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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.

Measurements over the north-Atlantic trade wind regions from the recent EUREC4A field campaign (ElUcidating the RolE of Cloud–Circulation Coupling in ClimAte) have revealed a large variability in mesoscale (ca. 200 km) vertical velocity. This variability is primarily attributable to shallow mesoscale overturning circulations (SMOCs) , which have also been shown to influence mesoscale moisture variability. From EUREC4A observations, it is found that the mesoscale horizontal divergence (D) averaged over the mixed layer covaries strongly with surface D. We exploit this finding by using satellite observations of surface divergence to understand SMOCs further. We mainly use WindSAT measurements for surface divergence due to its larger swath compared to scatterometers and its superior performance under precipitating conditions. In WindSAT observations, surface divergence shows a negative correlation with integrated water vapour (IWV), but also shows the large variance when IWV is large, indicating that there might be two regimes in the divergence-moisture relationship. To further investigate the divergence-moisture relationship, we perform object-identification in the IWV field and characterize surface divergence therein. A synergy with geostationary cloudiness fields from GOES-16 helps us further interpret these characteristics in the context of the spatial organization of clouds. As satellite observations go beyond the space-time coverage of field campaigns, we are able to document (a) statistics of the spatial scales of SMOCs as well as (b) some consistent relationships between SMOCs and atmospheric moisture.

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.

Shallow trade cumulus clouds cool the planet and fuel the large-scale circulation. Their unknown response to climate change is a major source of uncertainty in climate projections. Differing changes in cloudiness near the base of the cumulus layer with warming control the spread in simulated trade cumulus cloud feedbacks in models, with high climate sensitivity models showing a strong negative coupling between lower-tropospheric mixing and cloudiness. However, such a mixing-desiccation mechanism has never been tested with observations. Here we present novel measurements of the convective mass flux, cloud fraction and relative humidity at cloud base from the recent EUREC4A field campaign and find the dynamical control of cloudiness through the mass flux to overwhelm the thermodynamic response to humidity. Because the mesoscale vertical velocity controls the mass flux as much as entrainment does, the mass flux ends up being uncorrelated to relative humidity, which opposes the mixing-desiccation hypothesis. The magnitude, variability, and coupling of mass flux and cloudiness differs drastically between climate models and the EUREC4A observations. Models that have particularly strong trade cumulus feedbacks tend to exaggerate the dependence of cloudiness on humidity rather than the mass flux, and also exaggerate variability in cloudiness. The process-based constraints presented here render those strongly positive trade cumulus feedbacks unrealistic, for the first time supporting and explaining a weak trade cumulus feedback at the relevant process scale.

We find an abundance of low-level, mesoscale circulations in the atmosphere below the trade-wind inversion layer based on observations of the mesoscale atmospheric circulation taken during the EUREC4A campaign. Over time-means of 3-6 hours, the mean sub-cloud divergence anomaly correlates negatively with the mean divergence anomaly in the cloud layer. Here, the term anomaly means the deviation from the EUREC4A-wide month-long mean of divergence at the corresponding altitude. Additionally, sub-cloud divergence anomaly correlates negatively with specific humidity anomaly in the sub-cloud and cloud layers, indicating moist, convergent regimes and dry, divergent regimes. We hypothesise that the presence of shallow circulations below the inversion layer explains these associations. Our proposed mechanism of shallow circulations is that regions of ascending air are balanced by neighbouring cells of subsidence, thus creating and maintaining moist and dry regions, which reinforce the shallow circulations. We use mixed-layer theory to estimate the time-scales at which the sub-cloud layer moisture would respond to such divergence patterns. The observed relationships are also evident in reanalysis data, which further reinforce that these are indeed mesoscale features and not large-scale signals captured by the observations.

The characterization of systematic forecast errors in lower-tropospheric winds is an essential component of model improvement. This paper is motivated by a global, long-standing surface bias in the operational medium-range weather forecasts produced with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Over the tropical oceans, excessive easterly flow is found. A similar bias is found in the western North Atlantic trades, where the EUREC4A field campaign provides an unprecedented wealth of measurements. We analyze the wind bias in the IFS and ERA5 reanalysis throughout the entire lower troposphere during EUREC4A. The wind bias varies greatly from day to day, resulting in root mean square errors (RMSEs) up to 2.5 m s−1, with a mean wind speed bias up to −1 m s−1 near and above the trade inversion in the forecasts and up to −0.5 m s−1 in reanalyses. These biases are insensitive to the assimilation of sondes. The modeled zonal and meridional winds exhibit a diurnal cycle that is too strong, leading to a weak wind speed bias everywhere up to 5 km during daytime but a wind speed bias below 2 km at nighttime that is too strong. Removing momentum transport by shallow convection reduces the wind bias near the surface but leads to stronger easterly near cloud base. The update in moist physics in the newest IFS cycle (cycle 47r3) reduces the meridional wind bias, especially during daytime. Below 1 km, modeled friction due to unresolved physical processes appears to be too strong but is (partially) compensated for by the dynamics, making this a challenging coupled problem.

