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Urban heat islands (UHIs) are enhanced temperatures in urban regions (Oke, 1982). • UHIs are studied fairly well for larger cities, but there is a knowledge gap in the extent of UHI effects in smaller or moderately-sized cities such as Augusta, GA. • Four different types of UHI: • Surface • Canopy Layer • Hydrological • Boundary Layer
In this work, we investigate the ability of mesoscale and large-eddy simulation (LES) model configurations to predict the mean wind speed profile within the boundary layer of tropical cyclones (TCs). To this end, we perform idealized simulations of five hypothetical intense storms ranging from categories 1 to 5 on the Saffir–Simpson scale and extract time-averaged quantities near the eyewall region. We compare the model-generated data against mean wind speed profiles compiled from dropsondes launched from reconnaissance aircraft operating in the North Atlantic basin. Our analysis shows that mesoscale- and LES-generated mean wind fields display important differences in the boundary layer, including the magnitude of shear as well as the height where their low-level wind speed maxima are located. In addition, a comparison between the two model configurations with the dropsonde data shows that both modeling approaches are unable to capture the typical structure of mean winds in the lower part of the TC boundary layer (10–500 m), calling into question the use of simulations of near-axisymmetric storms for investigating the wind structure of past events. To better understand these differences, we conduct a momentum-budget analysis and show that modeled turbulent fluxes are underestimated in the mesoscale boundary layer parameterization compared to the LES model. Based on the analysis of the horizontal turbulent fluxes and their potential impact on mean flow quantities, a TC-specific boundary layer parameterization may be needed.
The Doppler lidar (DL) is an active remote-sensing instrument that provides range- and time-resolved measurements of the line-of-sight component of air velocity (i.e., radial velocity) and attenuated aerosol backscatter. The DL operates in the near-infrared and is sensitive to backscatter from atmospheric aerosol, which are assumed to be ideal tracers of atmospheric wind fields. The DL works by transmitting short pulses of infrared laser light into the atmosphere. Atmospheric aerosols scatter a small fraction of that light energy back to the transceiver, where it is collected and recorded as a time-resolved signal. From the delay between the outgoing pulse and the backscattered signal, the instrument infers the distance to the scattering volume. Coherent detection is used to measure the Doppler frequency shift of the backscatter signal. This is accomplished by mixing the backscatter signal with a reference laser beam (i.e., local oscillator) of known frequency. The onboard signal processor then determines the Doppler frequency shift from the spectrum of the mixed signal. The Doppler frequency shift and thus the radial air velocity is determined from the peak of the Doppler spectrum. The attenuated backscatter is determined from the energy content of the Doppler spectra. The DL provides accurate measurements of radial velocity in regions of the atmosphere where aerosol concentrations are high enough to ensure good signal-to-noise ratio. Thus, valid data are usually limited to the atmospheric boundary layer where aerosol is ubiquitous. Valid measurements can also be obtained in elevated aerosol layers or in optically thin clouds above the boundary layer. Most of the ARM DLs have full upper-hemispheric scanning capability, enabling 3D mapping of turbulent flows in the atmospheric boundary layer. With the scanner pointed vertically, the DL provides height- and time-resolved measurements of vertical velocity.
Abstract. The mean altitude of the smoke loading over the southeast Atlantic moves from the boundary layer in July to the free troposphere by October. This study details the month-by-month changes in cloud properties and the large-scale environment as a function of the biomass burning aerosol loading at Ascension Island (8∘ S, 14.5∘ W) from July to October, based on island measurements, satellite retrievals, and reanalysis. In July and August, the smoke loading predominantly varies within the boundary layer. During both months, the low-cloud fraction is less and is increasingly cumuliform when more smoke is present, with the exception of a late morning boundary layer deepening that encourages a short-lived cloud development. The meteorology varies little, suggesting aerosol–cloud interactions explain the cloudiness changes. September marks a transition month during which midlatitude disturbances can intrude into the Atlantic subtropics, constraining the free tropospheric aerosol closer to the African coast. Stronger boundary layer winds on cleaner days help deepen, dry, and cool much of the marine boundary layer compared to that on days with high smoke loadings, with stratocumulus reducing everywhere but at the northern deck edge. The September free troposphere is better mixed on smoky days compared to October. Longwave cooling rates, generated by a sharp water vapor gradient at the aerosol layer top, encourage a small-scale vertical mixing that could help maintain the well-mixed smoky September free troposphere. The October meteorology primarily varies as a function of the strength of the free tropospheric winds advecting aerosol offshore. The free tropospheric aerosol loading is less than in September, and the moisture variability is greater. Low-level clouds increase and are more stratiform in October when the smoke loadings are higher. The increased free tropospheric moisture can help sustain the clouds through a reduction in evaporative drying during cloud-top entrainment. Enhanced subsidence above the coastal upwelling region, increasing cloud droplet number concentrations, may further prolong cloud lifetime through microphysical interactions. Reduced subsidence underneath stronger free tropospheric winds at Ascension Island supports slightly higher cloud tops during smokier conditions. Overall, the monthly changes in the large-scale aerosol and moisture vertical structure act to amplify the seasonal cycle in low-cloud amount and morphology. This is climatically important, as cloudiness changes dominate changes in the top-of-atmosphere radiation budget.
