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State-of-the-art Earth system models typically employ grid spacings of O(100 km), which is too coarse to explicitly resolve main drivers of the flow of energy and matter across the Earth system. In this paper, we present the new ICON-Sapphire model configuration, which targets a representation of the components of the Earth system and their interactions with a grid spacing of 10 km and finer. Through the use of selected simulation examples, we demonstrate that ICON-Sapphire can (i) be run coupled globally on seasonal timescales with a grid spacing of 5 km, on monthly timescales with a grid spacing of 2.5 km, and on daily timescales with a grid spacing of 1.25 km; (ii) resolve large eddies in the atmosphere using hectometer grid spacings on limited-area domains in atmosphere-only simulations; (iii) resolve submesoscale ocean eddies by using a global uniform grid of 1.25 km or a telescoping grid with the finest grid spacing at 530 m, the latter coupled to a uniform atmosphere; and (iv) simulate biogeochemistry in an ocean-only simulation integrated for 4 years at 10 km. Comparison of basic features of the climate system to observations reveals no obvious pitfalls, even though some observed aspects remain difficult to capture. The throughput of the coupled 5 km global simulation is 126 simulated days per day employing 21 % of the latest machine of the German Climate Computing Center. Extrapolating from these results, multi-decadal global simulations including interactive carbon are now possible, and short global simulations resolving large eddies in the atmosphere and submesoscale eddies in the ocean are within reach.

As part of the EUREC4A (Elucidating the role of cloud–circulation coupling in climate) field campaign, the German research aircraft HALO (High Altitude and Long Range Research Aircraft), configured as a cloud observatory, conducted 15 research flights in the trade-wind region east of Barbados in January and February 2020. Narrative text, aircraft state data, and metadata describing HALO's operation during the campaign are provided. Each HALO research flight is segmented by timestamp intervals into standard elements to aid the consistent analysis of the flight data. Photographs from HALO's cabin and animated satellite images synchronized with flight tracks are provided to visually document flight conditions. As a comprehensive product from the remote sensing observations, a multi-sensor cloud mask product is derived and quantifies the incidence of clouds observed during the flights. In addition, to lower the threshold for new users of HALO's data, a collection of use cases is compiled into an online book, How to EUREC4A, included as an asset with this paper. This online book provides easy access to most of EUREC4A's HALO data through an intake catalogue. Code and data are freely available at the locations specified in Table 6.

An overview of cloud vertical structure (CVS) and cloud radiative forcing (CRF) during Indian summer monsoon is obtained over Kanpur, through observations made during the Interaction of Convective Organisation and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) field campaign of 2016. Associations of CVS parameters with CRF at surface and top of atmosphere (TOA) are also investigated. 137 radiosondes were launched at Indian Institute of Technology Kanpur (IITK), between 5th and 28th July, 2016. CVS is determined using an algorithm that identifies cloud layers from vertical profiles of relative humidity (RH), with altitude-dependent RH thresholds. CVS is analysed by separating the campaign period on the basis of presence and absence of depressions/low-pressure systems. Compared to non-depression periods, low-pressure events showed significant difference in all CVS and CRF parameters except cloud-top height. CVS was multi-layered in ~75% launches, with deep, mixed-phase clouds being present in ~70% launches. CRF was calculated from clear-sky measurements and TOA observations from Clouds and the Earth's Radiant Energy System (CERES) satellite retrievals, and surface measurements. A net cooling effect was found overall, with instantaneous shortwave forcing (SWCRF) (mean values of -95.92 and -101.89 W/m2 at surface and TOA, respectively) dominating longwave forcing (LWCRF) (mean values of 15.33 and 66.55 W/m2 at surface and TOA, respectively). Results suggest that SWCRF depends on total depth of cloud layers, and is independent of cloud altitude, whereas LWCRF depends on both depth and vertical location of cloud layers, with base and top heights regulating LWCRF at surface and TOA, respectively.

Shallow cumulus clouds in the trade-wind regions cool the planet by reflecting solar radiation. The response of trade cumulus clouds to climate change is a key uncertainty in climate projections1–4. Trade cumulus feedbacks in climate models are governed by changes in cloud fraction near cloud base5,6, with high-climate-sensitivity models suggesting a strong decrease in cloud-base cloudiness owing to increased lower-tropospheric mixing5–7. Here we show that new observations from the EUREC4A (Elucidating the role of cloud-circulation coupling in climate) field campaign8,9 refute this mixing-desiccation hypothesis. We find the dynamical increase of cloudiness through mixing to overwhelm the thermodynamic control through humidity. Because mesoscale motions and the entrainment rate contribute equally to variability in mixing but have opposing effects on humidity, mixing does not desiccate clouds. The magnitude, variability and coupling of mixing and cloudiness differ markedly among climate models and with the EUREC4A observations. Models with large trade cumulus feedbacks tend to exaggerate the dependence of cloudiness on relative humidity as opposed to mixing and also exaggerate variability in cloudiness. Our observational analyses render models with large positive feedbacks implausible and both support and explain at the process scale a weak trade cumulus feedback. Our findings thus refute an important line of evidence for a high climate sensitivity10,11.