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David B. Mechem and Yefim L. Kogan

Abstract

A case of coastal California summer season boundary layer cloud has been simulated with the U.S. Navy Coupled Ocean–Atmosphere Mesoscale Prediction System and the results analyzed in the context of consistency with conclusions derived from large eddy simulation–based (LES) studies. Results show a pronounced diurnal cycle and fair agreement with satellite-derived observations of liquid water path. When drizzle processes are included, a significant degree of mesoscale organization emerges in the form of cloud bands, accompanied by a transition from a well-mixed boundary layer topped by unbroken stratocumulus cloud into a more potentially unstable, convective boundary layer regime. The transition and the subsequent development of mesoscale variability is analogous to the drizzle-induced cloud breakup produced in large eddy simulation studies. The dynamics of the pure stratocumulus cloud are dictated by the model's subgrid parameterization, while the more convective regime exhibits appreciable vertical velocities characteristic of an ensemble of cumulus updrafts. The existence of convective updrafts is tied to a weak drizzle-induced decoupling of the cloud and subcloud layer, after which air of higher equivalent potential temperature (θ e) can pool at the surface. Some similarities to the propagation of deep convection are also noted.

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Yefim L. Kogan and David B. Mechem

Abstract

Unbiased calculations of microphysical process rates such as autoconversion and accretion in mesoscale numerical weather prediction models require that subgrid-scale (SGS) variability over the model grid volume be taken into account. This variability can be expressed as probability distribution functions (PDFs) of microphysical variables. Using dynamically balanced large-eddy simulation (LES) model results from a case of marine trade cumulus, the authors develop PDFs of the cloud water, droplet concentration, and rainwater variables (q c, N c, and q r). Both 1D and 2D joint PDFs (JPDFs) are presented. The authors demonstrate that accounting for the JPDFs results in more accurate process rates for a regional-model grid size. Bias in autoconversion and accretion rates are presented, assuming different formulations of the JPDFs. Approximating the 2D PDF using a product of individual 1D PDFs overestimates the autoconversion rates by an order of magnitude, whereas neglecting the SGS variability altogether results in a drastic underestimate of the grid-mean autoconversion rate. PDF assumptions have a much smaller impact on accretion, largely because of the near-linear dependence of the variables in the accretion rate formula and the relatively weak correlation between q c and q r over the small LES grid volumes. The latter is attributed to the spatial decorrelation in the vertical between the two fields. Although the full PDFs are both height and time dependent, results suggest that fixed-in-time and fixed-in-height PDFs give an acceptable level of accuracy, especially for the crucial autoconversion calculation.

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Yefim L. Kogan and David B. Mechem

Abstract

Calculating unbiased microphysical process rates over mesoscale model grid volumes necessitates knowledge of the subgrid-scale (SGS) distribution of variables, typically represented as probability distribution functions (PDFs) of the prognostic variables. In the 2014 Journal of the Atmospheric Sciences paper by Kogan and Mechem, they employed large-eddy simulation of Rain in Cumulus over the Ocean (RICO) trade cumulus to develop PDFs and joint PDFs of cloud water, rainwater, and droplet concentration. In this paper, the approach of Kogan and Mechem is extended to deeper, precipitating cumulus congestus clouds as represented by a simulation based on conditions from the TOGA COARE field campaign. The fidelity of various PDF approximations was assessed by evaluating errors in estimating autoconversion and accretion rates. The dependence of the PDF shape on grid-mean variables is much stronger in congestus clouds than in shallow cumulus. The PDFs obtained from the TOGA COARE simulations for the calculation of accretion rates may be applied to both shallow and congestus cumulus clouds. However, applying the TOGA COARE PDFs to calculate autoconversion rates introduces unacceptably large errors in shallow cumulus clouds, thus precluding the use of a “universal” PDF formulation for both cloud types.

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David B. Mechem and Yefim L. Kogan

Abstract

A parameterization for giant cloud condensation nuclei (GCCN), suitable for use in bulk microphysical models, has been developed that uses precise representations of the condensational growth of aerosol particles in the subcloud layer. The formulation employs an observationally based GCCN distribution function and directly observable parameters of GCCN, such as concentration and the shape of the aerosol spectra. The parameterization couples naturally to parameterizations of sea salt flux from the ocean surface. The behavior of the GCCN parameterization in a large eddy simulation (LES) framework is consistent with simulations employing explicit, size-resolving microphysical methods. The parameterization properly represents the sensitivity of cloud, drizzle, turbulence, and radiative properties to changes in GCCN concentration for polluted and clean background CCN environments.

