We present a proof-of-concept for the adaptive mesh refinement method applied to atmospheric boundary-layer simulations. Such a method may form an attractive alternative to static grids for studies ...on atmospheric flows that have a high degree of scale separation in space and/or time. Examples include the diurnal cycle and a convective boundary layer capped by a strong inversion. For such cases, large-eddy simulations using regular grids often have to rely on a subgrid-scale closure for the most challenging regions in the spatial and/or temporal domain. Here we analyze a flow configuration that describes the growth and subsequent decay of a convective boundary layer using direct numerical simulation (DNS). We validate the obtained results and benchmark the performance of the adaptive solver against two runs using fixed regular grids. It appears that the adaptive-mesh algorithm is able to coarsen and refine the grid dynamically whilst maintaining an accurate solution. In particular, during the initial growth of the convective boundary layer a high resolution is required compared to the subsequent stage of decaying turbulence. More specifically, the number of grid cells varies by two orders of magnitude over the course of the simulation. For this specific DNS case, the adaptive solver was not yet more efficient than the more traditional solver that is dedicated to these types of flows. However, the overall analysis shows that the method has a clear potential for numerical investigations of the most challenging atmospheric cases.
We have identified certain fundamental limitations of a mixing-length parametrization used in a popular turbulent kinetic energy-based subgrid-scale model. Replacing this parametrization with a more ...physically realistic one significantly improves the overall quality of the large-eddy simulation (LES) of stable boundary layers. For the range of grid sizes considered here (specifically, 1 m–12.5 m), the revision dramatically reduces the grid-size sensitivity of the simulations. Most importantly, the revised scheme allows us to reliably estimate the first- and second-order statistics of a well-known LES intercomparison case, even with a coarse grid size of O(10 m).
Subtropical marine low cloud sensitivity to an idealized climate change is compared in six large‐eddy simulation (LES) models as part of CGILS. July cloud cover is simulated at three locations over ...the subtropical northeast Pacific Ocean, which are typified by cold sea surface temperatures (SSTs) under well‐mixed stratocumulus, cool SSTs under decoupled stratocumulus, and shallow cumulus clouds overlying warmer SSTs. The idealized climate change includes a uniform 2 K SST increase with corresponding moist‐adiabatic warming aloft and subsidence changes, but no change in free‐tropospheric relative humidity, surface wind speed, or CO2. For each case, realistic advective forcings and boundary conditions are generated for the control and perturbed states which each LES runs for 10 days into a quasi‐steady state. For the control climate, the LESs correctly produce the expected cloud type at all three locations. With the perturbed forcings, all models simulate boundary‐layer deepening due to reduced subsidence in the warmer climate, with less deepening at the warm‐SST location due to regulation by precipitation. The models do not show a consistent response of liquid water path and albedo in the perturbed climate, though the majority predict cloud thickening (negative cloud feedback) at the cold‐SST location and slight cloud thinning (positive cloud feedback) at the cool‐SST and warm‐SST locations. In perturbed climate simulations at the cold‐SST location without the subsidence decrease, cloud albedo consistently decreases across the models. Thus, boundary‐layer cloud feedback on climate change involves compensating thermodynamic and dynamic effects of warming and may interact with patterns of subsidence change.
Key Points
Marine low cloud sensitivity to an idealized climate change is studied
The models do not show consistent cloud changes in the perturbed climate
Low cloud feedbacks involve cancellation between different effects of warming
Using a simple entraining plume model, an idealized deep convective environmental temperature profile is perturbed to analyze extreme precipitation scaling from a frequently used relation based on ...the column condensation rate. The plume model simulates a steady precipitation increase that is greater than ClausiusClapeyron scaling (super-CC scaling). Precipitation intensity increase is shown to be controlled by a flux of moisture through the cloud base and in-cloud lateral moisture convergence. Decomposition of this scaling relation into a dominant thermodynamic and additional dynamic component allows for better understanding of the scaling and demonstrates the importance of vertical velocity in both dynamic and thermodynamic scaling. Furthermore, systematically increasing the environmental stability by adjusting the temperature perturbations from constant to moist adiabatic increase reveals a dependence of the scaling on the change in environmental stability. As the perturbations become increasingly close to moist adiabatic, the scaling found by the entraining plume model decreases to CC scaling. Thus, atmospheric stability changes, which are expected to be dependent on the latitude, may well play a key role in the behavior of precipitation extremes in the future climate.
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.
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.
Plain Language Summary
The most detailed models of our atmosphere frequently have their clouds spontaneously organize into large clusters. Small clouds (less than a kilometer in size) seem to play an important role in such “self‐aggregation.” However, even in detailed models small clouds are hard to adequately capture: Typically, they must resolve the motions in these clouds using only a few pixels, thus requiring additional, lower‐accuracy models for cloudy motions smaller than the pixel size. Here, we show that merely varying the resolution of several state‐of‐the‐art atmospheric models has an effect on how quickly they predict the self‐aggregation of clouds to occur, even when many complex, uncertain processes are removed from the problem. We show that this results from inconsistencies in how the smallest, resolved motions are represented at various model resolutions, and hypothesize that these inconsistencies arise because our models for the unresolved motions control the vigor of the cloudy motions in different ways when the resolution changes. To help work out how important self‐aggregation is in the real world, models of the phenomenon may therefore require finer resolutions than previously thought, or better models for the unresolved motions.
Key Points
In large‐eddy simulations, sub‐kilometer scale cumulus convection self‐organizes into mesoscale structures through shallow circulations
The aggregation time‐scale does not converge with model resolution for typical discretization choices
Numerical representations of the tropical mesoscales may require finer model resolutions than previously thought
To quantify the turbulent transport at gray zone length scales between 1 and 10 km the Lagrangian evolution of the CONSTRAIN cold air outbreak (CAO) case was simulated with seven large eddy models. ...The case is characterized by rather large latent and sensible heat fluxes, and a rapid deepening rate of the boundary layer. In some models the entrainment velocity exceeds 4 cm/s. A significant fraction of this growth is attributed to a strong longwave radiative cooling of the inversion layer. The evolution and the timing of the breakup of the stratocumulus cloud deck differ significantly among the models. Sensitivity experiments demonstrate that a decrease in the prescribed cloud droplet number concentration, and the inclusion of ice microphysics, both act to speed up the thinning of the stratocumulus by enhancing the production of precipitation. In all models the formation of mesoscale fluctuations is clearly evident in the cloud fields but also in the horizontal wind velocity. Resolved vertical fluxes remain important for scales up to 10 km. The simulation results show that the resolved vertical velocity variance gradually diminishes with a coarsening of the horizontal mesh, but the total vertical fluxes of heat, moisture, and momentum are only weakly affected. This is a promising result as it demonstrates the potential use of a mesh size dependent turbulent length scale for convective boundary layers at gray zone model resolutions.
A new generation of operational atmospheric models operating at horizontal resolutions in the range 200 m ∼ 2 km is becoming increasingly popular for operational use in numerical weather prediction ...and climate applications. Such grid spacings are becoming sufficiently fine to resolve a fraction of the turbulent transports. Here we analyze Large‐eddy simulation results of a convective boundary layer obtained by coarsening horizontal grid spacings up to 800 m. The aim is to explore the dependency of the mean state and turbulent fluxes on the grid resolution. Both isotropic and anisotropic eddy diffusion approaches are evaluated, where in the latter case the horizontal and vertical eddy diffusivities differ in accord with their horizontal and vertical grid spacings. For coarsening horizontal grid sizes entrainment at the top of the boundary layer tends to get slightly enhanced for isotropic diffusion, whereas for the anisotropic diffusion approach the vertically well‐mixed boundary‐layer structure becomes severely degraded. An analysis of the energy spectrum shows that anisotropic diffusion causes relatively more dissipation of variance at smaller length scales. This leads, in turn, to a shift of spectral energy toward larger length scales that also becomes apparent from a rather different kind of spatial organization of convection. The present study therefore suggests that details with regards to the representation of processes at small scales might impact the organization at length scales much larger than the smallest scales that can be resolved by the model.
Plain Language Summary
A new generation of operational atmospheric models operating at horizontal resolutions in the range 200 m ∼ 2 km is becoming increasingly popular for operational use in numerical weather prediction and climate applications. Owing to ever increasing computational power their grid spacings are nowadays becoming sufficiently fine to allow for resolving a fraction of the turbulent transports. However, these types of models are operated with grid spacings that are much larger in the horizontal directions than in the vertical direction. In the present study we explore the extent to which the spatial organization of turbulence structures is affected by the size of the horizontal grid spacing. This question is addressed by means of large‐eddy simulation, which is an established modeling technique that has been designed specifically to resolve the dominant turbulent eddies at a high spatial resolution. It is found that differences in the way how turbulence at scales smaller than the grid spacing is calculated can have an effect on the organization of turbulent structures at much larger spatial scales.
Key Points
A grid anisotropy factor is introduced to efficiently switch from an isotropic to an anisotropic eddy diffusion approach for large‐eddy simulation models
The organization of clear boundary‐layer convection depends on the horizontal grid spacings, most notably for the anisotropic eddy diffusion approach
Reduced variances at the smallest length scales may be compensated by opposite increases at larger length scales
Results of four Lagrangian stratocumulus-to-shallow-cumulus transition cases as obtained from six different large-eddy simulation models are presented. The model output is remarkably consistent in ...terms of the representation of the evolution of the mean state, which is characterized by a stratocumulus cloud layer that rises with time and that warms and dries relative to the subcloud layer. Also, the effect of the diurnal insolation on cloud-top entrainment and the moisture flux at the top of the subcloud layer are consistently captured by the models. For some cases, the models diverge in terms of the liquid water path (LWP) during nighttime, which can be explained from the difference in the sign of the buoyancy flux at cloud base. If the subcloud buoyancy fluxes are positive, turbulence sustains a vertically well-mixed layer, causing a cloud layer that is relatively cold and moist and consequently has a high LWP. After some simulation time, all cases exhibit subcloud-layer dynamics that appear to be similar to those of the dry convective boundary layer. The humidity flux from the subcloud layer toward the stratocumulus cloud layer, which is one of the major sources of stratocumulus cloud liquid water, is larger during the night than during the day. The sensible heat flux becomes constant in time, whereas the latent heat flux tends to increase during the transition. These findings are explained from a budget analysis of the subcloud layer.
Abstract
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 >
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(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
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(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.
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