Search Results

You are looking at 1 - 10 of 11 items for :

  • Author or Editor: H. Morrison x
  • Journal of the Atmospheric Sciences x
  • Refine by Access: All Content x
Clear All Modify Search
H. Morrison
and
J. O. Pinto

Abstract

A new two-moment bulk microphysics scheme is implemented into the polar version of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to simulate arctic mixed-phase boundary layer stratiform clouds observed during Surface Heat Budget of the Arctic (SHEBA) First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Arctic Cloud Experiment (ACE). The microphysics scheme predicts the number concentrations and mixing ratios of four hydrometeor species (cloud droplets, small ice, rain, snow) and includes detailed treatments of droplet activation and ice nucleation from a prescribed distribution of aerosol obtained from observations. The model is able to reproduce many features of the observed mixed-phase cloud, including a near-adiabatic liquid water content profile located near the top of a well-mixed boundary layer, droplet number concentrations of about 200–250 cm−3 that were distributed fairly uniformly through the depth of the cloud, and continuous light snow falling from the cloud base to the surface. The impacts of droplet and ice nucleation, radiative transfer, turbulence, large-scale dynamics, and vertical resolution on the simulated mixed-phase stratiform cloud are examined. The cloud layer is largely self-maintained through strong cloud-top radiative cooling that exceeds 40 K day−1. It persists through extended periods of downward large-scale motion that tend to thin the layer and reduce water contents. Droplet activation rates are highest near cloud base, associated with subgrid vertical motion that is diagnosed from the predicted turbulence kinetic energy. A sensitivity test neglecting subgrid vertical velocity produces only weak activation and small droplet number concentrations (<90 cm−3). These results highlight the importance of parameterizing the impact of subgrid vertical velocity to generate local supersaturation for aerosol-droplet closure. The primary ice nucleation mode in the simulated mixed-phase cloud is contact freezing of droplets. Sensitivity tests indicate that the assumed number and size of contact nuclei can have a large impact on the evolution and characteristics of mixed-phase cloud, especially the partitioning of condensate between droplets and ice.

Full access
J. A. Milbrandt
and
H. Morrison

Abstract

The predicted particle properties (P3) scheme introduced in Part I of this series represents all ice hydrometeors using a single “free” category, in which the bulk properties evolve smoothly through changes in the prognostic variables, allowing for the representation of any type of ice particle. In this study, P3 has been expanded to include multiple free ice-phase categories allowing particle populations with different sets of bulk properties to coexist, thereby reducing the detrimental effects of property dilution. The modified version of P3 is the first scheme to parameterize ice-phase microphysics using multiple free categories.

The multicategory P3 scheme is described and its overall behavior is illustrated. It is shown using an idealized 1D kinematic model that the overall simulation of total ice mass, reflectivity, and surface precipitation converges with additional categories. The correct treatment of the rime splintering process, which promotes multiple ice modes, is shown to require at least two categories in order to be included without introducing problems associated with property dilution. Squall-line simulations using a 3D dynamical model with one, two, and three ice categories produce reasonable reflectivity structures and precipitation rates compared to radar observations. In the multicategory simulations, ice hydrometeors from different categories and with different bulk properties are shown to coexist at the same points, with effects on reflectivity structure and precipitation. The new scheme thus appears to work reasonably in a full 3D model and is ready to be tested more widely for research and operational applications.

