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In radiative-convective equilibrium simulations, convective self-aggregation (CSA) is the spontaneous organization into segregated cloudy and cloud-free regions. Evidence exists for how CSA is stabilized, but how it arises favorably on large domains is not settled. Using large-eddy simulations, we link the spatial organization emerging from the interaction of cold pools (CPs) to CSA. We systematically weaken simulated rain evaporation to reduce maximal CP radii, R_{max}, and find reducing R_{max} causes CSA to occur earlier. We further identify a typical rain cell generation time and a minimum radius, R_{min}, around a given rain cell, within which the formation of subsequent rain cells is suppressed. Incorporating R_{min} and R_{max}, we propose a toy model that captures how CSA arises earlier on large domains: when two CPs of radii r_i,r_j ∈ [R_{min}, R_{max}] collide, they form a new convective event. These findings imply that interactions between CPs may explain the initial stages of CSA. In radiative-convective equilibrium simulations, convective self-aggregation (CSA) is the spontaneous organization into segregated cloudy and cloud-free regions. Evidence exists for how CSA is stabilized, but how it arises favorably on large domains is not settled. Using large-eddy simulations, we link the spatial organization emerging from the interaction of cold pools (CPs) to CSA. We systematically weaken simulated rain evaporation to reduce maximal CP radii, R_{max}, and find reducing R_{max} causes CSA to occur earlier. We further identify a typical rain cell generation time and a minimum radius, R_{min}, around a given rain cell, within which the formation of subsequent rain cells is suppressed. Incorporating R_{min} and R_{max}, we propose a toy model that captures how CSA arises earlier on large domains: when two CPs of radii r_i,r_j ∈ [R_{min}, R_{max}] collide, they form a new convective event. These findings imply that interactions between CPs may explain the initial stages of CSA.

Clustering of tropical thunderstorms constitutes an important climate feedback because it influences the heat radiated to space. Convective self-aggregation (CSA) is a profound modelling paradigm for explaining the clustering of tropical oceanic thunderstorms. However, CSA is hampered in the realistic limit of fine model resolution when cold pools -- dense air masses beneath thunderstorm clouds -- are well-resolved. Studies on CSA usually assume the surface temperature to be constant, despite realistic surface temperatures varying significantly between night and day, even over the sea. Here we mimic oscillating surface temperatures in cloud resolving numerical experiments and show that, in the presence of a diurnal cycle, CSA is enabled by high resolutions. We attribute this finding to vigorous combined cold pools emerging in symbiosis with mesoscale convective systems. Such cold pools suppress buoyancy in extended regions ($\mathbf{\sim 100}$ km) and enable the formation of persistent dry patches. Our findings help clarify how the tropical cloud field forms sustained clusters under realistic conditions and may have implications for the origin of extreme thunderstorm rainfall and tropical cyclones., 12 pages, 4 figures, 1 table + 5 supplementary take up one additional page each

Convective self-aggregation (CSA) is an established modelling paradigm for large-scale thunderstorm clusters, as they form in mesoscale convective systems, the Madden-JulianOscillation or tropical cyclo-genesis [1]. The onset of CSA is characterized by the spontaneous formation of persistently dry patches with suppressed deep convective rainfall. Recently another type of spatio-temporal pattern formation was observed in simulations where the diurnal cycle was mimicked by a sinusoidally varying surface temperature [2]. This diurnal aggregation (DA) is characterized by clusters of intense rain that correlate negatively from one day to the next. Here we demonstrate that the diurnal cycle can also act as a trigger of persistently dry patches resembling the early stages of CSA. When the surface temperature is held constant, CSA has been shown to occur within simulations of coarse horizontal model resolution, but not when the resolution was increased [3]. We show that, when a temporally periodic surface temperature forcing is imposed, persistently convection free patches occur even faster when the spatial resolution is increased. The failure to achieve CSA at high horizontal resolution has so far been attributed to the more pronounced cold pool effects at such resolution. In our simulations these cold pools in fact play a key role in promoting CSA. Our results have implications for the origin of persistent convective organization over continents and the sea — and point a path towards achieving such clustering under realistic conditions.[1] Christopher S Bretherton, Peter N Blossey, and Marat Khairoutdinov. An energy-balance analysisof deep convective self-aggregation above uniform SST.Journal of the Atmospheric Sciences, 62(12):4273–4292, 2005.[2] J. O. Haerter, B. Meyer, and S. B. Nissen. Diurnal self-aggregation.npj Climate and AtmosphericScience, 3:30, 2020.[3] Caroline Muller and Sandrine Bony. What favors convective aggregation and why?GeophysicalResearch Letters, 42(13):5626–5634, 2015. doi: https://doi.org/10.1002/2015GL064260.

