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Abstract. In early 2020, an international team set out to investigatetrade-wind cumulus clouds and their coupling to the large-scale circulationthrough the field campaign EUREC4A: ElUcidating the RolE ofClouds-Circulation Coupling in ClimAte. Focused on the western tropicalAtlantic near Barbados, EUREC4A deployed a number of innovativeobservational strategies, including a large network of water isotopicmeasurements collectively known as EUREC4A-iso, to study the tropicalshallow convective environment. The goal of the isotopic measurements was toelucidate processes that regulate the hydroclimate state – for example, byidentifying moisture sources, quantifying mixing between atmospheric layers,characterizing the microphysics that influence the formation and persistenceof clouds and precipitation, and providing an extra constraint in theevaluation of numerical simulations. During the field experiment,researchers deployed seven water vapor isotopic analyzers on two aircraft,on three ships, and at the Barbados Cloud Observatory (BCO). Precipitationwas collected for isotopic analysis at the BCO and from aboard four ships.In addition, three ships collected seawater for isotopic analysis. All told,the in situ data span the period 5 January–22 February 2020 andcover the approximate area 6 to 16∘ N and 50 to 60∘ W,with water vapor isotope ratios measured from a few meters above sea levelto the mid-free troposphere and seawater samples spanning the ocean surfaceto several kilometers depth. This paper describes the full EUREC4A isotopic in situ data collection– providing extensive information about sampling strategies and datauncertainties – and also guides readers to complementary remotely sensedwater vapor isotope ratios. All field data have been made publicly availableeven if they are affected by known biases, as is the case for high-altitudeaircraft measurements, one of the two BCO ground-based water vapor timeseries, and select rain and seawater samples from the ships. Publication ofthese data reflects a desire to promote dialogue around improving waterisotope measurement strategies for the future. The remaining, high-qualitydata create unprecedented opportunities to close water isotopic budgets andevaluate water fluxes and their influence on cloudiness in the trade-windenvironment. The full list of dataset DOIs and notes on data quality flagsare provided in Table 3 of Sect. 5 (“Data availability”). 

Abstract. Our climate is constrained by the balance between solar energy absorbed by the Earth and terrestrial energy radiated tospace. This energy balance has been widely used to infer equilibrium climate sensitivity (ECS) from observations of20th-century warming. Such estimates yield lower values than other methods, and these have been influential in pushing downthe consensus ECS range in recent assessments. Here we test the method using a 100-member ensemble of the Max Planck Institute Earth System Model(MPI-ESM1.1) simulations of the period 1850–2005 with known forcing. We calculate ECS in each ensemble member usingenergy balance, yielding values ranging from 2.1 to 3.9K. The spread in the ensemble is related to the centralassumption in the energy budget framework: that global average surface temperature anomalies are indicative of anomaliesin outgoing energy (either of terrestrial origin or reflected solar energy). We find thatthis assumption is not well supportedover the historical temperature record in the model ensemble or more recent satellite observations. We find that framingenergy balance in terms of 500hPa tropical temperature better describes the planet's energy balance. 

Abstract. 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. 

Abstract The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.