Full access
Evan A. Kalina
,
Katja Friedrich
,
Hugh Morrison
, and
George H. Bryan

Abstract

Idealized supercell thunderstorms are simulated with the Weather Research and Forecasting (WRF) Model at 15 cloud condensation nuclei (CCN) concentrations (100–10 000 cm−3) using four environmental soundings with different low-level relative humidity (RH) and vertical wind shear values. The Morrison microphysics scheme is used with explicit prediction of cloud droplet number concentration and a variable shape parameter for the raindrop size distribution (results from simulations with a fixed shape parameter are also presented). Changes in the microphysical process rates with CCN concentration are negligible beyond CCN ≈ 3000 cm−3. Changes in cold pool characteristics with CCN concentration are nonmonotonic and highly dependent on the environmental conditions. In moist conditions with moderate vertical wind shear, the cold pool area is nearly constant with respect to CCN concentration, while the area is reduced by 84% and 22% in the soundings with dry RH and large vertical wind shear, respectively. With the exception of the dry RH sounding, domain-averaged precipitation peaks between 500 and 5000 cm−3, after which it remains constant or slowly decreases. For the dry RH sounding, the domain-averaged precipitation monotonically decreases with CCN concentration. Accumulated precipitation is enhanced (by up to 25 mm) in the most polluted cases near the updrafts, except for the dry RH sounding. The different responses for moist and dry soundings are mostly due to increased (decreased) low-level latent cooling from melting hail (evaporating rain) with increasing CCN concentration in the moist soundings. This compensating effect does not exist when the low-level RH is dry.

Full access
H. Morrison
,
J. A. Curry
, and
V. I. Khvorostyanov

Abstract

A new double-moment bulk microphysics scheme predicting the number concentrations and mixing ratios of four hydrometeor species (droplets, cloud ice, rain, snow) is described. New physically based parameterizations are developed for simulating homogeneous and heterogeneous ice nucleation, droplet activation, and the spectral index (width) of the droplet size spectra. Two versions of the scheme are described: one for application in high-resolution cloud models and the other for simulating grid-scale cloudiness in larger-scale models. The versions differ in their treatment of the supersaturation field and droplet nucleation. For the high-resolution approach, droplet nucleation is calculated from Kohler theory applied to a distribution of aerosol that activates at a given supersaturation. The resolved supersaturation field and condensation/deposition rates are predicted using a semianalytic approximation to the three-phase (vapor, ice, liquid) supersaturation equation. For the large-scale version of the scheme, it is assumed that the supersaturation field is not resolved and thus droplet activation is parameterized as a function of the vertical velocity and diabatic cooling rate. The vertical velocity includes a subgrid component that is parameterized in terms of the eddy diffusivity and mixing length. Droplet condensation is calculated using a quasi-steady, saturation adjustment approach. Evaporation/deposition onto the other water species is given by nonsteady vapor diffusion allowing excess vapor density relative to ice saturation.

Full access
H. Morrison
,
J. A. Curry
,
M. D. Shupe
, and
P. Zuidema

Abstract

The new double-moment microphysics scheme described in Part I of this paper is implemented into a single-column model to simulate clouds and radiation observed during the period 1 April–15 May 1998 of the Surface Heat Budget of the Arctic (SHEBA) and First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment–Arctic Clouds Experiment (FIRE–ACE) field projects. Mean predicted cloud boundaries and total cloud fraction compare reasonably well with observations. Cloud phase partitioning, which is crucial in determining the surface radiative fluxes, is fairly similar to ground-based retrievals. However, the fraction of time that liquid is present in the column is somewhat underpredicted, leading to small biases in the downwelling shortwave and longwave radiative fluxes at the surface. Results using the new scheme are compared to parallel simulations using other microphysics parameterizations of varying complexity. The predicted liquid water path and cloud phase is significantly improved using the new scheme relative to a single-moment parameterization predicting only the mixing ratio of the water species. Results indicate that a realistic treatment of cloud ice number concentration (prognosing rather than diagnosing) is needed to simulate arctic clouds. Sensitivity tests are also performed by varying the aerosol size, solubility, and number concentration to explore potential cloud–aerosol–radiation interactions in arctic stratus.

