We investigate whether and how spatial organisation affects the pathway to precipitation in large-domain hectometer simulations of the North Atlantic trades. We decompose the development of surface precipitation (P) in warm shallow trade cumulus into a formation phase, where cloud condensate is converted into rain, and a sedimentation phase, where rain falls towards the ground while some of it evaporates. With strengthened organisation, rain forms in weaker updrafts from smaller cloud droplets so that cloud condensate is less efficiently converted into rain. At the same time, organisation creates a locally moister environment and modulates the microphysical conversion processes that determine the raindrops' size. This reduces evaporation and more of the formed rain reaches the ground. Organisation thus affects how the two phases contribute to P, but only weakly affects the total precipitation efficiency. We conclude that the pathway to precipitation differs with organisation and suggest that organisation buffers rain development.

Global uncoupled storm-resolving simulations using the ICOsahedral Non-hydrostatic (ICON) model with prescribed sea surface temperature show a double band of precipitation in the Western Pacific, a feature explained by reduced precipitation over the warm pool. Three hypotheses using an energetic framework are advanced to explain the warm pool precipitation bias, and they are related to 1) high-cloud radiative effect, 2) too-frequent or highly efficient precipitating shallow convection, and 3) surface heat fluxes in light near-surface winds. Our results show that increasing surface heat fluxes in light near-surface winds produce more precipitation over the warm pool and a single precipitation band in the Western Pacific. Further improvements were stronger near-surface winds over the Western Pacific and a moister and warmer tropical troposphere, but these improvements were not enough to fully overcome the existing biases. Simulations with an increased high-cloud radiative effect did not affect precipitation over the warm pool, and according to the energetic framework, due to compensation between the radiative effect and both, surface heat fluxes and circulation. Moreover, the representation of shallow convection did not affect warm pool precipitation. Thus, our results show the importance of the feedback between winds, surface heat fluxes, and convection for a correct representation of the oceanic tropical rainbelt structure in regions of weak sea surface temperature gradient as the warm pool.

The new capabilities of global storm-resolving models to resolve individual clouds allow for a more physical perspective on the tropical high-cloud radiative effect and how it might change with warming. In this study, we develop a conceptual model of the high-cloud radiative effect as a function of cloud thickness measured by ice water path. We use atmospheric profiles from a global ICON simulation with 5 km horizontal grid spacing to calculate the radiation offline with the ARTS line-by-line radiative transfer model. The conceptual model of the high-cloud radiative effect reveals that it is sufficient to approximate high clouds as a single layer characterised by an albedo, emissivity and temperature, which vary with ice water path. The increase of the short-wave high-cloud radiative effect with ice water path is solely explained by the high-cloud albedo. The increase of the long-wave high-cloud radiative effect with ice water path is governed by an increase of emissivity for ice water path below 10-1 kg m-2, and by a decrease of high-cloud temperature with increasing ice water path above this threshold. The total high-cloud radiative effect from the ARTS simulations for the chosen day of this ICON model run is 2.59 W m-2, which is closely matched by our conceptual model with 2.56 W m-2. Because the high-cloud radiative effect depends on the assumed radiative alternative, assumptions on low clouds make a substantial difference. The conceptual model predicts that doubling the fraction of low clouds causes a doubling of the high-cloud radiative effect.

Reducing the model spread in free-tropospheric relative humidity (RH) and its response to warming is a crucial step towards reducing the uncertainty in clear-sky climate sensitivity, a step that is hoped to be taken with recently developed global storm-resolving models (GSRMs). In this study we quantify the inter-model differences in tropical present-day RH across GSRMs, making use of DYAMOND, a first 40-day intercomparison. We find that the inter-model spread in tropical mean free-tropospheric RH is reduced compared to conventional atmospheric models, except from the the tropopause region and the transition to the boundary layer. We estimate the reduction to approximately 50-70% in the upper troposphere and 25-50% in the mid troposphere. However, the remaining RH differences still result in a spread of 1.2 Wm-2 in tropical mean clear-sky outgoing longwave radiation (OLR). This spread is mainly caused by RH differences in the lower and mid free troposphere, whereas RH differences in the upper troposphere have a minor impact. By examining model differences in moisture space we identify two regimes with a particularly large contribution to the spread in tropical mean clear-sky OLR: rather moist regimes at the transition from deep convective to subsidence regimes and very dry subsidence regimes. Particularly for these regimes a better understanding of the processes controlling the RH biases is needed.