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David B. Mechem, Yefim L. Kogan, and David M. Schultz

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More studies on the dynamics of marine stratus and stratocumulus clouds have been performed than comparable studies on continental stratocumulus. Therefore, to increase the number of observations of continental stratocumulus and to compare marine and continental stratocumulus to each other, the approach of large-eddy observation (LEO) was applied to a case of nocturnal continental stratocumulus observed over the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) in the central United States on 8 April 2006. The stratocumulus occurred in cold-air and dry-air advection behind a surface cold front. LEOs were obtained from millimeter-wavelength cloud radar and micropulse lidar, whereas traditional meteorological observations described the synoptic environment. This study focuses on a 9-h period of a predominantly nonprecipitating stratocumulus layer 250–400 m thick. A slight thinning of the cloud layer over time is consistent with dry-air advection. A deep layer of descent overlaid a shallower layer of ascent from the surface up to 800 mb, providing a mechanism for strengthening the inversion at cloud top. Time series of Doppler velocity indicate vertically coherent structures identifiable throughout much of the cloud layer. The magnitude of turbulence, as indicated by the variance of the vertical velocity, was weak relative to typical marine stratocumulus and to the one other case of continental stratocumulus in the literature. Conditional sampling of the eddy structures indicate that strong downdrafts were more prevalent than strong updrafts, and negative skewness of vertical velocity in the cloud implies an in-cloud circulation driven by longwave cooling at cloud top, similar to that in marine stratocumulus.

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David B. Mechem, Yefim L. Kogan, and David M. Schultz

Abstract

Previous large-eddy simulations (LES) of stratocumulus-topped boundary layers have been exclusively set in marine environments. Boundary layer stratocumulus clouds are also prevalent over the continent but have not been simulated previously. A suite of LES runs was performed for a case of continental post-cold-frontal stratocumulus observed by the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF), located in northern Oklahoma. Comparison with fixed, ground-based sensors necessitated an Eulerian approach in which it was necessary to supply to the model estimates of synoptic-scale advection and vertical motion, particularly given the quickly evolving, baroclinic nature of the synoptic environment. Initial analyses from the Rapid Update Cycle model supplied estimates for these forcing terms.

Turbulent statistics calculated from the LES results are consistent with large-eddy observations obtained from millimeter-wave cloud radar. The magnitude of turbulence is weaker than in typical marine stratocumulus, a result attributed to highly decoupled cloud and subcloud circulations associated with a deep layer of negative buoyancy flux arising from the entrainment of warm, free-tropospheric air. Model results are highly sensitive to variations in advection of temperature and moisture and much less sensitive to changes in synoptic-scale vertical velocity and surface fluxes. For this case, moisture and temperature advection, rather than entrainment, tend to be the governing factors in the analyzed cloud system maintenance and decay. Typical boundary layer entrainment scalings applied to this case do not perform very well, a result attributed to the highly decoupled nature of the circulation. Shear production is an important part of the turbulent kinetic energy budget. The dominance of advection provides an optimistic outlook for mesoscale, numerical weather prediction, and climate models because these classes of models represent these grid-scale processes better than they do subgrid-scale processes such as entrainment.

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David B. Mechem, Sandra E. Yuter, and Simon P. de Szoeke

Abstract

A near-large-eddy simulation approach with size-revolving (bin) microphysics is employed to evaluate the relative sensitivity of southeast Pacific marine boundary layer cloud properties to thermodynamic and aerosol parameters. Simulations are based on a heavily drizzling cloud system observed by the NOAA ship Ronald H. Brown during the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study—Regional Experiment (VOCALS-Rex) field campaign. A suite of numerical experiments examines the sensitivity of drizzle to variations in boundary layer depth and cloud condensation nuclei (CCN) concentration in a manner consistent with the variability of those parameters observed during VOCALS-Rex. All four simulations produce cellular structures and turbulence characteristics of a circulation driven predominantly in a bottom-up fashion. The cloud and subcloud layers are coupled by strong convective updrafts that provide moisture to the cloud layer. Distributions of reflectivity calculated from model droplet spectra agree well with reflectivity distributions from the 5-cm-wavelength scanning radar aboard the ship, and the statistical behavior of cells over the course of the simulation is similar to that documented in previous studies of southeast Pacific stratocumulus. The simulations suggest that increased aerosol concentration delays the onset of drizzle, whereas changes in the boundary layer height are more important in modulating drizzle intensity.

