Aerosol-cloud interactions are a persistent source of uncertainty in climate research. This study presents findings from a model intercomparison project examining the impact of aerosols on clouds and climate in convection-permitting radiative-convective equilibrium (RCE) simulations. Specifically, 11 different modeling teams conducted RCE simulations under varying aerosol concentrations, domain configurations, and sea surface temperatures (SSTs). We analyze the response of domain-mean cloud and radiative properties to imposed aerosol concentrations across different SSTs. Additionally, we explore the potential impact of aerosols on convective aggregation and large-scale circulation in large-domain simulations. The results reveal that the cloud and radiative responses to aerosols vary substantially across models. However, a common trend across models, SSTs, and domain configurations is that increased aerosol loading tends to suppress warm rain formation, enhance cloud water content in the mid-troposphere, and consequently increase mid-tropospheric humidity and upper-tropospheric temperature, thereby impacting static stability. The warming of the upper troposphere can be attributed to reduced lateral entrainment effects due to the higher environmental humidity in the mid-troposphere. However, models do not agree on aerosol impacts on convective updraft velocity based on the preliminary examination of high-percentiles of vertical velocity at a single mid-troposheric layer (500 hPa). In large-domain simulations, where convection tends to self-organize, aerosol loading does not consistently influence self-organization but tends to reduce the intensity of large-scale circulation forming between convective clusters and dry regions. This reduction in circulation intensity can be explained by the increase in static stability due to the upper tropospheric warming.

Forecasting solar radiation is critical for balancing the electricity grid due to increasing production from solar energy. To this end, we need precise simulation of clouds, which is traditionally done by numerical weather prediction. However, these large-scale (LS) models struggle especially with forecasting stratocumulus clouds because their coarse vertical resolution cannot capture the sharp inversion present at stratocumulus cloud top. To address this issue, we employ large eddy simulation (LES), which operates at high resolution and has demonstrated superior accuracy in simulating stratocumulus clouds. However, LES relies on input data from a LS model, which is imperfect. To reduce the uncertainty caused by the LS data, we integrate a single ensemble Kalman filter step at the start of simulation in the LES model, utilizing local observations. Our results show that this approach is computationally feasible, robust, and reduces prediction error at assimilation by 50%. The improvement diminishes after approximately 1 hour of simulation due to the influence of large-scale forcing. Future work will focus on enhancing the LS inflow through nested simulations with realistic lateral boundary conditions to sustain the improvements in forecasting accuracy.

The vertical profiles of the wind speed and direction in atmospheric boundary layers are strongly controlled by turbulence. Most global weather forecast and climate models parameterize the vertical transport of horizontal momentum by turbulent eddies by means of a downgradient eddy diffusion approach, in which the same stability-dependent eddy viscosity profile is applied to both horizontal wind components. In this study we diagnose eddy viscosity profiles from large-eddy simulations of five convective boundary layers with wind shear. Each simulation was forced by the same geostrophic wind of 7.5 (Formula presented.), but with different surface heat fluxes in the range between 0.03 and 0.18 (Formula presented.). We find that the eddy viscosity profiles for the two horizontal wind components differ significantly, in particular, we diagnose negative eddy viscosities, indicating vertical turbulent transport that is counter the mean gradient. This suggests that a purely downgradient diffusion approach for turbulent momentum fluxes is inadequate. A modified solution of the Ekman spiral demonstrates that different eddy viscosity profiles for the two horizontal wind components lead to a different wind profile. To improve parameterizations that apply a downgradient diffusion approach for momentum, correction terms to allow for non-local, boundary-layer scale transport should be incorporated.

Clouds affected by solar eclipses could influence the reflection of sunlight back into space and might change local precipitation patterns. Satellite cloud retrievals have so far not taken into account the lunar shadow, hindering a reliable spaceborne assessment of the eclipse-induced cloud evolution. Here we use satellite cloud measurements during three solar eclipses between 2005 and 2016 that have been corrected for the partial lunar shadow together with large-eddy simulations to analyze the eclipse-induced cloud evolution. Our corrected data reveal that, over cooling land surfaces, shallow cumulus clouds start to disappear at very small solar obscurations (~15%). Our simulations explain that the cloud response was delayed and was initiated at even smaller solar obscurations. We demonstrate that neglecting the disappearance of clouds during a solar eclipse could lead to a considerable overestimation of the eclipse-related reduction of net incoming solar radiation. These findings should spur cloud model simulations of the direct consequences of sunlight-intercepting geoengineering proposals, for which our results serve as a unique benchmark.

Numerical simulations of the tropical mesoscales often exhibit a self-reinforcing feedback between cumulus convection and shallow circulations, which leads to the self-aggregation of clouds into large clusters. We investigate whether this basic feedback can be adequately captured by large-eddy simulations (LESs). To do so, we simulate the non-precipitating, cumulus-topped boundary layer of the canonical “BOMEX” case over a range of numerical settings in two models. Since the energetic convective scales underpinning the self-aggregation are only slightly larger than typical LES grid spacings, aggregation timescales do not converge even at rather high resolutions (<100 m). Therefore, high resolutions or improved sub-filter scale models may be required to faithfully represent certain forms of trade-wind mesoscale cloud patterns and self-aggregating deep convection in large-eddy and cloud-resolving models, and to understand their significance relative to other processes that organize the tropical mesoscales.

