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Small shallow cumulus clouds (<1 km) over the tropical oceans appear to possess the ability to self‐organize into mesoscale (10–100 km) patterns. To better understand the processes leading to such self‐organized convection, we present Cloud Botany, an ensemble of 103 large‐eddy simulations on domains of 150 km, produced by the Dutch Atmospheric Large Eddy Simulation model on supercomputer Fugaku. Each simulation is run in an idealized, fixed, larger‐scale environment, controlled by six free parameters. We vary these over characteristic ranges for the winter trades, including parameter combinations observed during the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) field campaign. In contrast to simulation setups striving for maximum realism, Cloud Botany provides a platform for studying idealized, and therefore more clearly interpretable causal relationships between conditions in the larger‐scale environment and patterns in mesoscale, self‐organized shallow convection. We find that any simulation that supports cumulus clouds eventually develops mesoscale patterns in their cloud fields. We also find a rich variety in these patterns as our control parameters change, including cold pools lined by cloudy arcs, bands of cross‐wind clouds and aggregated patches, sometimes topped by thin anvils. Many of these features are similar to cloud patterns found in nature. The published data set consists of raw simulation output on full 3D grids and 2D cross‐sections, as well as post‐processed quantities aggregated over the vertical (2D), horizontal (1D) and all spatial dimensions (time‐series). The data set is directly accessible from Python through the use of the EUREC4A intake catalog. Plain Language Summary: The organization of shallow cumulus clouds over the tropical ocean has recently received a lot of attention. This type of organization is potentially important for how the clouds are affected by a changing climate and also for how they modulate further warming. We present a collection of 103 detailed simulations of shallow cumulus clouds in idealized atmospheric environments. These environments are described by six parameters, and our collection is formed by systematically simulating different parameter combinations. This way an ensemble is created that spans up a multidimensional phase space of environmental conditions typical for the wintertime subtropical Atlantic Ocean. This approach allows us to form a picture of how the environmental conditions relate to the cloud organization that develops in the simulations. At a glance, most simulations evolve similarly: They quickly form small cumulus clouds, which then grow in size and organize into patterns. Often this leads to rainfall, which then causes further heterogeneity and pattern formation. The data is openly available online, and will serve future studies of cumulus clouds, their organization, and how they interact with the climate. Key Points: We present Cloud Botany, an ensemble of idealized large‐eddy simulations of the winter trade wind regions, controlled by six varied parametersThe parameter ranges are chosen to match the climatology of the trade wind regionThe simulations show a variety of cloud organization patterns: small cumulus, stripes, cold pools, cloud arcs, and anvils [ABSTRACT FROM AUTHOR]