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The present study analyzes novel observations of vertical wind (w)$(w)$in the tropical upper troposphere‐lower stratosphere obtained from a radar wind profiler in Cochin, India. Between December 2022 and April 2023, 63 consecutive 4 hr curtains of w$w$were measured with a vertical spacing of 180 m and a sampling time step of 44 s, thus resolving almost the whole spectrum of vertical motions. Spectra of w$w$strongly vary with altitude. They are generally flat up to the local Brunt‐Väisälä frequency (BVF), but sometimes exhibit a peak of w$w$variance closer to BVF, a feature which may be attributed to trapped gravity waves. At other times and locations, the w$w$profiles reveal Kelvin‐Helmholtz billows. Finally, the variability of w$w$variance over the 4 month campaign period is investigated. Using brightness temperature from geostationary satellites as a convective proxy, it is found that w$w$variance is highly correlated with fluctuations in convective activity. Plain Language Summary Vertical wind is a key meteorological parameter. In the tropical Upper Troposphere Lower Stratosphere (UTLS, the atmospheric layer between 14 and 20 km altitude above sea level), it crucially affects the formation of clouds and the transport of trace gases, such as water vapor, ozone and radiatively active constituents. The ensuing impacts on stratospheric composition and the Earth radiative budget have consequences for surface weather and climate. However, only a few instruments are capable of measuring vertical wind accurately in clear air, and these include VHF radars. In this study, we analyze radar measurements of UTLS vertical wind over Cochin, India taken at a 44 s sampling rate and with a vertical resolution of 180 m. Thanks to its high quality and temporal resolution, the data resolves the full spectrum of vertical motions and provides invaluable insights into the complex dynamics of the UTLS. In particular, it suggests a frequent occurrence of trapped gravity waves in this region. Trapped waves are confined vertically due to a specific vertical structure of wind and stability, but propagate long distances horizontally. The study also finds a clear relationship between vertical wind magnitude in the UTLS and convective clouds in the troposphere. Key Points Measurements of the vertical wind throughout the upper troposphere and lower stratosphere (UTLS) from a recently built radar Observations of Kelvin‐Helmholtz billows and trapped gravity waves in the tropical UTLS Impact of convection on clear‐sky vertical wind variance in the tropical UTLS

Small‐scale turbulence above 10 km is investigated using observations from two recent airborne field campaigns: the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP) and the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS). Turbulence is enhanced by factors of 2–24 inside clouds, within 100 km of active deep convection, above atmospheric jets, and above mountains coincident with strong low‐level winds. In DCOTSS, which sampled outflow from overshooting convection over the continental United States, turbulence occurred most frequently near the tropopause, indicating enhanced troposphere‐stratosphere exchange. In ACCLIP, conducted over the northwestern Pacific, turbulence was most common in the upper troposphere. We evaluate the performance of several turbulence diagnostics computed from the European Centre for Medium‐Range Weather Forecasts' fifth reanalysis (ERA5) and operational forecasts, along with the clear‐air turbulence flag recently introduced in the forecasts. Among the diagnostics tested, TI3 computed from operational forecast data is most skillful.

Turbulent air motions determine the local environment in which cloud ice crystals form. Homogeneous freezing of aqueous solution droplets is the most fundamental pathway to nucleate ice crystals in cirrus. Lack of knowledge about the role of turbulence in cirrus ice formation limits our understanding of how uncertainties in small-scale cloud processes affect the climatological radiative effect of cirrus. Here we shed first light on how turbulent fluctuations in temperature and supersaturation interact with probabilistic homogeneous freezing. We show that spatial model resolution substantially below 1–10 m is needed to properly simulate homogeneous freezing events. Importantly, microscale turbulence generates large variability in nucleated ice crystal number concentrations. Previous research ascribed this variability to mesoscale dynamical forcing due to gravity waves alone. The turbulence-generated microphysical variability has macrophysical implications. The wide range of predicted cloud radiative heating anomalies in anvil cirrus due to turbulence-ice nucleation interactions, comparable to typical mean values, is potentially large enough to affect the response of tropical cirrus cloud systems to global warming. Our results have ramifications for the multiscale modeling of cirrus clouds and the interpretation of in situ measurements.