Trade wind convection organises into a rich spectrum of spatial patterns, often in conjunction with precipitation development. Which role spatial organisation plays for precipitation and vice versa is not well understood. We analyse scenes of trade wind convection scanned by the C-band radar Poldirad during the EUREC4A field campaign to investigate how trade wind precipitation fields are spatially organised, quantified by the cells’ number, mean size and spatial arrangement, and how this matters for precipitation characteristics. We find that the mean rain rate, i.e. the amount of precipitation in a scene, and the intensity of precipitation (mean conditional rain rate) relate differently to the spatial pattern of precipitation. While the amount of precipitation increases with mean cell size or number, as it scales well with the precipitation fraction, the intensity increases predominantly with mean cell size. In dry scenes, the increase of precipitation intensity with mean cell size is stronger than in moist scenes. Dry scenes usually contain fewer cells with a higher degree of clustering than moist scenes. High precipitation intensities hence typically occur in dry scenes with rather large, few and strongly clustered cells, while high precipitation amounts typically occur in moist scenes with rather large, numerous and weakly clustered cells. As cell size influences both the intensity and amount of precipitation, its importance is highlighted. Our analyses suggest that the cells’ spatial arrangement, correlating mainly weakly with precipitation characteristics, is of second order importance for precipitation across all regimes, but could be important for high precipitation intensities and to maintain precipitation amounts in dry environments.

We conduct a series of eight 45-day experiments with a global storm-resolving model (GSRM) to test the sensitivity of relative humidity R in the tropics to changes in model resolution and parameterizations. These changes include changes in horizontal and vertical grid spacing as well as in the parameterizations of microphysics and turbulence, and are chosen to capture currently existing differences among GSRMs. To link the R distribution in the tropical free troposphere with processes in the deep convective regions, we adopt a trajectory-based assessment of the last-saturation paradigm. The perturbations we apply to the model result in tropical mean R changes ranging from 0.5% to 8% (absolute) in the mid troposphere. The generated R spread is similar to that in a multi-model ensemble of GSRMs and smaller than the spread across conventional general circulation models, supporting that an explicit representation of deep convection reduces the uncertainty in tropical R. The largest R changes result from changes in parameterizations, suggesting that model physics represent a major source of humidity spread across GSRMs. The R in the moist tropical regions is disproportionately sensitive to vertical mixing processes within the tropics, which impact R through their effect on the last-saturation temperature rather than their effect on the evolution of the humidity since last-saturation. In our analysis the R of the dry tropical regions strongly depends on the exchange with the extra-tropics. The interaction between tropics and extratropics could change with warming and presage changes in the radiatively sensitive dry regions.

Understanding drivers of cloud organization is crucial for accurately estimating clouds’ feedback to a warming climate. Shallow mesoscale circulations are thought to play an important role in cloud organization, but they have not been observed. Here, we present observational evidence for shallow mesoscale overturning circulations (SMOCs) from divergence measurements made during the EUREC4A field campaign in the north-Atlantic trades. Meteorological reanalyses reproduce the observed low-level divergence well and confirm SMOCs to be mesoscale features (ca. 200 km). Large mesoscale variability, five-fold the mean, is shown to be associated with the ubiquity of SMOCs. Furthermore, time-lag correlations suggest that SMOCs amplify mesoscale moisture variance at cloud-base and in the sub-cloud layer. Through their modulation of cloud-base moisture, SMOCs influence the drying efficiency of entrainment, thus yielding moist ascending branches and dry descending branches. The observed moisture variance differs from expectations from large-eddy simulations, which show largest variance near cloud top and negligible sub-cloud variance. The ubiquity of SMOCS and their coupling to moisture and cloud fields suggest that the strength and scale of mesoscale circulations are important in determining how clouds couple to climate, something which is not considered by present theories.

The science guiding the \EURECA campaign and its measurements are presented. \EURECA comprised roughly five weeks of measurements in the downstream winter trades of the North Atlantic — eastward and south-eastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, \EURECA marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or, or the life-cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso (200 km) and larger (500 km) scales, roughly four hundred hours of flight time by four heavily instrumented research aircraft, four global-ocean class research vessels, an advanced ground-based cloud observatory, a flotilla of autonomous or tethered measurement devices operating in the upper ocean (nearly 10000 profiles), lower atmosphere (continuous profiling), and along the air-sea interface, a network of water stable isotopologue measurements, complemented by special programmes of satellite remote sensing and modeling with a new generation of weather/climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that \EURECA explored — from Brazil Ring Current Eddies to turbulence induced clustering of cloud droplets and its influence on warm-rain formation — are presented along with an overview \EURECA’s outreach activities, environmental impact, and guidelines for scientific practice.