Condensation in cumulus clouds plays a key role in structuring the mean, nonprecipitating trade wind boundary layer. Here, we summarize how this role also explains the spontaneous growth of mesoscale [.O(10) km] fluctuations in clouds and moisture around the mean state in a minimal-physics, large-eddy simulation of the undisturbed period during BOMEX on a large [O(100) km] domain. Small, spatial anomalies in condensation in cumulus clouds, which form on top of small moisture fluctuations, power circulations that transport moisture, but not heat, from dry to moist regions, and thus reinforce the condensation anomaly. We frame this positive feedback as a linear instability in mesoscale moisture fluctuations, whose time scale depends only on (i) a vertical velocity scale and (ii) the mean environment's vertical structure. In our minimal-physics setting, we show both ingredients are provided by the shallow cumulus convection itself: it is intrinsically unstable to length scale growth. The upshot is that energy released by clouds at kilometer scales may play a more profound and direct role in shaping the mesoscale trade wind environment than is generally appreciated, motivating further research into the mechanism's relevance.

The parameterised description of subgrid-scale processes in the clear and cloudy boundary layer has a strong impact on the performance skill in any numerical weather prediction (NWP) or climate model and is still a prime source of uncertainty. Yet, improvement of this parameterised description is hard because operational models are highly optimised and contain numerous compensating errors. Therefore, improvement of a single parameterised aspect of the boundary layer often results in an overall deterioration of the model as a whole. In this paper, we will describe a comprehensive integral revision of three parameterisation schemes in the High Resolution Local Area Modelling - Aire Limitée Adaptation dynamique Développement InterNational (HIRLAM-ALADIN) Research on Mesoscale Operational NWP In Europe - Applications of Research to Operations at Mesoscale (HARMONIE-AROME) model that together parameterise the boundary layer processes: the cloud scheme, the turbulence scheme, and the shallow cumulus convection scheme. One of the major motivations for this revision is the poor representation of low clouds in the current model cycle. The newly revised parametric descriptions provide an improved prediction not only of low clouds but also of precipitation. Both improvements can be related to a stronger accumulation of moisture under the atmospheric inversion. The three improved parameterisation schemes are included in a recent update of the HARMONIE-AROME configuration, but its description and the insights in the underlying physical processes are of more general interest as the schemes are based on commonly applied frameworks. Moreover, this work offers an interesting look behind the scenes of how parameterisation development requires an integral approach and a delicate balance between physical realism and pragmatism.

The misrepresentation of the diurnal cycle of boundary layer clouds by large-scale models strongly impacts the modeled regional energy balance in southern West Africa. In particular, recognizing the processes involved in the maintenance and transition of the nighttime stratocumulus to diurnal shallow cumulus over land remains a challenge. This is due to the fact that over vegetation, surface fluxes exhibit a much larger magnitude and variability than on the more researched marine stratocumulus transitions. An improved understanding of the interactions between surface and atmosphere is thus necessary to improve its representation. To this end, the Dynamics-aerosol-chemistry-cloud interactions in West Africa (DACCIWA) measurement campaign gathered a unique dataset of observations of the frequent stratocumulus-to-cumulus transition in southern West Africa. Inspired and constrained by these observations, we perform a series of numerical experiments using large eddy simulation. The experiments include interactive radiation and surface schemes where we explicitly resolve, quantify and describe the physical processes driving such transition. Focusing on the local processes, we quantify the transition in terms of dynamics, radiation, cloud properties, surface processes and the evolution of dynamically relevant layers such as subcloud layer, cloud layer and inversion layer. We further quantify the processes driving the stratocumulus thinning and the subsequent transition initiation by using a liquid water path budget. Finally, we study the impact of mean wind and wind shear at the cloud top through two additional numerical experiments. We find that the sequence starts with a nighttime well-mixed layer from the surface to the cloud top, in terms of temperature and humidity, and transitions to a prototypical convective boundary layer by the afternoon. We identify radiative cooling as the largest factor for the maintenance leading to a net thickening of the cloud layer of about 18 g m^-2 h^-1 before sunrise. Four hours after sunrise, the cloud layer decouples from the surface through a growing negative buoyancy flux at the cloud base. After sunrise, the increasing impact of entrainment leads to a progressive thinning of the cloud layer. While the effect of wind on the stratocumulus layer during nighttime is limited, after sunrise we find shear at the cloud top to have the largest impact: the local turbulence generated by shear enhances the boundary layer growth and entrainment aided by the increased surface fluxes. As a consequence, wind shear at the cloud top accelerates the breakup and transition by about 2 h. The quantification of the transition and its driving factors presented here sets the path for an improved representation by larger-scale models.