This study uses cloud and radiative properties collected from in situ and remote sensing instruments during two coordinated campaigns over the Southern Ocean between Tasmania and Antarctica in January–February 2018 to evaluate the simulations of clouds and precipitation in nudged‐meteorology simulations with the CAM6 and AM4 global climate models sampled at the times and locations of the observations. Fifteen SOCRATES research flights sampled cloud water content, cloud droplet number concentration, and particle size distributions in mixed‐phase boundary layer clouds at temperatures down to −25°C. The 6‐week CAPRICORN2 research cruise encountered all cloud regimes across the region. Data from vertically pointing 94 GHz radars deployed was compared with radar simulator output from both models. Satellite data were compared with simulated top‐of‐atmosphere (TOA) radiative fluxes. Both models simulate observed cloud properties fairly well within the variability of observations. Cloud base and top in both models are generally biased low. CAM6 overestimates cloud occurrence and optical thickness while cloud droplet number concentrations are biased low, leading to excessive TOA reflected shortwave radiation. In general, low clouds in CAM6 precipitate at the same frequency but are more homogeneous compared to observations. Deep clouds are better simulated but produce snow too frequently. AM4 underestimates cloud occurrence but overestimates cloud optical thickness even more than CAM6, causing excessive outgoing longwave radiation fluxes but comparable reflected shortwave radiation. AM4 cloud droplet number concentrations match observations better than CAM6. Precipitating low and deep clouds in AM4 have too little snow. Further investigation of these microphysical biases is needed for both models. Key Points CAM6 and AM4 simulate observed cloud properties and compositions fairly well within the variability of observations CAM6 clouds are “too frequent, too bright”; AM4 clouds are “too few, too bright” Cloud droplet number concentration in CAM6 is typically too low; AM4 clouds include too much small ice and too little snow

The tropical tropopause layer (TTL) is a sea of vertical motions. Convectively generated gravity waves create vertical winds on scales of a few to thousands of kilometers as they propagate in a stable atmosphere. Turbulence from gravity wave breaking, radiatively driven convection, and Kelvin–Helmholtz instabilities stirs up the TTL on the kilometer scale. TTL cirrus clouds, which moderate the water vapor concentration in the TTL and stratosphere, form in the cold phases of large-scale (> 100 km) wave activity. It has been proposed in several modeling studies that small-scale (< 100 km) vertical motions control the ice crystal number concentration and the dehydration efficiency of TTL cirrus clouds. Here, we present the first observational evidence for this. High-rate vertical winds measured by aircraft are a valuable and underutilized tool for constraining small-scale TTL vertical wind variability, examining its impacts on TTL cirrus clouds, and evaluating atmospheric models. We use 20 Hz data from five National Aeronautics and Space Administration (NASA) campaigns to quantify small-scale vertical wind variability in the TTL and to see how it varies with ice water content, distance from deep convective cores, and height in the TTL. We find that 1 Hz vertical winds are well represented by a normal distribution, with a standard deviation of 0.2–0.4 m s−1. Consistent with a previous observational study that analyzed two out of the five aircraft campaigns that we analyze here, we find that turbulence is enhanced over the tropical west Pacific and within 100 km of convection and is most common in the lower TTL (14–15.5 km), closer to deep convection, and in the upper TTL (15.5–17 km), further from deep convection. An algorithm to classify turbulence and long-wavelength (5 km < λ < 100 km) and short-wavelength (λ < 5 km) gravity wave activity during level flight legs is applied to data from the Airborne Tropical TRopopause EXperiment (ATTREX). The most commonly sampled conditions are (1) a quiescent atmosphere with negligible small-scale vertical wind variability, (2) long-wavelength gravity wave activity (LW GWA), and (3) LW GWA with turbulence. Turbulence rarely occurs in the absence of gravity wave activity. Cirrus clouds with ice crystal number concentrations exceeding 20 L−1 and ice water content exceeding 1 mg m−3 are rare in a quiescent atmosphere but about 20 times more likely when there is gravity wave activity and 50 times more likely when there is also turbulence, confirming the results of the aforementioned modeling studies. Our observational analysis shows that small-scale gravity waves strongly influence the ice crystal number concentration and ice water content within TTL cirrus clouds. Global storm-resolving models have recently been run with horizontal grid spacing between 1 and 10 km, which is sufficient to resolve some small-scale gravity wave activity. We evaluate simulated vertical wind spectra (10–100 km) from four global storm-resolving simulations that have horizontal grid spacing of 3–5 km with aircraft observations from ATTREX. We find that all four models have too little resolved vertical wind at horizontal wavelengths between 10 and 100 km and thus too little small-scale gravity wave activity, although the bias is much less pronounced in global SAM than in the other models. We expect that deficient small-scale gravity wave activity significantly limits the realism of simulated ice microphysics in these models and that improved representation requires moving to finer horizontal and vertical grid spacing.

