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Previous generations of climate models have been shown to under‐estimate the occurrence of tropical low‐level clouds and to over‐estimate their radiative effects. This study analyzes outputs from multiple climate models participating in the Fifth phase of the Coupled Model Intercomparison Project (CMIP5) using the Cloud Feedback Model Intercomparison Project Observations Simulator Package (COSP), and compares them with different satellite data sets. Those include CALIPSO lidar observations, PARASOL mono‐directional reflectances and CERES radiative fluxes at the top of the atmosphere. We show that current state‐of‐the‐art climate models predict overly bright low‐clouds, even for a correct low‐cloud cover. The impact of these biases on the Earth' radiation budget, however, is reduced by compensating errors. Those include the tendency of models to under‐estimate the low‐cloud cover and to over‐estimate the occurrence of mid‐ and high‐clouds above low‐clouds. Finally, we show that models poorly represent the dependence of the vertical structure of low‐clouds on large‐scale environmental conditions. The implications of this ‘too few, too bright low‐cloud problem’ for climate sensitivity and model development are discussed. Key Points Low clouds too optically thick; particularly shallow cumulus clouds Compensating errors: underestimate low‐cloud & overestimate high‐cloud fraction Relative frequency of stratocumulus & shallow cumulus clouds not captured well

Anomalous tropical longwave cloud‐radiative heating of the atmosphere is generated when convective precipitation occurs, which plays an important role in the dynamics of tropical disturbances. Defining the observed cloud‐radiative feedback as the reduction of top‐of‐atmosphere longwave radiative cooling per unit precipitation, the feedback magnitudes are sensitive to the observed precipitation data set used when comparing two versions of Global Precipitation Climatology Project, version 1.3 (GPCPv1.3) and the newer version 3.2 (GPCPv3.2). GPCPv3.2 contains larger magnitudes and variance of daily precipitation, which yields a weaker cloud‐radiative feedback in tropical disturbances at all frequencies and zonal wavenumbers. Weaker cloud‐radiative feedbacks occur in GPCPv3.2 at shorter zonal lengths on intraseasonal timescales, which implies a preferential growth at planetary scales for the Madden‐Julian oscillation. Phase relationships between precipitation, radiative heating, and other thermodynamic variables in eastward‐propagating gravity waves also change with the updated GPCPv3.2. Plain Language Summary High‐altitude, widespread anvil clouds are generated when heavy convective precipitation occurs in the tropics. These clouds are not only a passive product produced by convection, but they also can subsequently enhance convection by trapping upward infrared radiative flux emitted by the Earth, effectively heating the atmosphere. This additional radiative heating effect can induce upward motion in the tropics, supporting the convective systems by transporting more humid air from below. However, the strength of this cloud‐radiative feedback is hard to estimate because global, continuous observations of surface precipitation are difficult to derive. In this study, the strength of the radiative feedback is calculated using the same product of observed radiative heating against two different observational precipitation products. A newer improved precipitation product yields much weaker radiative feedback strengths for all types of tropical weather systems. In addition, cloud‐radiative heating is found to substantially lag behind precipitation in certain fast, eastward‐propagating tropical rainfall systems in the newer precipitation product, unlike the older one. Why such a lag exists is unclear. The discrepancy of the estimation of cloud‐radiative feedback strengths and properties in the older versus the newer precipitation products indicates that our understanding of mechanisms supporting tropical disturbances is still incomplete. Key Points The updated Global Precipitation Climatology Project (GPCP) precipitation product has more frequent high rain rates, yielding a weaker longwave radiative feedback The updated radiative feedback supports less moistening of the Madden‐Julian oscillation, but imposes stronger planetary scale selection The phase relationship between precipitation and thermodynamic fields in eastward‐propagating tropical waves are sensitive to GPCP versions

