A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two‐layer model.

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short) scales, the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similar to past studies we find an improved representation of precipitation at kilometer scales, as compared to models with parameterised convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the timescales considered-most notably over the Tropical ocean. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hecto-meter scales. Hectometer scales appear more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when reducing the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct 1 connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with an already improved simulation as compared to more parameterised models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change.

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.

In this study Lagrangian large-eddy simulation of cloudy mixed layers in evolving warm air masses in the Arctic is constrained by in situ observations from the recent PASCAL field campaign. A key novelty is that time dependence is maintained in the large-scale forcings. An iterative procedure featuring large-eddy simulation on microgrids is explored to calibrate the case setup, inspired by and making use of the typically long memory of Arctic air masses for upstream conditions. The simulated mixed-phase clouds are part of a turbulent mixed layer that is weakly coupled to the surface and is occasionally capped by a shallow humidity layer. All eight simulated mixed layers exhibit a strong time evolution across a range of time scales, including diurnal but also synoptic fingerprints. A few cases experience rapid cloud collapse, coinciding with a rapid decrease in mixed-layer depth. To gain insight, composite budget analyses are performed. In the mixed-layer interior the heat and moisture budgets are dominated by turbulent transport, radiative cooling, and precipitation. However, near the thermal inversion the large-scale vertical advection also contributes significantly, showing a distinct difference between subsidence and upsidence conditions. A bulk mass budget analysis reveals that entrainment deepening behaves almost time-constantly, as long as clouds are present. In contrast, large-scale subsidence fluctuates much more strongly and can both counteract and boost boundary-layer deepening resulting from entrainment. Strong and sudden subsidence events following prolonged deepening periods are found to cause the cloud collapses, associated with a substantial reduction in the surface downward longwave radiative flux.

Abstract. Forward models are a key tool to generate synthetic observations given knowledge of the atmospheric state. In this way, they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud-resolving models (CRMs). Herein, CRM profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for upward- and downward-looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing upwelling and downwelling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications and interfaces to many different formats of input and output, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh–Gans approximation (SSRGA) for both active and passive applications, which becomes especially important for the investigation of frozen hydrometeors.

The diurnal dependence of cumulus cloud size distributions over land is investigated by means of an ensemble of large-eddy simulations (LESs). A total of 146 days of transient continental shallow cumulus are selected and simulated, reflecting a low midday maximum of total cloud cover, weak synoptic forcing, and the absence of strong surface precipitation. The LESs are semi-idealized, forced by large-scale model output but using an interactive surface. This multitude of cases covers a large parameter space of environmental conditions, which is necessary for identifying any diurnal dependencies in cloud size distributions. A power-law exponential function is found to describe the shape of the cloud size distributions for these days well, with the exponential component capturing the departure from power-law scaling at the larger cloud sizes. To assess what controls the largest cloud size in the distribution, the correlation coefficients between the maximum cloud size and various candidate variables reflecting the boundary layer state are computed. The strongest correlation is found between total cloud cover and maximum cloud size. Studying the size density of the cloud area revealed that larger clouds contribute most to a larger total cloud cover, and not the smaller ones. Besides cloud cover, cloud-base and cloud-top height are also found to weakly correlate with the maximum cloud size, suggesting that the classic idea of deeper boundary layers accommodating larger convective thermals still holds for shallow cumulus. Sensitivity tests reveal that the results are only minimally affected by the representation of microphysics and the output resolution.

Vertically pointing radar observations combining multiple frequencies and Doppler measurements have been recently shown to contain valuable information about ice particle growth processes, such as aggregation and riming. In this study, we use a two-months X, Ka, W-Band Doppler radar dataset of midlatitude winter clouds to infer statistical growth signatures of ice and snow particles. The observational statistics are compared to forward-simulated radar moments based on simulations of the campaign time period with a high-resolution version of the ICON model and a two-moment microphysical scheme. The statistical comparison shows very good agreement of the simulated vertical structure of radar reflectivity and surface precipitation rate. The dual-wavelength ratios, which are closely related to the mean particle size, also show consistently a major increase at temperatures higher than-15 • C. However, at temperatures higher than-7 • C, ICON increasingly overestimates the mean particle size. The statistics of mean Doppler velocities also reveal that the model overestimates the terminal velocity of snow particles, especially at larger sizes. We discuss possible reasons for the identified discrepancies, such as an unrealistic temperature dependence of the sticking efficiency or the non-saturation of terminal velocities at larger sizes caused by the implemented power law relations. Our study demonstrates examples of the importance of combining various radar techniques for identifying issues in simulated microphysical processes, which can otherwise be hidden due to compensating errors.

Abstract. The science guiding the EUREC4A campaign and its measurements are presented. EUREC4A 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, 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, 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 EUREC4A 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 EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice.