Using highly resolved large-eddy simulations on two different domain sizes, we investigate the influence of precipitation and spatial organization on the thermodynamic structure of the trade-wind layer, under a uniform 4 K warming at constant relative humidity. In nonprecipitating simulations, the increased surface latent heat flux in the warmer climate produces a deeper and drier cloud layer with reduced cloud fractions between 1.5 and 4 km. Precipitation prevents the deepening and drying of the cloud layer in response to warming. Cloud fractions still decrease in the upper cloud layer, because stratiform outflow layers near cloud tops are less pronounced and because the larger liquid water contents are confined to narrower updrafts. Simulations on a 16-fold larger domain lead to the spatial organization of clouds into larger and deeper cloud clusters. The presence of deeper clouds results in a shallower, warmer, and drier trade-wind layer, with strongly reduced cloud cover. The warming response in the precipitating largedomain simulation nevertheless remains similar to the small-domain precipitating simulation. On the large domain, deeper clouds can also develop without precipitation, because moisture-convection feedbacks strengthen in the absence of cold-pool dynamics. Overall, total cloud cover and albedo decrease only slightly with warming in all cases. This demonstrates the robustness of shallow cumuli-in particular of cloud fraction near the lifting condensation level-to changes in the large-scale environment.

Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. 123Surv Geophys (2017) 38:1529-1568 https://doi.org/10.1007/s10712-017-9428-0 cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of tradecumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.

A description of the daily cycle of oceanic shallow cumulus for undisturbed boreal winter conditions in the North Atlantic trades is presented. Modern investigation tools are used, including storm‐resolving and large‐eddy simulations, runover large domains in realistic configurations, and observations from in situ measurements and satellite‐based retrievals. Models and observations clearly show pronounced diurnal variations in cloudiness, both near cloud base and below the trade inversion. The daily cycle reflects the evolution of two cloud populations: (i) a population of nonprecipitating small cumuli with weak vertical extent, which grows during the day and maximizes around sunset, and (ii) a population o deeper precipitating clouds with a stratiform cloud layer below the trade inversion, which grows during the night and maximizes just before sunrise. Previous studies have reported that cloudiness near cloud base undergoes weak variations on time scales longer than a day. However, here we find that it can vary strongly at the diurnal time scale. This daily cycle could serve as a critical test of the models' representation of the physical processes controlling cloudiness near cloud base, which is thought to be key for the determination of the Earth's climate response to warming.

We evaluate the new icosahedral nonhydrostatic atmospheric (ICON‐A) general circulation model of the Max Planck Institute for Meteorology that is flexible to be run at grid spacings from a few tens of meters to hundreds of kilometers. A simulation with ICON‐A at a low resolution (160 km) is compared to a not‐tuned fourfold higher‐resolution simulation (40 km). Simulations using the last release of the ECHAM climate model (ECHAM6.3) are also presented at two different resolutions. The ICON‐A simulations provide a compelling representation of the climate and its variability. The climate of the low‐resolution ICON‐A is even slightly better than that of ECHAM6.3. Improvements are obtained in aspects that are sensitive to the representation of orography, including the representation of cloud fields over eastern‐boundary currents, the latitudinal distribution of cloud top heights, and the spatial distribution of convection over the Indian Ocean and the Maritime Continent. Precipitation over land is enhanced, in particular at high‐resolution ICON‐A. The response of precipitation to El Niño sea surface temperature variability is close to observations, particularly over the eastern Indian Ocean. Some parameterization changes lead to improvements, for example, with respect to rain intensities and the representation of equatorial waves, but also imply a warmer troposphere, which we suggest leads to an unrealistic poleward mass shift. Many biases familiar to ECHAM6.3 are also evident in ICON‐A, namely, a too zonal SPCZ, an inadequate representation of north hemispheric blocking, and a relatively poor representation of tropical intraseasonal variability.