Large‐eddy simulation is used to study the sensitivity of trade wind cumulus clouds to perturbations in cloud droplet number concentrations. We find that the trade wind cumulus system approaches a radiative‐convective equilibrium state, modified by net warming and drying from imposed large‐scale advective forcing. The system requires several days to reach equilibrium when cooling rates are specified but much less time, and with less sensitivity to cloud droplet number density, when radiation depends realistically on the vertical distribution of water vapor. The transient behavior and the properties of the near‐equilibrium cloud field depend on the microphysical state and therefore on the cloud droplet number density, here taken as a proxy for the ambient aerosol. The primary response of the cloud field to changes in the cloud droplet number density is deepening of the cloud layer. This deepening leads to a decrease in relative humidity and a faster evaporation of small clouds and cloud remnants constituting a negative lifetime effect. In the near‐equilibrium regime, the decrease in cloud cover compensates much of the Twomey effect, i.e., the brightening of the clouds, and the overall aerosol effect on the albedo of the organized precipitating cumulus cloud field is small. Key Points: The trade wind cumulus system approaches a radiative‐convective equilibrium Clear sky radiative effects accelerate the adjustment to equilibrium More cloud droplets lead to deeper and drier cloud layers and hence less cloud

This paper reports on a new index for low cloud cover (LCC), the estimated cloud-top entrainment index (ECTEI), which is a modification of estimated inversion strength (EIS) and takes into account a cloud-top entrainment (CTE) criterion. Shipboard cloud observation data confirm that the index is strongly correlated with LCC. It is argued here that changes in LCC cannot be fully determined from changes in EIS only, but can be better determined from changes in both EIS and sea surface temperature (SST) based on the ECTEI. Furthermore, it is argued that various proposed predictors of LCC change, including the moist static energy vertical gradient, SST, and midlevel clouds, can be better understood from the perspective of the ECTEI.

The Arctic is warming at more than twice the rate of the global average. This warming is influenced by clouds, which modulate the solar and terrestrial radiative fluxes and, thus, determine the surface energy budget. However, the interactions among clouds, aerosols, and radiative fluxes in the Arctic are still poorly understood. To address these uncertainties, the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) study was conducted from September 2019 to August 2020 in Ny-Ålesund, Svalbard. The campaign’s primary goal was to elucidate the life cycle of aerosols in the Arctic and to determine how they modulate cloud properties throughout the year. In situ and remote sensing observations were taken on the ground at sea level, at a mountaintop station, and with a tethered balloon system. An overview of the meteorological and the main aerosol seasonality encountered during the NASCENT year is introduced, followed by a presentation of first scientific highlights. In particular, we present new findings on aerosol physicochemical and molecular properties. Further, the role of cloud droplet activation and ice crystal nucleation in the formation and persistence of mixed-phase clouds, and the occurrence of secondary ice processes, are discussed and compared to the representation of cloud processes within the regional Weather Research and Forecasting Model. The paper concludes with research questions that are to be addressed in upcoming NASCENT publications.

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.

Satellite observations show a near-zero trend in the top-of-atmosphere global-mean net cloud radiative effect (CRE), suggesting that clouds did not further cool nor heat the planet over the last two decades. The causes of this observed trend are unknown and can range from effective radiative forcing (ERF) to cloud feedbacks, cloud masking, and internal variability. We find that the near-zero NetCRE trend is a result of a significant negative trend in the longwave (LW) CRE and a significant positive trend in the shortwave (SW) CRE, cooling and heating the climate system, respectively. We find that it is exceptionally unlikely (<1% probability) that internal variability can explain the observed LW and SW CRE trends. Instead, the majority of the observed LWCRE trend arises from cloud masking wherein increases in greenhouse gases reduce OLR in all-sky conditions less than in clear-sky conditions. In SWCRE, rapid cloud adjustments to greenhouse gases, aerosols, and natural forcing agents (ERF) explain a majority of the observed trend. Over the northeast Pacific, we show that ERF, hitherto an ignored factor, contributes as much as cloud feedbacks to the observed SWCRE trend. Large contributions from ERF and cloud masking to the global-mean LW and SW CRE trends are supplemented by negative LW and positive SW cloud feedback trends, which are detectable at 80%–95% confidence depending on the observational uncertainty assumed. The large global-mean LW and SW cloud feedbacks cancel, leaving a small net cloud feedback that is unconstrained in sign, implying that clouds could amplify or dampen global warming.