Spontaneous aggregation of clouds is a puzzling phenomenon observed in field studies [Holloway et al. (2017)] and idealized simulations alike [Held et al. (1993), Bretherton et al. (2005)]. With its relevance to climate sensitivity and extreme events, aggregation continues to be heavily studied, [Wing et al., 2017 for a review], with radiative-convective feedbacks emerging as main drivers of simulated convective self-aggregation (CSA) [Mueller & Bony (2015)].In state-of-the art cloud-resolving models, CSA finds itself consistently hampered by finer horizontal resolutions [Muller & Held (2012), Yanase et al. (2020)]. This feature was ascribed to the effect of cold pool (CP) gust fronts in opposing the positive moisture feedback underlying CSA [Jeevanjee & Romps (2013)]. In contrast, recent numerical experiments [Haerter et al. (2020)] with diurnally oscillating surface temperature highlights an orthogonal effect: stronger CPs, driven by small-scale density gradients, promote cloud field self-organization into mesoscale convective systems (MCS). Interestingly, this upscale growth, which we here term diurnal self-organisation (DSO), differs from classical CSA as it is driven by CPs rather than large-scale radiative imbalances. In stark contrast to CSA, strengthening CPs promotes this organization effect.Hence, numerical simulations of CSA and DSO should go beyond the typical cloud-resolving paradigm and achieve cold pool-resolving capabilities. The current study systematically examines the impact of model resolution on CP effects. First, numerical convergence is probed in a 12km x 20km laterally periodic domain where a single CP propagates and self-collides at the domain's edges. As the spatial resolution is stepwise increased from 250 to 25m, it is shown that the initially coarsely resolved density current dissipates and collision and updraft effects are weak. As finer resolution is approached, we identify a cold pool resolving resolution D, which is deemed satisfactory for propagation and collision properties. Second, convergence for a (250km)2 domain under a diurnal radiative cycle is assessed at various spatial resolutions, including the scale D. This mesoscale configuration allows us to quantify the impact of resolution of cold pool dynamics on DSO.Together, this work systematically lays out the numerical requirements to study mesoscale clustering by means of explicit numerical simulations.

Convective self-aggregation is a modelling paradigm for thunderstorm organisation over a constant-temperature tropical sea surface. This setup can give rise to cloud clusters over timescales of weeks. In reality, sea surface temperatures do oscillate diurnally, affecting the atmospheric state. Over land, surface temperatures vary more strongly, and rain rate is significantly influenced. Here, we carry out a substantial suite of cloud-resolving numerical experiments, and find that even weak surface temperature oscillations enable qualitatively different dynamics to emerge: the spatial distribution of rainfall is only homogeneous during the first day. Already on the second day, the rain field is firmly structured. In later days, the clustering becomes stronger and alternates from day-to-day. We show that these features are robust to changes in resolution, domain size, and surface temperature, but can be removed by a reduction of the amplitude of oscillation, suggesting a transition to a clustered state. Maximal clustering occurs at a scale of $\mathbf{l_{max}\approx 180\;km}$, a scale we relate to the emergence of mesoscale convective systems. At $\mathbf{l_{max}}$ rainfall is strongly enhanced and far exceeds the rainfall expected at random. We explain the transition to clustering using simple conceptual modelling. Our results may help clarify how continental extremes build up and how cloud clustering over the tropical ocean could emerge much faster than through conventional self-aggregation alone., 27 pages, 4 main figures, 7 supplementary figures, 2 main tables, 1 supplementary table

