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The responses of tropical anvil cloud and low‐level cloud to a warming climate are among the largest sources of uncertainty in our estimates of climate sensitivity. However, most research on cloud feedbacks relies on either global climate models with parameterized convection, which do not explicitly represent small‐scale convective processes, or small‐domain models, which cannot directly simulate large‐scale circulations. We investigate how self‐aggregation, the spontaneous clumping of convection in idealized numerical models, depends on cloud‐radiative interactions with different cloud types, sea surface temperatures (SSTs), and stages of aggregation in simulations that form part of RCEMIP (the Radiative‐Convective Equilibrium Model Intercomparison Project). Analysis shows that the presence of anvil cloud, which tends to enhance aggregation when collocated with anomalously moist environments, is reduced in nearly all models when SSTs are increased, leading to a corresponding reduction in the aggregating influence of cloud‐longwave interactions. We also find that cloud‐longwave radiation interactions are stronger in the majority of General Circulation Models (GCMs), typically resulting in faster aggregation compared to Cloud‐system Resolving Models (CRMs). GCMs that have stronger cloud‐longwave interactions tend to aggregate faster, whereas the influence of circulations is the main factor affecting the aggregation rate in CRMs. Plain Language Summary The spatial organization of tropical rainstorms has major effects on weather and climate. This organization influences the duration and intensity of these convective storms, and alters the amount of radiation absorbed and emitted by the atmosphere. There is great uncertainty in the response of organization to a warming climate, and this results in one of the largest sources of uncertainty in climate predictions. Climate projections rely on either General Circulation Models (GCMs) that can represent the large‐scale motions, or smaller high‐resolution models that represent small‐scale features like cloud formations, but not the large motions. In this study, we compare convective organization in GCMs and Cloud‐system Resolving Models (CRMs) across a range of sea surface temperatures (SSTs). We find that the cloud‐radiation feedbacks that make the convective environment more favorable for further convection, and the non‐convective environment less favorable for convection, are stronger in GCMs than CRMs on average. This is related to larger cloud amounts in GCMs, leading GCMs to have typically faster organization than CRMs. We find these feedbacks which drive aggregation decrease as SST increases, yet the aggregation rate is largely insensitive to SST because of the decrease in the effect of atmospheric motions that oppose aggregation. Key Points General Circulation Models (GCMs) aggregate faster than Cloud‐system Resolving Models (CRMs) on average due to an enhanced longwave feedback Feedbacks tend to decrease in magnitude as sea surface temperature increases, although the rate of aggregation remains similar Aggregation rate in GCMs is correlated with diabatic feedbacks, while in CRMs it is more related to advection feedbacks

A shallow cumulus cloud transition from a sugar to flower type of organization occurred under a layer of mineral dust on 2 February 2020, during the multinational Atlantic Tradewind Ocean‐Atmosphere Mesoscale Interaction Campaign (ATOMIC) and the Elucidating the Role of Clouds‐Circulation Coupling in Climate (EUREC4A) campaigns. Lagrangian large eddy simulations following an airmass trajectory along the tradewinds are used to explore radiative impacts of the diel cycle and mineral dust on the sugar‐to‐flower (S2F) cloud transition. The large‐scale meteorological forcing is derived from the European Center for Medium‐Range Weather Forecasts Reanalysis Fifth Generation and based on aerosol measurements from the U.S. Ronald H. Brown Research Vessel and the French ATR‐42 Research Aircraft during the field campaigns. A 12‐hr delay in the diel cycle accelerates the S2F transition at night, leading to more cloud liquid water and precipitation. The aggregated clouds generate more and stronger cold pools, which alter the original mechanism responsible for the organization. Although there is still mesoscale moisture convergence in the cloud layer, the near‐surface divergence associated with cold pools transports the subcloud moisture to the drier surrounding regions. New convection forms along the cold‐pool edges, generating new flower clouds. The modulation of the surface radiative budget by free‐tropospheric mineral dust poses a less dramatic effect on the S2F transition. Mineral dust releases longwave radiation, reducing the cloud amount at night, and absorbs shortwave radiation during the day, cooling the boundary‐layer temperature and increasing the overall cloud amount. Cloud‐top radiative heating because of more clouds strengthens the mesoscale organization, enlarging the aggregate areas, and increasing the cloud amount further. Plain Language Summary During a joint field study called ATOMIC and EUREC4A, a transition between two cloud systems took place during the day on 2 February 2020. Very small and shallow clouds called “sugar” transitioned into deeper and wider cloud aggregates called “flowers.” A dense mineral‐dust layer was also observed above the tradewind cumulus cloud field, likely modulating the radiation interacting with the clouds. High‐resolution simulations are applied to help understand the same cloud transition as if it had taken place at night, and to explore the impacts of mineral dust on the transition. A 12‐hr delay in the daily cycle such that the transition occurs at night affects the cloud transition more significantly than when the transition occurs during the day under a layer of mineral dust. The cloud transition that occurs at night produces more clouds and rain. The mineral dust blocks the solar radiation and cools the air beneath during the day, but does not change the cloud and rain amount as much. Key Points The transition from sugar to flowers occurs more rapidly at night, producing more cloud and rain, with stronger organization and cold pools Precipitation and cold pools weaken the mechanism of cloud aggregation as they transport moisture to drier regions to form new convection Mineral dust above the clouds modulates radiative fluxes below leading to weaker mesoscale organization at night but stronger during the day

Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity （typically less than 2%） to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.