Full access
Minghui Diao
,
George H. Bryan
,
Hugh Morrison
, and
Jorgen B. Jensen

Abstract

Output from idealized simulations of a squall line are compared with in situ aircraft-based observations from the Deep Convective Clouds and Chemistry campaign. Relative humidity distributions around convection are compared between 1-Hz aircraft observations (≈250-m horizontal scale) and simulations using a double-moment bulk microphysics scheme at three horizontal grid spacings: Δx = 0.25, 1, and 4 km. The comparisons focus on the horizontal extent of ice supersaturated regions (ISSRs), the maximum and average relative humidity with respect to ice (RHi) in ISSRs, and the ice microphysical properties during cirrus cloud evolution, with simulations at 0.25 and 1 km providing better results than the 4-km simulation. Within the ISSRs, all the simulations represent the dominant contributions of water vapor horizontal heterogeneities to ISSR formation on average, but with larger variabilities in such contributions than the observations. The best results are produced by a Δx = 0.25-km simulation with the RHi threshold for initiating ice nucleation increased to 130%, which improves almost all the ISSR characteristics and allows for larger magnitude and frequency of ice supersaturation (ISS) > 8%. This simulation also allows more occurrences of clear-sky ISSRs and a higher spatial fraction of ISS for in-cloud conditions, which are consistent with the observations. These improvements are not reproduced by modifying other ice microphysical processes, such as a factor-of-2 reduction in the ice nuclei concentration; a factor-of-10 reduction in the vapor deposition rate; turning off heterogeneous contact and immersion freezing; or turning off homogeneous freezing of liquid water.

Full access
Hugh Morrison
,
Jason A. Milbrandt
,
George H. Bryan
,
Kyoko Ikeda
,
Sarah A. Tessendorf
, and
Gregory Thompson

Abstract

A new microphysics scheme has been developed based on the prediction of bulk particle properties for a single ice-phase category, in contrast to the traditional approach of separating ice into various predefined species (e.g., cloud ice, snow, and graupel). In this paper, the new predicted particle properties (P3) scheme, described in Part I of this series, is tested in three-dimensional simulations using the Weather Research and Forecasting (WRF) Model for two contrasting well-observed cases: a midlatitude squall line and winter orographic precipitation. Results are also compared with simulations using other schemes in WRF. Simulations with P3 can produce a wide variety of particle characteristics despite having only one free ice-phase category. For the squall line, it produces dense, fast-falling, hail-like ice near convective updraft cores and lower-density, slower-falling ice elsewhere. Sensitivity tests show that this is critical for simulating high precipitation rates observed along the leading edge of the storm. In contrast, schemes that represent rimed ice as graupel, with lower fall speeds than hail, produce lower peak precipitation rates and wider, less distinct, and less realistic regions of high convective reflectivity. For the orographic precipitation case, P3 produces areas of relatively fast-falling ice with characteristics of rimed snow and low- to medium-density graupel on the windward slope. This leads to less precipitation on leeward slopes and more on windward slopes compared to the other schemes that produce large amounts of snow relative to graupel (with generally the opposite for schemes with significant graupel relative to snow). Overall, the new scheme produces reasonable results for a reduced computational cost.

Full access
Hugh Morrison
,
Mikael Witte
,
George H. Bryan
,
Jerry Y. Harrington
, and
Zachary J. Lebo

Abstract

This study investigates droplet size distribution (DSD) characteristics from condensational growth and transport in Eulerian dynamical models with bin microphysics. A hierarchy of modeling frameworks is utilized, including parcel, one-dimensional (1D), and three-dimensional large-eddy simulation (LES). The bin DSDs from the 1D model, which includes only vertical advection and condensational growth, are nearly as broad as those from the LES and in line with observed DSD widths for stratocumulus clouds. These DSDs are much broader than those from Lagrangian microphysical calculations within a parcel framework that serve as a numerical benchmark for the 1D tests. In contrast, the bin-modeled DSDs are similar to the Lagrangian microphysical benchmark for a rising parcel in which Eulerian transport is not considered. These results indicate that numerical diffusion associated with vertical advection is a key contributor to broadening DSDs in the 1D model and LES. This DSD broadening from vertical numerical diffusion is unphysical, in contrast to the physical mixing processes that previous studies have indicated broaden DSDs in real clouds. It is proposed that artificial DSD broadening from vertical numerical diffusion compensates for underrepresented horizontal variability and mixing of different droplet populations in typical LES configurations with bin microphysics, or the neglect of other mechanisms that broaden DSDs such as growth of giant cloud condensation nuclei. These results call into question the ability of Eulerian dynamical models with bin microphysics to investigate the physical mechanisms for DSD broadening, even though they may reasonably simulate overall DSD characteristics.