Motivated by an observed relationship between marine low cloud cover and surface wind speed, this study investigates how vertical wind shear affects trade-wind cumulus convection, including shallow cumulus and congestus with tops below the freezing level. We ran large-eddy simulations for an idealized case of trade-wind convection using different vertical shears in the zonal wind. Backward shear, whereby surface easterlies become upper westerlies, is effective at limiting vertical cloud development, which leads to a moister, shallower, and cloudier trade-wind layer. Without shear or with forward shear, shallow convection tends to deepen more, but clouds tops are still limited under forward shear. A number of mechanisms explain the observed behavior: First, shear leads to different surface wind speeds and, in turn, surface heat and moisture fluxes due to momentum transport, whereby the weakest surface wind speeds develop under backward shear. Second, a forward shear profile in the subcloud layer enhances moisture aggregation and leads to larger cloud clusters, but only on large domains that generally support cloud organization. Third, any absolute amount of shear across the cloud layer limits updraft speeds by enhancing the downward oriented pressure perturbation force. Backward shear—the most typical shear found in the winter trades—can thus be argued a key ingredient at setting the typical structure of the trade-wind layer.

Momentum transport by boundary layer turbulence causes a weak synoptic-scale vertical motion. The classical textbook solution for the strength of this Ekman pumping depends on the curl of the surface momentum flux. A new solution for Ekman pumping is derived in terms of the curl of the geostrophic wind and a term that depends in a nontrivial way on the vertical profile of the turbulent momentum flux. The solution is confined to a boundary layer regime that is vertically well mixed and horizontally homogeneous. The momentum flux is computed from a commonly used bulk surface drag formula and a flux jump relation to capture the entrainment flux of momentum at the top of the boundary layer. It is found that the strength of Ekman pumping is bounded. The weakening of Ekman pumping for enhanced turbulent surface friction can be explained from the fact that it will reduce the magnitude of the horizontal wind. It is demonstrated that entrainment of momentum across the top of the boundary layer tends to diminish the large-scale divergence of the wind. As momentum transport is parameterized in large-scale models, the analysis is relevant for the understanding and interpretation of the evolution of synoptic-scale vertical motions as predicted by such models.

To study the influence of convective momentum transport (CMT) on wind, boundary layer and cloud evolution in a marine cold air outbreak (CAO) we use large-eddy simulations subject to different baroclinicity (wind shear) but similar surface forcing. The simulated domain is large enough, (Formula presented.) km²), to develop typical mesoscale cellular convective structures. We find that a maximum friction induced by momentum transport (MT) locates in the cloud layer for an increase of geostrophic wind with height (forward shear, FW) and near the surface for a decrease of wind with height (backward shear, BW). Although the total MT always acts as a friction, the interaction of friction-induced cross-isobaric flow with the Coriolis force can develop supergeostrophic winds near the surface (FW) or in the cloud layer (BW). The contribution of convection to MT is evaluated by decomposing the momentum flux by column water vapor and eddy size, revealing that CMT acts to accelerate subcloud layer winds under FW shear and that mesoscale circulations contribute significantly to MT for this horizontal resolution (250 m), even if small-scale eddies are nonnegligible and likely more important as resolution increases. Under FW shear, a deeper boundary layer and faster cloud transition are simulated, because MT acts to increase surface fluxes and wind shear enhances turbulent mixing across cloud tops. Our results show that the coupling between winds and convection is crucial for a range of problems, from CAO lifetime and cloud transitions to ocean heat loss and near-surface wind variability.

This study investigated the surface temperature, air temperature and mean radiant temperature inside an idealized 2D street geometry during daytime. The goal was to unravel the relative impact of radiative transfer, heat conduction and ventilation to the urban heat budget. A building-resolving simulation model has been used, which represents these processes at a 1 m spatial resolution. Different combinations of the canyon height to width ratio (H/W) and physical mechanisms were investigated. Shortwave radiation is the main source of energy, and for small H/W can be higher at the canyon ground level compared to flat terrain due to multiple reflections. The longwave trapping effect has the second largest contribution and becomes relatively more important with increasing H/W ratio. The influence of the interior building temperature is small. Surface temperature and mean radiant temperature are closely related, since both are largely controlled by radiative properties. No straightforward relation was found between surface temperature and air temperature, since air temperature is dependent on the competing mechanisms of forced and natural convection. A small increase in air temperature inside the canyon was observed compared to the ambient temperature above roof level. The inclusion of all key physical processes in high detail resulted in large computational requirements. If multiple reflections by the building facades are small, the more traditional, yet much simpler view factor approach will strongly reduce the computational costs as compared to the Monte Carlo technique. The influence of using the view factors on the results must be investigated.

The authors regret to inform the readers that a programming error was found in the numerical code described and used in the original submission [1]. Longwave trapping was not correctly scaled with the local cell size and is underpredicted for deep canyons. Calculations have been repeated and this corrigendum provides an overview of the new results for a deep canyon. All new results will be published in a forthcoming Phd thesis [2] that will made publicly available through the TU Delft website (https://repository.tudelft.nl/). The authors would like to apologise for any inconvenience caused.