Large-eddy simulation (LES) is able to capture key boundary-layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly constrained for LES simulations. We derive these quantities from measurements and reanalysis obtained for two cold air outbreak (CAO) events during Phase I of the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) in February-March 2020. We study the two contrasting CAO cases by performing LES simulations and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from the reanalysis data ERA5 agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time evolving heat fluxes, wind and advective tendencies profiles from ERA5 reanalysis data to drive the LES simulations. We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 reanalysis data and validated by the observations. We show that the divergence (or vertical advection) is important in regulating the BL growth driven by surface heat fluxes in LES simulations. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path simulated in LES agrees reasonably well with the ACTIVATE measurements. This study paves the path to investigate aerosol-cloud-meteorology interactions using LES informed and evaluated by ACTIVATE field measurements.

As part of the EUREC4A field campaign which took place over the tropical North Atlantic during January–February 2020, 1215 dropsondes from the HALO and WP-3D aircraft were deployed through 26 flights to characterize the thermodynamic and dynamic environment of clouds in the trade-wind regions. We present JOANNE (Joint dropsonde Observations of the Atmosphere in tropical North atlaNtic meso-scale Environments), the dataset that contains these dropsonde measurements and the products derived from them. Along with the raw measurement profiles and basic post-processing of pressure, temperature, relative humidity and horizontal winds, the dataset also includes a homogenized and gridded dataset with 10 m vertical spacing. The gridded data are used as a basis for deriving diagnostics of the area-averaged mesoscale circulation properties such as divergence, vorticity, vertical velocity and gradient terms, making use of sondes dropped at regular intervals along a circular flight path. A total of 85 such circles, ∼ 222 km in diameter, were flown during EUREC4A. We describe the sampling strategy for dropsonde measurements during EUREC4A, the quality control for the data, the methods of estimation of additional products from the measurements and the different post-processed levels of the dataset. The dataset is publicly available (https://doi.org/10.25326/246, George et al., 2021b) as is the software used to create it (https://doi.org/10.5281/zenodo.4746312, George, 2021).

As part of the EUREC4A field campaign, the German research aircraft HALO, 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 meta data describing HALO's operation during the campaign are provided. Each HALO research flight is segmented by time-stamp 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.

We use measurements from the Elucidating the role of clouds-circulation coupling in climate (EUREC4A) campaign to characterise the variability in the meso-scale divergence and vertical motion (pressure velocity, 𝜔) ranging across time-scales from a few hours to a month (the entire campaign period from 19th January - 15th February, 2020). The area-averaged divergence is estimated using measurements of horizontal winds from dropsondes launched in a circular flight path (~200 km diameter), something that was carried out extensively during EUREC4A – 85 circles over 19 flight-days in the North Atlantic trade-wind region.From these estimates, we characterise the vertical structure and variability of divergence and 𝜔 in the trades. We find that 𝜔 above the sub-cloud layer is quite consistent vertically when averaged over long periods. The value stays around 1-1.5 hPa/h, which agrees well with the roughly 1.5 K/day cooling rate of the trades. However, significant intra- and inter-day variability can be found between 𝜔 profiles, in terms of the magnitudes, ranging from -7 hPa/h to 6 hPa/h as well as in terms of the vertical structure of these profiles. Daily mean sub-cloud layer divergence varies significantly from that of the cloud-layer in magnitude, and for most flight days, we also observe a sign change between the two. Changes in the vertical structure over different days suggest that a local maximum of either divergence or convergence is usually seen near the inversion layer. Our findings can provide insight into how the atmospheric state varies over short time-scales, as well as their impact on cloudiness, thus providing clues about a predominantly important question in climate science — the clouds-circulation coupling.

Cloud free skies are rare in the trades. We analyze conditions in which cloud-free conditions prevail. For this purpose Raman water vapor measurements from the Barbados Cloud Observatory, complemented by ship-based measurements during EUREC4A are used to explore water vapor variability in the marine boundary layer. We explore the consistency of the inferred cloud base height with estimates of temperature and water vapor from the lidar signal, and examine the co-variability of these quantities. After having established the properties of these measurements, we seek to use them as well as others, to explain in what ways periods of cloud-free conditions are maintained, investigating the hypothesis that only when the wind stills is it simply sunny.

The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A 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 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 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and 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 EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.