Full access
Kamal Kant Chandrakar
,
Hugh Morrison
,
Wojciech W. Grabowski
, and
George H. Bryan

Abstract

Advanced microphysics schemes (such as Eulerian bin and Lagrangian superdroplet) are becoming standard tools for cloud physics research and parameterization development. This study compares a double-moment bin scheme and a Lagrangian superdroplet scheme via large-eddy simulations of nonprecipitating and precipitating cumulus congestus clouds. Cloud water mixing ratio in the bin simulations is reduced compared to the Lagrangian simulations in the upper part of the cloud, likely from numerical diffusion, which is absent in the Lagrangian approach. Greater diffusion in the bin simulations is compensated by more secondary droplet activation (activation above cloud base), leading to similar or somewhat higher droplet number concentrations and smaller mean droplet radius than the Lagrangian simulations for the nonprecipitating case. The bin scheme also produces a significantly larger standard deviation of droplet radius than the superdroplet method, likely due to diffusion associated with the vertical advection of bin variables. However, the spectral width in the bin simulations is insensitive to the grid spacing between 50 and 100 m, suggesting other mechanisms may be compensating for diffusion as the grid spacing is modified. For the precipitating case, larger spectral width in the bin simulations initiates rain earlier and enhances rain development in a positive feedback loop. However, with time, rain formation in the superdroplet simulations catches up to the bin simulations. Offline calculations using the same drop size distributions in both schemes show that the different numerical methods for treating collision–coalescence also contribute to differences in rain formation. The stochastic collision–coalescence in the superdroplet method introduces more variability in drop growth for a given rain mixing ratio.

Full access
Kamal Kant Chandrakar
,
Wojciech W. Grabowski
,
Hugh Morrison
, and
George H. Bryan

Abstract

Entrainment mixing and turbulent fluctuations critically impact cloud droplet size distributions (DSDs) in cumulus clouds. This problem is investigated via a new sophisticated modeling framework using the Cloud Model 1 (CM1) LES model and a Lagrangian cloud microphysics scheme—the “superdroplet method” (SDM)—coupled with subgrid-scale (SGS) schemes for particle transport and supersaturation fluctuations. This modeling framework is used to simulate a cumulus congestus cloud. Average DSDs in different cloud regions show broadening from entrainment and secondary cloud droplet activation (activation above the cloud base). DSD width increases with increasing entrainment-induced dilution as expected from past work, except in the most diluted cloud regions. The new modeling framework with SGS transport and supersaturation fluctuations allows a more sophisticated treatment of secondary activation compared to previous studies. In these simulations, it contributes about 25% of the cloud droplet population and impacts DSDs in two contrasting ways: narrowing in extremely diluted regions and broadening in relatively less diluted. SGS supersaturation fluctuations contribute significantly to an increase in DSD width via condensation growth and evaporation. Mixing of superdroplets from SGS velocity fluctuations also broadens DSDs. The relative dispersion (ratio of DSD dispersion and mean radius) negatively correlates with gridscale vertical velocity in updrafts but is positively correlated in downdrafts. The latter is from droplet activation driven by positive SGS supersaturation fluctuations in grid-mean subsaturated conditions. Finally, the sensitivity to model grid length is evaluated. The SGS schemes have greater influence as the grid length is increased, and they partially compensate for the reduced model resolution.

Full access