Aerosol and aerosol-cloud radiation interactions significantly influence Earth’s radiative balance, hydrological cycle, global monsoons, atmospheric circulation, and climate, attracting substantial scientific attention. This study employs bibliometric and quantitative trend analyses to evaluate the development, knowledge structure, and research trends in aerosol and aerosol-cloud radiation interactions from 1999 to 2023 using Web of Science Core Collection data. Results reveal a consistent increase in publications and citations, indicating sustained attention in this field. The USA and China are identified as the most prolific countries, with significant contributions from institutions like the National Aeronautics and Space Administration and the Chinese Academy of Sciences. However, while the USA shows a recent decline in growth, China has demonstrated a significant upward trend in research contributions. Productive journals include Atmospheric Chemistry and Physics and the Journal of Geophysical Research-Atmospheres, with prolific authors such as Babu S. Suresh and Li Zhanqing. A co-occurrence analysis of keywords identifies research topics focused on aerosol optical properties, aerosol types, aerosol radiation interactions, and aerosol-cloud interactions. Emerging trends emphasize advanced methodologies such as remote sensing, model simulation, and artificial intelligence, with growing attention to regions like the Southern Ocean and the Arctic. This comprehensive analysis provides valuable insights for researchers, identifying knowledge gaps and guiding future research directions in aerosol and aerosol-cloud radiation interactions, which are crucial for understanding their climatic and atmospheric impacts.

Aerosols significantly affect cloud microphysics and energy budget in different ways. The contribution of the direct, semi‐direct, and indirect effects of aerosols on radiation are here investigated over the North Atlantic tropical ocean under different aerosol loadings. The Weather Research and Forecasting Model is used to perform a set of numerical idealized experiments, which are forced with prescribed aerosol profiles. We evaluate the effects of aerosols on modeled shallow clouds and surface radiative budget. The results indicate that large aerosol loadings are associated with enhanced cloudiness and reduced precipitation. While the change in rainfall is mainly due to the larger number of smaller droplets, the change in cloudiness is attributed to the effects of absorbing aerosols, mainly dust particles, which are responsible for a rise of temperature that feeds back onto specific humidity. As in the boundary layer the increase of moisture dominates, the net effect is a higher relative humidity, which favors the formation of thin low non‐precipitating clouds. The feedback accounts for a dynamical change in the lower troposphere: shortwave radiation absorption increases temperature at the top of the marine atmospheric boundary‐layer and reduces entrainment of warm and dry air, increasing low level moisture content. Despite the overall increase in cloudiness, daytime cloud cover is reduced. The semi‐direct effect of aerosols on clouds results in a warming of the surface, opposite to the indirect effect. Large aerosol loads are associated with enhanced cloudiness and reduced precipitation. Shortwave radiation absorption increases temperature at the top of the marine atmospheric boundary‐layer and reduces entrainment of warm and dry air, increasing low level moisture content. Despite the overall increase in cloudiness, daytime cloud cover is reduced. The semi‐direct effect of aerosols on clouds results in a warming of the surface, opposite to the indirect effect.

Strong lensing offers a precious opportunity for studying the formation and early evolution of super star clusters that are rare in our cosmic backyard. The Sunburst Arc, a lensed Cosmic Noon galaxy, hosts a young super star cluster with escaping Lyman continuum radiation. Analyzing archival Hubble Space Telescope images and emission line data from Very Large Telescope/MUSE and X-shooter, we construct a physical model for the cluster and its surrounding photoionized nebula. We confirm that the cluster is ≲4 Myr old, is extremely massive M ⋆ ∼ 107 M ⊙, and yet has a central component as compact as several parsecs, and we find a gas-phase metallicity Z = (0.22 ± 0.03)Z ⊙. The cluster is surrounded by ≳105 M ⊙ of dense clouds that have been pressurized to P ∼ 109 K cm−3 by perhaps stellar radiation at within 10 pc. These should have large neutral columns N HI > 1022.8 cm−2 to survive rapid ejection by radiation pressure. The clouds are likely dusty as they show gas-phase depletion of silicon, and may be conducive to secondary star formation if N HI > 1024 cm−2 or if they sink farther toward the cluster center. Detecting strong [N iii]λ λ 1750,1752, we infer heavy nitrogen enrichment log(N/O)=−0.21−0.11+0.10 . This requires efficiently retaining ≳500 M ⊙ of nitrogen in the high-pressure clouds from massive stars heavier than 60 M ⊙ up to 4 Myr. We suggest a physical origin of the high-pressure clouds from partial or complete condensation of slow massive star ejecta, which may have an important implication for the puzzle of multiple stellar populations in globular clusters.

