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Adrian A. Hill
,
Graham Feingold
, and
Hongli Jiang

Abstract

This study uses large-eddy simulation with bin microphysics to investigate the influence of entrainment and mixing on aerosol–cloud interactions in the context of idealized, nocturnal, nondrizzling marine stratocumulus (Sc). Of particular interest are (i) an evaporation–entrainment effect and a sedimentation–entrainment effect that result from increasing aerosol concentrations and (ii) the nature of mixing between clear and cloudy air, where homogeneous and extreme inhomogeneous mixing represent the bounding mixing types. Simulations are performed at low resolution (Δz = 20 m; Δx, y = 40 m) and high resolution (Δz = 10 m; Δx, y = 20 m). It is demonstrated that an increase in aerosol from clean conditions (100 cm−3) to polluted conditions (1000 cm−3) produces both an evaporation–entrainment and a sedimentation–entrainment effect, which couple to cause about a 10% decrease in liquid water path (LWP) when all warm microphysical processes are included. These dynamical effects are insensitive to both the resolutions tested and the mixing assumption. Regardless of resolution, assuming extreme inhomogeneous rather than homogeneous mixing results in a small reduction in cloud-averaged drop number concentration, a small increase in cloud drop effective radius, and ∼1% decrease in cloud optical depth. For the case presented, these small changes play a negligible role when compared to the impact of increasing aerosol and the associated entrainment effects. Finally, it is demonstrated that although increasing resolution causes an increase in LWP and number concentration, the relative sensitivity of cloud optical depth to changes in aerosol is unaffected by resolution.

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Zachary J. Lebo
,
Ben J. Shipway
,
Jiwen Fan
,
Istvan Geresdi
,
Adrian Hill
,
Annette Miltenberger
,
Hugh Morrison
,
Phil Rosenberg
,
Adam Varble
, and
Lulin Xue
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Adrian A. Hill
,
Zachary J. Lebo
,
Miroslaw Andrejczuk
,
Sylwester Arabas
,
Piotr Dziekan
,
Paul Field
,
Andrew Gettelman
,
Fabian Hoffmann
,
Hanna Pawlowska
,
Ryo Onishi
, and
Benoit Vié

Abstract

The Kinematic Driver-Aerosol (KiD-A) intercomparison was established to test the hypothesis that detailed warm microphysical schemes provide a benchmark for lower-complexity bulk microphysics schemes. KiD-A is the first intercomparison to compare multiple Lagrangian cloud models (LCMs), size bin-resolved schemes, and double-moment bulk microphysics schemes in a consistent 1D dynamic framework and box cases. In the absence of sedimentation and collision-coalescence, the drop size distributions (DSDs) from the LCMs exhibit similar evolution with expected physical behaviors and good inter-scheme agreement, with the volume mean diameter (Dvol ) from the LCMs within 1 to 5% of each other. In contrast, the bin schemes exhibit non-physical broadening with condensational growth. These results further strengthen the case that LCMs are an appropriate numerical benchmark for DSD evolution under condensational growth. When precipitation processes are included, however, the simulated liquid water path, precipitation rates, and response to modified cloud drop/aerosol number concentrations from the LCMs vary substantially, while the bin and bulk schemes are relatively more consistent with each other. The lack of consistency in the LCM results stems from both the collision-coalescence process and the sedimentation process, limiting their application as a numerical benchmark for precipitation processes. Reassuringly, however, precipitation from bulk schemes, which are the basis for cloud microphysics in weather and climate prediction, is within the spread of precipitation from the detailed schemes (LCMs and bin). Overall, this intercomparison identifies the need for focused effort on the comparison of collision-coalescence methods and sedimentation in detailed microphysics schemes, especially LCMs.

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Greg M. McFarquhar
,
Christopher S. Bretherton
,
Roger Marchand
,
Alain Protat
,
Paul J. DeMott
,
Simon P. Alexander
,
Greg C. Roberts
,
Cynthia H. Twohy
,
Darin Toohey
,
Steve Siems
,
Yi Huang
,
Robert Wood
,
Robert M. Rauber
,
Sonia Lasher-Trapp
,
Jorgen Jensen
,
Jeffrey L. Stith
,
Jay Mace
,
Junshik Um
,
Emma Järvinen
,
Martin Schnaiter
,
Andrew Gettelman
,
Kevin J. Sanchez
,
Christina S. McCluskey
,
Lynn M. Russell
,
Isabel L. McCoy
,
Rachel L. Atlas
,
Charles G. Bardeen
,
Kathryn A. Moore
,
Thomas C. J. Hill
,
Ruhi S. Humphries
,
Melita D. Keywood
,
Zoran Ristovski
,
Luke Cravigan
,
Robyn Schofield
,
Chris Fairall
,
Marc D. Mallet
,
Sonia M. Kreidenweis
,
Bryan Rainwater
,
John D’Alessandro
,
Yang Wang
,
Wei Wu
,
Georges Saliba
,
Ezra J. T. Levin
,
Saisai Ding
,
Francisco Lang
,
Son C. H. Truong
,
Cory Wolff
,
Julie Haggerty
,
Mike J. Harvey
,
Andrew R. Klekociuk
, and
Adrian McDonald

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 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.

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