International audience; We use estimates of mesoscale vertical velocity and collocated cloud measurements from the second Next-Generation Aircraft Remote Sensing for Validation campaign (NARVAL2) in the tropical North Atlantic to show the observed impact of mesoscale vertical motion on tropical clouds. Our results not only confirm previously untested hypotheses about the role of dynamics being nonnegligible in determining cloudiness, but go further to show that at the mesoscale, the dynamics has a more dominant control on cloudiness variability than thermodynamics. A simple massflux estimate reveals that mesoscale vertical velocity at the subcloud-layer top explains much of the variations in peak shallow cumulus cloud fraction. In contrast, we find that thermodynamic cloud-controlling factors, such as humidity and stability, are unable to explain the variations in cloudiness at the mesoscale. Thus, capturing the observed variability of cloudiness may require not only a consideration of thermodynamic factors, but also dynamic ones such as the mesoscale vertical velocity. SIGNIFICANCE STATEMENT: Knowing how low clouds link to atmospheric circulation over a few hundred kilometers will reduce current uncertainties in the sensitivity of Earth's climate to warming. Such investigations have previously been limited by lack of circulation measurements at the mesoscale. However, using measurements now available from a recent field campaign over the tropical North Atlantic along with cloud measurements, we demonstrate how atmospheric vertical motion especially in the lower layers can influence the extent and structure of clouds. We find that the kinematics have a more dominant control on low-level cloudiness than conventionally studied thermodynamics. Our results show why it is important to focus attention to the circulation to improve our understanding of the variability in cloudiness.

This study uses measurements from the Elucidating the Role of Clouds-Circulation Coupling in Climate, EUREC4A and the second Next-Generation Aircraft Remote Sensing for Validation, NARVAL2 campaigns to investigate the influence of large-scale environmental conditions on cloudiness. For the first time, these campaigns provide divergence measurements, making it possible to explore the impact of large-scale vertical motions on clouds. We attempt to explain the cloudiness through the varying thermodynamics and dynamics in the different environments. For most of the NARVAL2 case-studies, cloudiness is poorly related to thermodynamical factors such as sea-surface temperature and lower tropospheric stability. Factors such as integrated water vapour and pressure velocity (ω) at 500 hPa and 700 hPa can be used to distinguish between actively convecting and suppressed regions, but they are not useful in determining the variation in cloudiness among suppressed cases. We find that ω in the boundary layer (up to ∼2 km) has a more direct control on the low-level cloudiness in these regions, than that in the upper layers. We use a simplistic method to show that ω at the lifting condensation level can be used to determine the cloud cover of shallow cumulus clouds. Thus, we argue that cloud schemes in models should not rely only on thermodynamical information, but also on dynamical predictors.

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.

The INCOMPASS field campaign combines airborne and ground measurements of the 2016 Indian monsoon, towards the ultimate goal of better predicting monsoon rainfall. The monsoon supplies the majority of water in South Asia, but forecasting from days to the season ahead is limited by large, rapidly developing errors in model parametrizations. The lack of detailed observations prevents thorough understanding of the monsoon circulation and its interaction with the land surface: a process governed by boundary- layer and convective-cloud dynamics. INCOMPASS used the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft for the first project of this scale in India, to accrue almost 100 h of observations in June and July 2016. Flights from Lucknow in the northern plains sampled the dramatic contrast in surface and boundary-layer structures between dry desert air in the west and the humid environment over the northern Bay of Bengal. These flights were repeated in pre-monsoon and monsoon conditions. Flights from a second base at Bengaluru in southern India measured atmospheric contrasts from the Arabian Sea, over the Western Ghats mountains, to the rain shadow of southeast India and the south Bay of Bengal. Flight planning was aided by forecasts from bespoke 4 km convection-permitting limited-area models at the Met Office and India's NCMRWF. On the ground, INCOMPASS installed eddy- covariance flux towers on a range of surface types, to provide detailed measurements of surface fluxes and their modulation by diurnal and seasonal cycles. These data will be used to better quantify the impacts of the atmosphere on the land surface, and vice versa. INCOMPASS also installed ground instrumentation supersites at Kanpur and Bhubaneswar. Here we motivate and describe the INCOMPASS field campaign. We use examples from two flights to illustrate contrasts in atmospheric structure, in particular the retreating mid-level dry intrusion during the monsoon onset.

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.

Large-eddy simulation (LES) is able to capture key boundary-layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly prescribed for LES simulations. We derive these quantities from measurements and reanalysis obtained for two cold air outbreak (CAO) events during Phase I of the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) in February-March 2020. We study the two contrasting CAO cases by performing LES and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from the reanalysis data ERA5 agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time evolving heat fluxes, wind and advective tendencies profiles from ERA5 reanalysis data to drive the LES. We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 reanalysis data and validated by the observations. We show that the divergence (or vertical velocity) is important in regulating the BL growth driven by surface heat fluxes in LES simulations. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path simulated in LES agrees reasonably well with the ACTIVATE measurements.This study paves the path to investigate aerosol-cloud-meteorology interactions using LES informed and evaluated by ACTIVATE field measurements., Accepted for publication in Journal of the Atmospheric Sciences