Cirrus dominate the longwave radiative budget of the tropics. For the first time, the variability in cirrus properties and longwave cloud radiative effects (CREs) that arises from using different microphysical schemes within nudged global storm‐resolving simulations from a single model, is quantified. Nudging allows us to compute radiative biases precisely using coincident satellite measurements and to fix the large‐scale dynamics across our set of simulations to isolate the influence of microphysics. We run 5‐day simulations with four commonly‐used microphysics schemes of varying complexity (SAM1MOM, Thompson, M2005 and P3) and find that the tropical average longwave CRE varies over 20 W m−2 between schemes. P3 best reproduces observed longwave CRE. M2005 and P3 simulate cirrus with realistic frozen water path but unrealistically high ice crystal number concentrations which commonly hit limiters and lack the variability and dependence on frozen water content seen in aircraft observations. Thompson and SAM1MOM have too little cirrus. Plain Language Summary Recently, advancements in computing have made it possible for atmospheric scientists to simulate Earth's global atmosphere with higher resolution than ever before. This new generation of models, called global‐storm resolving models, have a horizontal grid spacing of just a few kilometers, which permits the formation of thunderstorms. As a result, they simulate clouds more realistically than traditionally climate and weather models and are a great tool for diagnosing cloud biases in atmospheric models. Here, we run a single global storm‐resolving model with four different representations of cloud physics called M2005, P3, SAM1MOM and Thompson. We evaluate simulated tropical cirrus, which are stratiform ice clouds at the top of the troposphere that reduce the amount of infrared radiation emitted by the Earth, with satellite and aircraft data to see which representations have the best performance. SAM1MOM and Thompson make too little cirrus causing too much infrared radiation to be emitted, M2005 makes too much cirrus, causing too little infrared radiation to be emitted, and P3 makes about the right amount. Key Points Nudged global storm‐resolving simulations are valuable for microphysics sensitivity studies Mean tropical longwave cloud radiative effect varies over 20 W m−2 depending on microphysics scheme Two‐moment schemes outperform simpler one‐moment and partial double‐moment schemes, and P3 has the smallest longwave radiative bias

As a key macrophysical property, cloud horizontal scale plays a critical role in cloud radiative effect (CRE), precipitation and convective structures. Until now, however, how cloud scales vary with surface temperature anomaly and their subsequent impacts on CRE and precipitation remains unclear. This study fills the knowledge gap utilizing active satellite observations and finds cloud‐scale temperature sensitivity is strongly dependent on cloud height. Specifically, percentage of small‐scale clouds (<50 km) significantly decreases at low altitude but increases at high altitude, implying overall rising cloud height. The variations in low‐level small‐scale clouds account for 56.1% and 42.6% of the weakened shortwave cooling and longwave warming, while large‐scale clouds (>100 km) contribute insignificantly. Notably, robust increases in precipitation intensity occur only for low‐level large‐scale clouds, with 15.2% explained by decreased cloud optical depth, while precipitation percentage increases by 0.1%–0.5% K−1 across scales. Our results provide valuable observational constraints on cloud feedbacks.

A modified microphysics scheme is implemented in the Community Atmosphere Model, version 5 (CAM5). The new scheme features prognostic precipitation. The coupling between the microphysics and the rest of the model is modified to make it more flexible. Single-column tests show the new microphysics can simulate a constrained drizzling stratocumulus case. Substepping the cloud condensation (macrophysics) within a time step improves single-column results. Simulations of mixed-phase cases are strongly sensitive to ice nucleation. The new microphysics alters process rates in both single-column and global simulations, even at low (200 km) horizontal resolution. Thus, prognostic precipitation can be important, even in low-resolution simulations where advection of precipitation is not important. Accretion dominates as liquid water path increases in agreement with cloud-resolving model simulations and estimates from observations. The new microphysics with prognostic precipitation increases the ratio of accretion over autoconversion. The change in process rates appears to significantly reduce aerosol–cloud interactions and indirect radiative effects of anthropogenic aerosols by up to 33% (depending on substepping) to below 1 W m−2of cooling between simulations with preindustrial (1850) and present-day (2000) aerosol emissions.