Tropical cirrus clouds form through in situ ice nucleation below the homogeneous freezing temperature of water or through detrainment from deep convection. Despite their importance, limited understanding of their evolution and formation pathways contributes to large uncertainty in climate projections. To address these challenges, we implement novel passive tracers in the System for Atmospheric Modeling (SAM) cloud-resolving model to track the three-dimensional development of cirrus clouds. One tracer tracks air parcels exiting convective updrafts, revealing a rapid decline in ice crystal size and number as anvils age. Another tracer focuses on in situ cirrus, capturing their formation in the cold upper atmosphere and the subsequent reduction in their ice crystal number over time. We find that in situ cirrus dominate at colder temperatures and lower ice water contents, while anvil cirrus prevail at temperatures > −60 °C. Despite the frequent occurrence of in situ cirrus within the tropical tropopause layer, they account for only 6 %–7 % of the total tropical cirrus cloud top-of-the-atmosphere radiative effect. These findings improve our ability to assess the distinct roles of convective and in situ cirrus in shaping tropical cirrus properties and their impacts on climate. We also improve the model's representation of tropical cirrus through simple, computationally inexpensive microphysics modifications, improving agreement with tropical aircraft observations. We show that updrafts critical for tropical cirrus formation are only resolved in our simulations at a horizontal grid spacing of 250 m – much finer than those used in global storm-resolving models.

Recent advances in computing power have made it possible to run global atmospheric models with comprehensive physics with finer grid spacing than ever before. These models, called global storm-resolving models (GSRMs), explicitly simulate a wide range of dynamics from the mesoscale up to the planetary scale, making it possible to trace the impact of certain cloud-scale processes on the radiative budget of the Earth. GSRMs are particularly valuable when used in conjunction with observational datasets. Observations are critical for evaluating the representation of clouds in GSRMs, and GSRMs are useful for building a process-level understanding of the origin of observed cloud features. This work leverages data from 9 aircraft campaigns and 4 remote sensing datasets, and model output from 9 GSRM simulations, to explore three different topics in cloud physics: secondary ice production in Southern Ocean clouds, the sensitivity of tropical anvils to model microphysics, and the impact of small-scale motions on thin cirrus clouds in the tropical tropopause layer.

Mixed-phase Southern Ocean clouds are challenging to simulate, and their representation in climate models is an important control on climate sensitivity. In particular, the amount of supercooled water and frozen mass that they contain in the present climate is a predictor of their planetary feedback in a warming climate. The recent Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) vastly increased the amount of in situ data available from mixed-phase Southern Ocean clouds useful for model evaluation. Bulk measurements distinguishing liquid and ice water content are not available from SOCRATES, so single-particle phase classifications from the Two-Dimensional Stereo (2D-S) probe are invaluable for quantifying mixed-phase cloud properties. Motivated by the presence of large biases in existing phase discrimination algorithms, we develop a novel technique for single-particle phase classification of binary 2D-S images using a random forest algorithm, which we refer to as the University of Washington Ice–Liquid Discriminator (UWILD). UWILD uses 14 parameters computed from binary image data, as well as particle inter-arrival time, to predict phase. We use liquid-only and ice-dominated time periods within the SOCRATES dataset as training and testing data. This novel approach to model training avoids major pitfalls associated with using manually labeled data, including reduced model generalizability and high labor costs. We find that UWILD is well calibrated and has an overall accuracy of 95 % compared to 72 % and 79 % for two existing phase classification algorithms that we compare it with. UWILD improves classifications of small ice crystals and large liquid drops in particular and has more flexibility than the other algorithms to identify both liquid-dominated and ice-dominated regions within the SOCRATES dataset. UWILD misclassifies a small percentage of large liquid drops as ice. Such misclassified particles are typically associated with model confidence below 75 % and can easily be filtered out of the dataset. UWILD phase classifications show that particles with area-equivalent diameter (Deq)  < 0.17 mm are mostly liquid at all temperatures sampled, down to −40 ∘C. Larger particles (Deq>0.17 mm) are predominantly frozen at all temperatures below 0 ∘C. Between 0 and 5 ∘C, there are roughly equal numbers of frozen and liquid mid-sized particles (0.170.33 mm) are mostly frozen. We also use UWILD's phase classifications to estimate sub-1 Hz phase heterogeneity, and we show examples of meter-scale cloud phase heterogeneity in the SOCRATES dataset.

Southern Ocean boundary layer clouds affect global albedo and oceanic heat uptake. Most climate models and reanalyses underestimate cloudiness in the Southern Ocean, which biases seas surface temperatures and tropospheric winds, and likely influences the global atmospheric circulation and oceanic heat uptake. This robust and persistent model bias reveals gaps in our understanding of the physical controls on the formation and evolution of low clouds in the Southern Ocean, compared to more well-studied regions. The physics of Southern Ocean boundary layer clouds are uncertain due, in part, to a lack of in-situ observations in the region. Here, I use recent state-of-the-art measurements from the SOCRATES aircraft campaign and cloud resolving simulations, to investigate the influence of synoptic dynamics, boundary layer structure and microphysical properties on Southern Ocean boundary layer clouds. I developed a technique for simulating boundary layer clouds in the synoptically active Southern Ocean with a large eddy simulation (LES) and I set up five modelling case studies from SOCRATES observations. I find that the LES realistically represents diverse boundary layer structures but produces clouds with persistently low liquid water paths. CAM6 persistently underestimates droplet concentrations and cloud driven turbulence.