The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) is a satellite mission implemented by the European Space Agency (ESA), in cooperation with the Japan Aerospace Exploration Agency (JAXA), to measure global profiles of aerosols, clouds and precipitation properties together with radiative fluxes and derived heating rates. The simultaneous measurements of the vertical structure and horizontal distribution of cloud and aerosol fields, together with outgoing radiation, will be used in particular to evaluate their representation in weather forecasting and climate models and to improve our understanding of cloud and aerosol radiative impact and feedback mechanisms. To achieve the objective, the goal is that a retrieved scene with footprint size of 10 km × 10 km is measured with sufficiently high resolution that the atmospheric vertical profile of short-wave (solar) and long-wave (thermal) flux can be reconstructed with an accuracy of 10 W m−2 at the top of the atmosphere. To optimise the performance of the two active instruments, the platform will fly at a relatively low altitude of 393 km, with an equatorial revisit time of 25 d. The scientific payload consists of four instruments: an atmospheric lidar, a cloud-profiling radar with Doppler capability, a multi-spectral imager and a broadband radiometer. Co-located measurements from these instruments are processed in the ground segment, which produces and distributes a wide range of science data products. As well as the Level 1 (L1) product of each instrument, a large number of multiple-instrument L2 products have been developed, in both Europe and Japan, benefiting from the data synergy. An end-to-end simulator and several test scenes have been developed that simulate EarthCARE observations and provide a development and test environment for L1 and L2 processors. Within this paper the EarthCARE observational requirements are addressed. An overview is given of the space segment with a detailed description of the four science instruments, demonstrating how the observational requirements will be met. Furthermore, the elements of the space segment and ground segment that are relevant for science data users are described and the data products are introduced.

Mineral dust impacts key processes in the Earth system, including the radiation budget, clouds, and nutrient cycles. We evaluate dust aerosols in 16 models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) against multiple reanalyses and observations. We note that both the reanalyses and observations used here have their limitations and particularly that dust emission and deposition in reanalyses are poorly constrained. Most models, and particularly the multi-model ensemble mean (MEM), capture the spatial patterns and seasonal cycles of global dust processes well. However, large uncertainties and inter-model diversity are found. For example, global dust emissions, primarily driven by model-simulated surface winds, vary by a factor of 5 across models, while the MEM estimate is double the amount in reanalyses. The ranges of CMIP6 model-simulated global dust emission, deposition, burden, and optical depth (DOD) are larger than previous generations of models. Models present considerable disagreement in dust seasonal cycles over North China and North America. Here, DOD values are overestimated by most CMIP6 models, with the MEM estimate 1.2–1.7 times larger compared to satellite and reanalysis datasets. Such overestimates can reach up to a factor of 5 in individual models. Models also fail to reproduce some key features of the regional dust distribution, such as dust accumulation along the southern edge of the Himalayas. Overall, there are still large uncertainties in CMIP6 models' simulated dust processes, which feature inconsistent biases throughout the dust life cycle between models, particularly in the relationship connecting dust mass to DOD. Our results imply that modelled dust processes are becoming more uncertain as models become more sophisticated. More detailed output and dust size-resolved variables in particular, relating to the dust cycle in future intercomparison projects, are needed to enable better constraints of global dust cycles and enable the potential identification of observationally constrained links between dust cycles and optical properties.

Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.

There is great interest in wind-borne mineral dust because of the role that dust plays in climate by modulating solar radiation and cloud properties. Today, much research focuses on North Africa because it is Earth’s largest and most persistently active dust source. Moreover, this region is expected to be greatly impacted by climate change, which would affect dust emission rates. Interest in dust was stimulated over 50 years ago when it was discovered that African dust was frequently transported across the Atlantic in great quantities. Here we report on the initial discovery of African dust in the Caribbean Basin. We show that there were three independent “first” discoveries of African dust in the 1950s through the 1960s. In each case, the discoverers were not seeking dust but, rather, they had other research objectives. The meteorological context of African dust transport was first elucidated in 1969 with the characterization of the Saharan air layer (SAL) and its role in effecting the efficient transport of African dust over great distances to the Western Hemisphere. The link between dust transport and African climate was established in the 1970s and 1980s when dust transport to the Caribbean increased greatly following the onset of severe drought in the Sahel. Here we chronicle these events and show how they contributed to our current state of knowledge.