Tropical convection over rainforests modulates atmospheric circulation and the energy and hydrological cycles across multiple scales. However, the scarcity of observations still limits our understanding of these processes. Although numerical models are utilized to investigate atmospheric physical processes, their performance depends on the choice of parameterizations and grid resolution. Here, in this work, we introduce and apply a multi‐variable, multi‐physics framework to evaluate and rank the Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1‐km resolution over the central Amazon during the wet season. A 48‐member ensemble combines three land‐surface models (LSMs), four planetary boundary layer (PBL), and four microphysics (MP) schemes. Model performance for seven convection‐related near‐surface and boundary‐layer variables is assessed using Taylor diagrams and the Taylor skill score (TSS), analysis of variance (ANOVA)‐based sensitivity metrics, and non‐parametric rank tests. We then construct a combined, weighted TSS to identify configurations that are comparatively robust across variables. Results showed that most configurations reproduce near‐surface temperature, sensible and latent heat fluxes, and boundary‐layer height reasonably well, whereas humidity and rainfall remain challenging. LSM choice has the strongest impact on the surface fluxes and a secondary influence on near‐surface temperature and humidity, PBL schemes dominate boundary‐layer height, and MP schemes exert the largest control on rainfall. No single configuration is optimal for all variables, but the combination of Noah (LSM), Yonsei University (PBL), and Morrison (MP) emerges as the most robust configuration for this case, with the WRF single‐moment six‐class scheme (WSM6) providing a competitive, computationally cheaper MP alternative. The framework is general and can be applied to other regions, seasons, and convective regimes.
Water availability at the Earth surface determines the portioning of the surface heat flux into its sensible and latent components, that is, the surface heat flux Bowen ratio. The two components affect differently the surface buoyancy flux and thus the development and growth of the convective boundary layer. As a result, the Bowen ratio has a strong impact on the daytime dry and moist convection development over land. Here, we use two canonical modeling test cases, one for the shallow convection and one for the shallow-to-deep convection transition, to document the impact of the surface Bowen ratio on daytime convection development. A simple approach is used where results from simulations featuring the original setup are contrasted with simulations where surface sensible heat flux takes on values of the latent heat flux and vice versa. Such a change illustrates the key impact of the surface water availability without changing the total surface heat flux. Because of the larger surface buoyancy flux, simulations with the reversed surface heat fluxes feature faster deepening of the convective boundary layer and wider clouds once moist convection develops. Mean cloud base width of cumulus clouds increases with the boundary layer depth. For shallow-to-deep convection transition, comparison of simulations with the observed large-scale flow that feature substantial lower-tropospheric shear with simulations with no mean horizontal flow suggests that the organization of convective circulations within the boundary layer strongly affects initial size and organization of shallow convection, as well as the subsequent width increase once convection deepens and eventually transitions to deep precipitating convection. A simple explanation is provided of why deeper well-mixed convective subcloud layer results in wider clouds. The key is the larger width of boundary layer coherent updraft structures when the mixed layer is deeper.
