Search for: All records

Abstract. 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. 

Abstract. Mixed-phase Southern Ocean clouds are challenging to simulate, and theirrepresentation in climate models is an important control on climatesensitivity. In particular, the amount of supercooled water and frozen massthat they contain in the present climate is a predictor of their planetaryfeedback in a warming climate. The recent Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) vastly increased theamount of in situ data available from mixed-phase Southern Ocean clouds usefulfor model evaluation. Bulk measurements distinguishing liquid and ice watercontent are not available from SOCRATES, so single-particle phaseclassifications from the Two-Dimensional Stereo (2D-S) probe are invaluablefor quantifying mixed-phase cloud properties. Motivated by the presence oflarge biases in existing phase discrimination algorithms, we develop a noveltechnique for single-particle phase classification of binary 2D-S images usinga random forest algorithm, which we refer to as the University of WashingtonIce–Liquid Discriminator (UWILD). UWILD uses 14 parameters computed frombinary image data, as well as particle inter-arrival time, to predict phase.We use liquid-only and ice-dominated time periods within the SOCRATES datasetas training and testing data. This novel approach to model training avoidsmajor pitfalls associated with using manually labeled data, including reducedmodel generalizability and high labor costs. We find that UWILD is wellcalibrated and has an overall accuracy of 95 % compared to72 % and 79 % for two existing phase classificationalgorithms that we compare it with. UWILD improves classifications of smallice crystals and large liquid drops in particular and has more flexibilitythan the other algorithms to identify both liquid-dominated and ice-dominatedregions within the SOCRATES dataset. UWILD misclassifies a small percentageof large liquid drops as ice. Such misclassified particles are typicallyassociated with model confidence below 75 % and can easily befiltered out of the dataset. UWILD phase classifications show that particleswith area-equivalent diameter (Deq)  < 0.17 mm are mostlyliquid at all temperatures sampled, down to −40 ∘C. Largerparticles (Deq>0.17 mm) are predominantly frozen at alltemperatures 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 phaseclassifications to estimate sub-1 Hz phase heterogeneity, and we showexamples of meter-scale cloud phase heterogeneity in the SOCRATES dataset. 

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.

 

Abstract 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 cloudsnucleating 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 RV 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 a 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, multi-layered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of 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.