Self-aggregation of convective cloud activity has attracted a lot of attention due to its role in the emergence of large scale weather phenomena such as the formation of hurricanes. Simulations with uniform boundary conditions show self-aggregation ocurring on the time-scale of a few weeks [1]. Recently, numerical experiments demonstrated that spatial clustering can form withing a few days, when the system is driven by diurnal temperature oscillations [2]. These simulations indicate that there may be a discontinuous phase transition between the clustered and the non-clustered state, i.e. that a threshold for the amplitudes of diurnal temperature oscillations exist, below which clustering does not emerge. A conceptual model has been proposed, suggesting that the phase transition might give rise to hysteresis in the sense that clustering emerging at high temperature amplitudes might persist if the amplitude is subsequently reduced to a level below the critical threshold.Here we test the hysteresis–hypothesis explicitly by performing cloud-resolving simulations with a high-amplitude transient period followed by a period with a low diurnal temperature amplitude. In reality, diurnal temperature oscillations have significantly larger amplitudes over land than over the ocean. The existence of hysteresis effects in the convective cloud clustering could have profound implications: clusters formed over land, where diurnal temperature variations are large, could persist over the ocean when transported there by large-scale wind advection. Once present, the clusters could even intensify over the ocean—with possible implications for cyclogenesis.[1] CJ Muller and IM Held, Journal of the Atmospheric Sciences, 69(8):2551–2565, 2012.[2] arXiv:2001.04740 [physics.ao-ph]

In radiative-convective equilibrium (RCE) simulations, convective self-aggregation (CSA) is the spontaneous organization into segregated cloudy and cloud-free regions. Evidence exists for how CSA is stabilized, but how it arises favorably on large domains is not settled. Using large-eddy simulations (LES), we link the spatial organization emerging from the interaction of cold pools (CPs) to CSA. We systematically weaken simulated rain evaporation to reduce maximal CP radii, $R_{\text{max}}$, and find reducing $R_{\text{max}}$ causes CSA to occur earlier. We further identify a typical rain cell generation time and a minimum radius, $R_{\text{min}}$, around a given rain cell, within which the formation of subsequent rain cells is suppressed. Incorporating $R_{\text{min}}$ and $R_{\text{max}}$, we propose a toy model that captures how CSA arises earlier on large domains: when two CPs of radii $r_{i,j}\in[R_{\text{min}},R_{\text{max}}]$ collide, they form a new convective event. These findings imply that interactions between CPs may explain the initial stages of CSA., 17 pages, 5 main figures, 4 supplementary figures

Convective self-aggregation is when thunderstorm clouds cluster over a constant temperature surface in radiative convective equilibrium. Self-aggregation was implicated in the Madden-Julian Oscillation and hurricanes. Yet, numerical simulations succeed or fail at producing self-aggregation, depending on modeling choices. Common explanations for self-aggregation invoke radiative effects, acting to concentrate moisture in a sub-domain. Interaction between cold pools, caused by rain evaporation, drives reorganization of boundary layer moisture and triggers new updrafts. We propose a simple model for aggregation by cold pool interaction, assuming a local number density $\rho(\mathbf{r})$ of precipitation cells, and that interaction scales quadratically with $\rho(\mathbf{r})$. Our model mimics global energy constraints by limiting further cell production when many cells are present. The phase diagram shows a continuous phase transition between a continuum and an aggregated state. Strong cold pool-cold pool interaction gives a uniform convective phase, while weak interaction yields few and independent cells. Segregation results for intermediate interaction strength.

In a changing climate, a key role may be played by the response of convective-type cloud and precipitation to temperature changes. Yet, it is unclear if precipitation intensities will increase mainly due to modified thermodynamic forcing or due to stronger convective dynamics. In gradual self-organization, convective events produce highest intensities late in the day. Tracking rain cells throughout their life cycles, we find that interacting events respond strongly to changes in boundary conditions. Conversely, events without interaction remain unaffected. Increased surface temperature indeed leads to more interaction and higher precipitation extremes. However, a similar intensification occurs when leaving temperature unchanged but simply granting more time for self-organization.Our study implies that the convective field as a whole acquires a memory of past precipitation and inter-cloud dynamics, driving extremes. Our results implicate that the dynamical interaction between convective clouds must be incorporated in global climate models to describe convective extremes and the diurnal cycle more realistically., Comment: 25 pages, 10 figures; removed typo in abstract