Marine cloud systems cover a substantial portion of the world’s oceans. Most of these clouds form relatively close to the ocean surface, typically within one to two kilometers, a region referred to by meteorologists as the marine boundary layer. They are composed predominantly of liquid water, although ice particles can occur in mid- and high-latitude marine clouds during winter. In satellite imagery, these clouds appear bright against the darker ocean surface below, reflecting a large fraction of incoming sunlight back into space that would otherwise warm the ocean. Because marine boundary layer clouds cover such an extensive area of the ocean, they exert a significant influence on Earth’s overall transfer of solar energy absorbed by the surface and thermal energy emitted to space, a balance known as the planetary radiation budget. Marine boundary layer clouds are typically thin, and their formation and dissipation depend on a delicate balance between processes acting at the ocean surface below and the warm, dry air above. They are notoriously difficult to simulate accurately in weather forecast models, which often produce too few marine low clouds in midlatitudes and clouds in tropical regions that are excessively bright, meaning they reflect too much solar radiation. The marine boundary layer is frequently characterized by widespread overcast cloud cover that often transitions from a continuous, single-layer deck to more broken cloud fields toward the tropics. These transitions typically proceed through an intermediate stage in which shallow, broken clouds form beneath the overlying stratiform cloud deck. Once broken clouds develop below the overcast, they frequently self-organize into cloud clusters known as marine boundary layer convective complexes (MBLCCs), although the mechanisms governing the formation and organization of MBLCCs remain poorly understood. Accurately representing these transitions in long-range weather forecast models is essential because they influence the properties of air masses advected over the continental United States and Europe, and they become increasingly important for forecasts on seasonal and longer timescales. We employed two complementary approaches to investigate the processes controlling MBLCCs and their impact on marine cloud cover. Long-term observations from the U.S. Department of Energy’s Eastern North Atlantic (ENA) Observatory provided a unique dataset that allowed us to characterize fundamental properties of MBLCCs, including their typical size and frequency of occurrence. These observations were combined with high-resolution numerical simulations performed on supercomputers to examine the evolution of MBLCCs during cold-air outbreaks over the ENA region.
It is shown that externally magnetized gas-puff z-pinches under compression can exhibit robust axial flux amplification under suitable axial boundary conditions. This effect relies upon the Hall term in the generalized Ohm's law to generate azimuthal currents in the presence of a driving axial electric field. Under dynamic compression, the total current tends to flow in a mostly force-free boundary layer, separating the predominately azimuthal field outside the layer and the predominately axial field inside the layer. The effect only appears to occur if the axial boundaries allow for outflow or absorption of electromagnetic energy. The effect is mitigated by imposing either periodic or conducting axial boundary conditions. A semi-analytic equilibrium analysis agrees with steady-state solutions of the time-dependent electron-magnetohydrodynamic equations and provides an estimate of the scaling of the boundary layer as well as suggesting a scenario for the formation of the boundary layer. When operative, the effect can significantly impede plasma compression due to the increase in axial flux that diffuses into the pre-compressed plasma or through the presence of conductors that inhibit movement of the generated axial flux. Several facilities have noted unusual implosion behavior in z-pinch experiments with applied axial fields that does not appear to be explainable within the standard magnetohydrodynamic model. In conclusion, it is suggested that these experiments can be explained by the axial flux amplification and concentration effect
Land-atmosphere interactions play a critical role in the evolution and formation of low-level clouds. The different states of coupling between low-level clouds and the surface are uncertain, primarily over continental regions, where complex thermodynamics complicates their investigation. This study uses observations from the Atmospheric Radiation Measurement User Facility to explore cloud-surface coupling and perform a climatological analysis of this interaction in five countries across three continents. The results reveal consistent coupling thresholds and average percentages across the five sites, with coupled clouds accounting for 66% of the cases and decoupled clouds for 34%. Thermodynamic and dynamic evaluations show distinct differences between coupled and decoupled clouds. Coupled clouds are characterized by humid environments, in which vertical motions connect the surface and lower atmosphere to the cloud base, conditions that favor the formation of boundary layer clouds. Decoupled clouds prefer to occur in a drier and colder environment with vertical motions inside the boundary layer being detached from the cloud base, under which boundary layer clouds are hard to form. Coupled clouds peak during warmer hours and seasons, and vice versa for decoupled clouds. This study underscores the complexity of cloud-land-surface interactions and paves the way for further investigations into cloud formation and evolution under different atmospheric environments.
