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  • American Meteorological Society  (2)
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  • 1
    Publication Date: 2019-01-21
    Description: Two case studies of marine stratocumulus (one nocturnal and drizzling, the other daytime and nonprecipitating) are simulated by the UCLA large-eddy simulation model with bin microphysics for comparison with aircraft in situ observations. A high-bin-resolution variant of the microphysics is implemented for closer comparison with cloud drop size distribution (DSD) observations and a turbulent collision–coalescence kernel to evaluate the role of turbulence on drizzle formation. Simulations agree well with observational constraints, reproducing observed thermodynamic profiles (i.e., liquid water potential temperature and total moisture mixing ratio) as well as liquid water path. Cloud drop number concentration and liquid water content profiles also agree well insofar as the thermodynamic profiles match observations, but there are significant differences in DSD shape among simulations that cause discrepancies in higher-order moments such as sedimentation flux, especially as a function of bin resolution. Counterintuitively, high-bin-resolution simulations produce broader DSDs than standard resolution for both cases. Examination of several metrics of DSD width and percentile drop sizes shows that various discrepancies of model output with respect to the observations can be attributed to specific microphysical processes: condensation spuriously creates DSDs that are too wide as measured by standard deviation, which leads to collisional production of too many large drops. The turbulent kernel has the greatest impact on the low-bin-resolution simulation of the drizzling case, which exhibits greater surface precipitation accumulation and broader DSDs than the control (quiescent kernel) simulations. Turbulence effects on precipitation formation cannot be definitively evaluated using bin microphysics until the artificial condensation broadening issue has been addressed.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 2
    Publication Date: 2019-07-12
    Description: Microphysics parameterizations in large-scale models often account for subgrid variability in the calculation of process rates by integrating over assumed subgrid distributions of the input variables. The variances and covariances that define distribution width may be specified or diagnosed. The correlation ρ of cloud and rain mass mixing ratio/liquid water content (LWC) is a key input for accurate prediction of the accretion rate and a constant value is typically assumed. In this study, high-frequency aircraft measurements with a spatial resolution of ≈22 cm are used to evaluate the scaling behavior of cloud and rain LWC (qc and qr, respectively) and to demonstrate how and why covariability varies with length scale ℓ. It is shown that power spectral densities of both qc and qr exhibit scale invariance across a wide range of scales (2.04–142 m for qc; 33–1.45 × 104 m for qr). Because the cloud–rain cospectrum is also scale invariant, ρ is therefore expected to vary with ℓ. Direct calculation of ρ shows that it generally increases with ℓ, but there is significant variability in the ρ–ℓ relationship that primarily depends on cloud drop number concentration N and cloud cellular organization, suggesting that ρ may also vary with cloud regime. A parameterization of ρ as a function of ℓ and N is developed from aircraft observations and implications for diagnosis of ρ from limited-area model output are also discussed.
    Print ISSN: 0022-4928
    Electronic ISSN: 1520-0469
    Topics: Geography , Geosciences , Physics
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