In a dry convective boundary layer, convective patterns of typical scales spontaneously develop, qualitatively similar to those in a fluid which is placed between two horizontal plates and sufficiently heated from below. As soon as precipitating cumulus clouds form, this pattern is disturbed and a transition to a different state occurs. Here we use idealized large-eddy simulations to explore how the horizontal scale of convection is modified during this transition in the course of a diurnal cycle. Before onset of precipitation, cells with relatively constant diameter self-organize, with diameters roughly on the scale of the atmospheric boundary layer height. We find that the onset of precipitation then signals an approximately linear increase in horizontal scale with time. For our transient simulations, this scale increase progresses at a speed which is relatively insensitive to modifications in mean surface temperature, modifications in the rate at which surface temperature changes, or the initial lapse rate. When exploring the strength of the spatial correlations, we find that precipitation onset causes a sudden disruption of order and a subsequent decline of organization-until precipitation eventually ceases. We discuss possible implications for the development of extreme precipitation events. ©2017. American Geophysical Union.

Using synoptic weather types and comparing high-resolution precipitation and temperature station data, a separation of large-scale and convective precipitation events is performed. We present percentiles of both types and their superposition for varying precipitation accumulation timescales. In some temperature ranges, large-scale, convective and total precipitation percentiles follow increases with temperature at rates higher than that of the saturation humidity increase of the atmosphere of roughly 7% per degree Kelvin — as given by the Clausius–Clapeyron (CC) relation. However, the increase in total precipitation is found to be due to the transition between the corresponding percentiles of the large-scale and convective types, rather than their individual sections of steep increase. Furthermore, convective precipitation displays a leveling-off towards higher temperatures. This poses further challenges to reconcile arguments brought forward elsewhere — namely those suggesting convective precipitation as the driver of the super-CC increase — with the present observational data.

intensities over Germany. We then combine this data set with surface temperature observations and synoptic observations to group tracks according to convective and stratiform conditions. Convective tracks show clear life cycles in intensity, with peaks shifted off-center toward the beginning of the track, whereas stratiform tracks have comparatively featureless intensity profiles. Our results show that the convective life cycle can lead to convection-dominating precipitation extremes at short time scales, while track-mean intensities may vary much less between the two types. The observed features become more pronounced as surface temperature increases, and in the case of convection even exceeded the rates expected from the Clausius-Clapeyron relation.

The gust fronts of convective cold pools (CPs) are increasingly recognized as loci of enhanced triggering for subsequent convective cells. It has so far been difficult to track these gust fronts in high‐resolution data, such as large eddy simulations (LES)—rendering mechanistic analysis of CP interaction incomplete. Here, a simple tracking method is defined, tested, and applied, which uses horizontal advection and a condition on horizontal divergence, to emit tracers at the perimeter of surface precipitation patches. Tracers are then reliably transported to the gust front, yielding closed bands marking the CP boundary. The method thereby allows analysis of the dynamics also along the gust front, which allows to identify point‐like loci of pronounced updrafts. The tracking works well for a single idealized CP and reliably tracks a population of CPs in a midlatitude diurnal cycle. As the method uniquely links CPs and their tracers to a specific parent precipitation cell, it may be useful for the analysis of interactions in evolving CP populations., Key Points Horizontally advected tracers are suitable for the tracking of cold pools gust frontsThe method allows for the analysis of radial and azimuthal dynamicsConvergence hot spots with strong updrafts can be identified

Observations and simulations have found convective cold pools to trigger and organize subsequent updrafts by modifying boundary layer temperature and moisture as well as by lifting air parcels at the outflow boundaries. We study the causality between cold pools and subsequent deep convection in idealized large‐eddy simulations by tracking colliding outflow boundaries preceding hundreds of deep convection events. When outflow boundaries collide, their common front position remains immobile, whereas the internal cold pool dynamics continues for hours. We analyze how this dynamics “funnels” moisture from a relatively large volume into a narrow convergence zone. We quantify moisture convergence and separate the contribution from surface fluxes, which we find to play a secondary role. Our results highlight that dynamical effects are crucial in triggering convection, even in radiative‐convective equilibrium. However, it is the low‐level convergence resulting from this dynamics that removes inhibition, moistens the atmosphere aloft, and ultimately permits deep convection.