Abstract. The eastern North Atlantic (ENA) is a region dominated by pristine marine environment and subtropical marine boundary layer clouds. Under unperturbed atmospheric conditions, the regional aerosol regime in the ENA varies seasonally due to different seasonal surface-ocean biogenic emissions, removal processes, and meteorological regimes. However, during periods when the marine boundary layer aerosol in the ENA is impacted by particles transported from continental sources, aerosol properties within the marine boundary layer change significantly, affecting the concentration of cloud condensation nuclei (CCN). Here, we investigate the impact of long-range transported continental aerosol on the regional aerosol regime in the ENA using data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility on Graciosa Island in 2017 during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign. We develop an algorithm that integrates number concentrations of particles with optical particle dry diameter (Dp) between 100 and 1000 nm, single scattering albedo, and black carbon concentration to identify multiday events (with duration >24 consecutive hours) of long-range continental aerosol transport in the ENA. In 2017, we detected nine multiday events of long-range transported particles that correspond to ∼ 7.5 % of the year. For each event, we perform HYSPLIT 10 d backward trajectories analysis, and we evaluate CALIPSO aerosol products to assess, respectively, the origins and compositions of aerosol particles arriving at the ENA site. Subsequently, we group the events into three categories, (1) mixture of dust and marine aerosols, (2) mixture of marine and polluted continental aerosols from industrialized areas, and (3) biomass burning aerosol from North America and Canada, and we evaluate their influence on aerosol population and cloud condensation nuclei in terms of potential activation fraction and concentrations at supersaturation of 0.1 % and 0.2 %. The arrival of plumes dominated by the mixture of dust and marine aerosol in the ENA in the winter caused significant increases in baseline Ntot. Simultaneously, the baseline particle size modes and CCN potential activation fraction remained almost unvaried, while cloud condensation nuclei concentrations increased proportionally to Ntot. Events dominated by a mixture of marine and polluted continental aerosols in spring, fall, and winter led to a statistically significant increase in baseline Ntot, a shift towards larger particular sizes, a higher CCN potential activation fractions, and cloud condensation nuclei concentrations of >170 % and up to 240 % higher than during baseline regime. Finally, the transported aerosol plumes characterized by elevated concentration of biomass burning aerosol from continental wildfires detected in the summertime did not statistically contribute to increase baseline aerosol particle concentrations in the ENA. However, particle diameters were larger than under baseline conditions, and CCN potential activation fractions were >75 % higher. Consequentially, cloud concentration nuclei concentrations increased by ∼ 115 % during the period affected by the biomass burning events. Our results suggest that, through the year, multiday events of long-range continental aerosol transport periodically affect the ENA and represent a significant source of CCN in the marine boundary layer. Based on our analysis, in 2017, the multiday aerosol plume transport dominated by a mixture of dust and marine aerosol, a mixture of marine and polluted continental aerosols, and biomass burning aerosols caused increases in the NCCN baseline regime of, respectively, 6.6 %, 8 %, and 7.4 % at SS 0.1 % (and, respectively, 6.5 %, 8.2 %, and 7.3 % at SS 0.2 %) in the ENA.
Abstract Flows in the atmospheric boundary layer are turbulent, characterized by a large Reynolds number, the existence of a roughness sublayer and the absence of a well-defined viscous layer. Exchanges with the surface are therefore dominated by turbulent fluxes. In numerical models for atmospheric flows, turbulent fluxes must be specified at the surface; however, surface fluxes are not known a priori and therefore must be parametrized. Atmospheric flow models, including global circulation, limited area models, and large-eddy simulation, employ Monin–Obukhov similarity theory (MOST) to parametrize surface fluxes. The MOST approach is a semi-empirical formulation that accounts for atmospheric stability effects through universal stability functions. The stability functions are determined based on limited observations using simple regression as a function of the non-dimensional stability parameter representing a ratio of distance from the surface and the Obukhov length scale (Obukhov in Trudy Inst Theor Geofiz AN SSSR 1:95–115, 1946), $$z/L$$ z / L . However, simple regression cannot capture the relationship between governing parameters and surface-layer structure under the wide range of conditions to which MOST is commonly applied. We therefore develop, train, and test two machine-learning models, an artificial neural network (ANN) and random forest (RF), to estimate surface fluxes of momentum, sensible heat, and moisture based on surface and near-surface observations. To train and test these machine-learning algorithms, we use several years of observations from the Cabauw mast in the Netherlands and from the National Oceanic and Atmospheric Administration’s Field Research Division tower in Idaho. The RF and ANN models outperform MOST. Even when we train the RF and ANN on one set of data and apply them to the second set, they provide more accurate estimates of all of the fluxes compared to MOST. Estimates of sensible heat and moisture fluxes are significantly improved, and model interpretability techniques highlight the logical physical relationships we expect in surface-layer processes.