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Yefim L. Kogan, Zena N. Kogan, and David B. Mechem

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Cloud microphysical parameterizations and retrievals rely heavily on knowledge of the shape of drop size distributions (DSDs). Many investigations assume that DSDs in the entire or partial drop size range may be approximated by known analytical functions. The most frequently employed approximations of function are of the type of gamma, lognormal, Khrgian–Mazin, and Marshall–Palmer. At present, little is known about the accuracy of these approximations. The authors employ a DSD dataset generated by the Cooperative Institute for Mesoscale Meteorological Studies Large-Eddy Simulation (CIMMS LES) explicit microphysics model for stratocumulus cases observed during the Atlantic Stratocumulus Transition Experiment (ASTEX) field project. The fidelity of analytic lognormal- and gamma-type DSD functions is evaluated according to how well they represent the higher-order moments of the drop spectra, such as precipitation flux and radar reflectivity. It is concluded that for boundary layer marine drizzling stratocumuli, a DSD based on the two-mode gamma distribution provides a more accurate estimate of precipitation flux and radar reflectivity than the DSD based on the lognormal distribution. The gamma distribution also provides a more accurate radar reflectivity field in two- and three-moment bulk microphysical models compared to the conventional Z–R relationship.

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Yefim L. Kogan, Zena N. Kogan, and David B. Mechem

Abstract

The errors of formulations of cloud retrievals based on radar reflectivity, mean Doppler velocity, and Doppler spectrum width are evaluated under the controlled framework of the Observing System Simulation Experiments (OSSEs). Cloud radar parameters are obtained from drop size distributions generated by the high-resolution Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) large-eddy simulation (LES) model with explicit microphysics. It is shown that in drizzling stratocumulus the accuracy of cloud liquid water (Ql) retrieval can be substantially increased when information on Doppler velocity or Doppler spectrum width is included in addition to radar reflectivity. In the moderate drizzle case (drizzle rate R of about 1 mm day−1) the mean and standard deviation of errors is of the order of 10% for Ql values larger than 0.2 g m−3; in stratocumulus with heavy drizzle (R > 2 mm day−1) these values are approximately 20%–30%. Similarly, employing Doppler radar parameters significantly improves the accuracy of drizzle flux retrieval. The use of Doppler spectrum width σd instead of Doppler velocity yields about the same accuracy, thus demonstrating that both Doppler parameters have approximately the same potential for improving microphysical retrievals. It is noted that the error estimates herein represent the theoretical lower bound on retrieval errors, because the actual errors will inevitably increase, first and foremost, due to uncertainties in estimation contributions from air turbulence.

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Kevin J. Nelson, David B. Mechem, and Yefim L. Kogan

Abstract

Several warm-rain microphysical parameterizations are evaluated in a regional forecast model setting (using the Naval Research Laboratory’s Coupled Ocean–Atmosphere Mesoscale Prediction System) by evaluating how accurately the model is able to represent the marine boundary layer (MBL). Cloud properties from a large suite of simulations using different parameterizations and concentrations of cloud condensation nuclei (CCN) are compared to ship-based observations from the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study—Regional Experiment (VOCALS-REx) field campaign conducted over the southeastern Pacific (SEP). As in previous studies, the simulations systematically underestimate liquid water path and MBL cloud depth. On the other hand, the simulations overestimate precipitation rates relative to those derived from the scanning C-band radar on board the ship. Most of the simulations exhibit a diurnal cycle, although details differ somewhat from a recent observational study. In addition to direct comparisons with the observations, the internal microphysical consistency of simulated MBL cloud properties is assessed by comparing simulation output to a number of observationally and theoretically derived scalings for precipitation and coalescence scavenging. Simulation results are broadly consistent with these scalings, suggesting COAMPS is behaving in a microphysically consistent fashion. However, microphysical consistency as defined in the analysis is highly dependent upon the horizontal resolution of the model. Excessive depletion of CCN from large coalescence processing rates suggests the importance of parameterizing a source term for CCN or imposing some form of fixed, climatological background CCN concentration.

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