation for the mean spatial scale of cloudy filaments was introduced to represent the progress toward microscale homogenization of a volume undergoing turbulent cloud–environment mixing, with the evaporation of cloud water allowed only when the filament scale approached the Kolmogorov microscale. Here, it is shown through a posteriori analysis of model simulations that one should also predict the volume fraction of the cloudy air that was diagnosed in the original approach. The resulting model of turbulent mixing and homogenization, referred to as the λ–β model, is applied in a series of shallow convection simulations using various spatial resolutions and compared to the traditional bulk model. This work represents an intermediate step in the development of a modeling framework to simulate characteristics of microphysical transformations during entrainment and subgrid-scale turbulent mixing.

A large set of rising adiabatic parcel simulations is executed to investigate the combined diffusional and accretional growth of cloud droplets in maritime and continental conditions, and to assess the impact of enhanced droplet collisions due to small-scale cloud turbulence. The microphysical model applies the droplet number density function to represent spectral evolution of cloud and rain/drizzle drops, and various numbers of bins in the numerical implementation, ranging from 40 to 320. Simulations are performed applying two traditional gravitational collection kernels and two kernels representing collisions of cloud droplets in the turbulent environment, with turbulent kinetic energy dissipation rates of 100 and 400 cm2 s−3. The overall result is that the rain initiation time significantly depends on the number of bins used, with earlier initiation of rain when the number of bins is low. This is explained as a combination of the increase of the width of activated droplet spectrum and enhanced numerical spreading of the spectrum during diffusional and collisional growth when the number of model bins is low. Simulations applying around 300 bins seem to produce rain at times which no longer depend on the number of bins, but the activation spectra are unrealistically narrow. These results call for an improved representation of droplet activation in numerical models of the type used in this study. Despite the numerical effects that impact the rain initiation time in different simulations, the turbulent speedup factor, the ratio of the rain initiation time for the turbulent collection kernel and the corresponding time for the gravitational kernel, is approximately independent of aerosol characteristics, parcel vertical velocity, and the number of bins used in the numerical model. The turbulent speedup factor is in the range 0.75–0.85 and 0.60–0.75 for the turbulent kinetic energy dissipation rates of 100 and 400 cm2 s−3, respectively.

Quantitative parameterization of turbulent collision of cloud droplets represents a major unsolved problem in cloud physics. Here a hybrid direct simulation tool is used specifically to quantify the turbulent enhancement of the gravitational collision-coalescence. Simulation results show that air turbulence can enhance the collision kernel by an average factor of about 2, and the observed trends are supported by scaling arguments. An impact study using the most realistic collection kernel suggests that cloud turbulence can significantly reduce the time for warm rain initiation. Areas for further development of the hybrid simulation and the impact study are indicated. Copyright © 2009 Royal Meteorological Society