Here we present an error analysis for the discontinuous Galerkin (DG) method applied to the discrete-ordinate discretization of the steady-state radiative transfer equation with isotropic scattering. Under some mild assumptions, we show that the DG method converges uniformly with respect to a scaling parameter which characterizes the strength of scattering in the system. However, the rate is not optimal and can be polluted by the presence of boundary layers. In one-dimensional slab geometries, we demonstrate optimal convergence when boundary layers are not present and analyze a simple strategy for balance interior and boundary layer errors. Some numerical tests are also provided in this reduced setting.
Two stratus lowering marine fog events observed on 28 September and 04 October 2018 during the Coastal Fog (C-Fog) field campaign that took place offshore of Eastern Canada during 1 September to 6 October 2018 are described. In-situ, profiling and remote sensing observations were made at selected land sites in eastern Newfoundland (NL) and Nova Scotia (NS) as well as aboard the research vessel (R/V) Hugh R. Sharp that cruised in adjoining coastal waters. Synoptic scale analysis showed that both fog episodes were an outcome of the interaction between synoptic-scale surface level low-pressure systems and a contiguous high-pressure system. At the same time, back trajectories revealed that the bulk of the fog layer is formed due to differential advection. Here, the diameter of the fog droplets at the surface gradually decreased from the centre of the fog layer to its leading/trailing edges. The bimodal fog droplet diameter distribution with peaks at 5-10 µm and 20-25 µm provided clues on droplet collision and coalescence processes. The observed difference between microphysical variables and droplet distribution between the two fog events and within same fog layer may have been governed by atmospheric boundary layer conditions (e.g., humidity conditions and turbulence) prevailed in the fog layer. Overall, it is concluded that the life cycle of observed stratus-lowering coastal-fog episodes is dependent on synoptic conditions as well as atmospheric boundary layer characteristics such as stability, cloud top cooling and entrainment.
Cascade catalysis for photoelectrochemical CO 2 reduction (CO 2 R) decouples the overall reaction into sequential steps occurring on separately optimized catalysts (for example, Ag and Cu) between which an intermediate species such as CO is transferred. A 3-terminal tandem (3TT) photovoltaic architecture advantageously holds two different catalytic regions at different potentials under a single illumination source, but its overall efficiency is low. Using a stochastic reaction-diffusion model, we have examined 3TT photocathode design principles, focusing on the coupling of surface chemistry and transport of CO both inside the boundary layer and outward, into the bulk electrolyte. We find that ensuring that the lateral diffusion distance within the boundary layer is short compared to the boundary layer thickness and controlling bulk flow are key, with interdigitated designs showing an overall conversion efficiency improvement by 2 orders of magnitude compared to the side-by-side case without flow. These findings can be adapted for other cascaded architectures.
Boundary-layer cloud interactions involving shortwave-absorbing aerosols remain one of the least understood aerosol influences on climate. Here, we find the highest stratocumulus cloud droplet number concentrations over the southeast Atlantic occur when agricultural fires coincide with synoptically-weakened surface warming over Angola, occurring June-early August. Dry convection fills a shallow continental boundary layer with smoke, and a nighttime (local solar time 2-9) land breeze transports the aerosol into the marine boundary layer. Offshore aerosol transport is strengthened by low-level easterlies from a continental pressure high southeast of Angola. Simultaneously, the South Atlantic subtropical high is weaker, allowing extensive dispersal of aerosol offshore into the boundary layer, obscuring cloud brightening from shipping. Meteorological co-variation at synoptic scales compensates for cloud brightening by the smoke. Outgoing shortwave radiation increases by 15–20% of the monthly mean in June and July when offshore droplet numbers are less but the stratocumulus deck is more developed.
