Due to their potential role in organizing tropical mesoscale convective systems, a better understanding of cold pool (CP) dynamics in such regions is critical, particularly over land where the diurnal cycle further concentrates convective activity. Numerical models help disentangle the processes involved but often lack observational benchmark studies. To close this gap, we analyze nearly 43 years of five-minute resolution near-surface timeseries records from twelve automatic weather stations across equatorial Africa. We identify 4289 CPs based on criteria for temperature and wind. The identified CP gust fronts, which exhibit respective median temperature and specific humidity decreases of 5.2 K and 2.8 g/kg, closely correlate with satellite-observed brightness temperature discontinuities. Despite weak diurnal variation in precipitation, observed CP occurrence shows a pronounced diurnal cycle with an afternoon peak — a finding we attribute to low-level moisture conditions. Our findings can serve as observational benchmark to improve simulations of CP organization.

Recent observations and modeling increasingly reveal the key role of cold pools in organizing the convective cloud field. Several methods for detecting cold pools in simulations exist, but are usually based on buoyancy fields and fall short in reliably identifying the active gust front. The current algorithm, termed CoolDeTA, aims to detect and track cold pools along with their active gust fronts and the “offspring” rain cells generated nearby. We show how CoolDeTA can reconstruct cold pool family trees. Using it allows us to contrast RCE and diurnal cycle cold pool dynamics, as well as cases with vertical wind shear and without. The results suggest a conceptual model where cold pool triggering of children rain cells follows a simple birth rate, which is proportional to a cold pool’s gust front length. The proportionality factor depends on the ambient atmospheric stability and is lower for RCE, in line with marginal stability as traditionally ascribed to the moist adiabat. In the diurnal case, where ambient stability is lower, the birth rate thus becomes substantially higher, in line with periodic insolation forcing — resulting in essentially run-away mesoscale excitations generated by a single parent rain cell and its cold pool.

Convective cold pools (CPs) are known to mediate the interaction between convective rain cells and thereby help organize thunderstorm clusters, in particular mesoscale convective systems and extreme rainfall events. Unfortunately, the observational detection of CPs on a large scale has so far been hampered by the lack of relevant large-scale nearsurface data. Unlike numerical studies, where high-resolution near-surface fields of relevant quantities such as virtual temperature and winds are available and frequently used to detect cold pools, observational studies mainly identify CPs based on surface time series. Since research vessels or weather stations measure these time series locally, the characterization of cold pools from observations is limited to regional or station-based studies. To eventually enable studies on a global scale, we here develop and evaluate a methodology for the detection of CPs that relies only on data that (i) is globally available and (ii) has high spatio-temporal resolution. We trained convolutional neural networks to segment CPs in cloud and rainfall fields from high-resolution cloud resolving simulation output. Such data is not only available from simulations, but also from geostationary satellites that fulfill both (i) and (ii). The networks make use of a U-Net architecture, a common choice for image segmentation due to its strength in learning spatial correlations at different scales. Based on cloud and rainfall fields only, the trained networks systematically identify CP pixels in the simulation output. Our methodology may thus open for reliable global CP detection from space-borne sensors. As it also provides information on the spatial extent and the relative positioning of CPs over time, our method may offer new insight into the role of CPs in convective organization.