Low-level clouds are ubiquitous over the oceans, and their impact on the Earth’ radiative budget is important. However, general circulation models (GCMs) that are used to represent our climate and its evolution still experience problems to represent their correct amount and radiative impact. In the extratropical latitudes (~30-60 N/S), cloud properties are strongly modulated by the occurrence of anti-cyclones (high pressure systems) and cyclones (low pressure systems). While deep clouds dominate in cyclones near the center and along the cold and warm fronts, low-level clouds populate the colder regions of the cyclones, and more specifically the region in the wake of the cold fronts, the post-cold frontal region (PCF). The GCMs mentioned above were found to underestimate the amount of these PCF clouds, and this caused errors in their representation of the amount of solar radiation at the surface of the southern hemisphere oceans, causing an excess in absorption and errors in long-term predictions. To better understand which processes are ill-represented in the GCMs to cause such issues, we used ground-based observations from the Eastern North Atlantic (ENA) ARM site and a high resolution regional model (called WRF) to examine the properties of PCF clouds. With the WRF model, we simulated the passage of a cold front at the ENA site using theoretically distinct representations of convection and the physics of the boundary layer. While these physical representations had little impact on the timing, structure and circulation of the cold front, we found a high sensitivity to how the large scale information was fed into the model. Errors rapidly developed if the incoming flow information was injected too far from the site, but 1000 km was found to be an optimal distance between the outer boundary and the ENA site for a realistic cold front passage. With this model, we then conducted a series of experiment where convection and boundary layer schemes were changed, and revealed that 1) the clouds were more sensitive to the convection than boundary layer schemes and 2) the interaction between the two has a large impact. Furthermore, changing the representation of the physics in the model had greater impacts on PCF clouds than changing the initial conditions. As large-scale models increase their spatial resolution, convection will eventually be resolved but it remains that their representation of the physics of the boundary layer will matter for the correct representation of shallow (low-level) clouds. Observations were used to find which large-scale information had a clear relationship with PCF cloud and precipitation properties, in view of helping with GCM parameterizations and evaluation. Both lower troposphere stability and surface forcing were found to be important for PCF clouds that experience more vigorous dynamics than their tropical or subtropical counterparts. For cloud base and top heights, a simple measure of the change in potential temperature between the surface and the 800 hPa was found to be a good predictor. This relationship was found to hold as well when using data from campaigns recently conducted in the southern ocean south of Tasmania. A recent GCM was found to succeed in representing similar relations. For cloud depth, water content, and different characteristics of precipitation both the temperature contrast between the surface and near-air and the near-surface wind speed had a strong relationship. To summarize, through observational constraints and regional model experiments, the project has provided guidance to evaluate GCMs and tools to improve their representation of low-level clouds in the extratropics. It has also highlighted differences in behavior between these clouds and those typically found in the subtropics, thus opening new avenues of research for shallow clouds in general.
This study assesses a 40-day 3.25-km global simulation of the Simple Cloud-Resolving E3SM Model (SCREAMv0) using high-resolution ground-based observations from the Atmospheric Radiation Measurement (ARM) Green Ocean Amazon (GoAmazon) field campaign. SCREAMv0 reasonably captures the diurnal timing of boundary layer clouds yet underestimates the boundary layer cloud fraction and mid-level congestus. SCREAMv0 well replicates the precipitation diurnal cycle, however it exhibits biases in the precipitation cluster size distribution compared to scanning radar observations. Specifically, SCREAMv0 overproduces clusters smaller than 128 km, and does not form enough large clusters. Such biases suggest an inhibition of convective upscale growth, preventing isolated deep convective clusters from evolving into larger mesoscale systems. This model bias is partially attributed to the misrepresentation of land-atmosphere coupling. This study highlights the potential use of high-resolution ground-based observations to diagnose convective processes in global storm resolving model simulations, identify key model deficiencies, and guide future process-oriented model sensitivity tests and detailed analyses.
We demonstrate conditions that give rise to cave-like features commonly found in dissolving cliffsides with a minimal two-phase physical model. Alcoves that are wider at the top and tapered at the bottom, with sharp-edged ceilings and sloping floors, are shown to develop on vertical solid surfaces dissolving in aqueous solvents. As evident from descending plumes, sufficiently large indentations evolve into alcoves as a result of the faster dissolution of the ceiling due to a solutal Rayleigh–Bénard density inversion instability. In contrast, defects of size below the boundary layer thickness set by the critical Rayleigh number smooth out, leading to stable planar interfaces. Furthermore, the ceiling recession rate and the alcove opening area evolution are shown to be given to first-order by the critical Rayleigh number. By tracking passive tracers in the fluid phase, we show that the alcoves are shaped by the detachment of the boundary layer flow and the appearance of a pinned vortex at the leading edge of the indentations. The attached boundary layer past the developing alcove is then found to lead to rounding of the other sides and the gradual sloping of the floor.