Jerry Y. Harrington

Parameterization of Ice Crystal Conversion Processes Due to Vapor Deposition for Mesoscale Models Using Double-Moment Basis Functions. Part I: Basic Formulation and Parcel Model Results

Abstract Observational data collected during the FIRE II experiment showing the existence of bimodal ice spectra along with experimental evidence of the size dependence of riming are utilized in the development of a bimodal ice spectrum parameterization for use in the RAMS model. Two ice classes are defined: pristine ice and snow, each described by a separate, complete gamma distribution function. Pristine ice is small ice consisting of particles with mean sizes less than 125 µm, while snow is the large class consisting of particles greater than 125 µm. Analytical equations are formulated for the conversion between the ice classes by vapor depositional growth (sublimation). During ice subsaturated conditions, a number concentration sink is parameterized for all ice species. The performance of the parameterizations in a simple parcel model is discussed and evaluated against an explicit Lagrangian parcel microphysical model.

Intercomparison of cloud model simulations of Arctic mixed‐phase boundary layer clouds observed during SHEBA/FIRE‐ACE

An intercomparison of six cloud-resolving and large-eddy simulation models is presented. This case study is based on observations of a persistent mixed-phase boundary layer cloud gathered on 7 May, 1998 from the Surface Heat Budget of Arctic Ocean (SHEBA) and First ISCCP Regional Experiment - Arctic Cloud Experiment (FIRE-ACE). Ice nucleation is constrained in the simulations in a way that holds the ice crystal concentration approximately fixed, with two sets of sensitivity runs in addition to the baseline simulations utilizing different specified ice nucleus (IN) concentrations. All of the baseline and sensitivity simulations group into two distinct quasi-steady states associated with either persistent mixed-phase clouds or all-ice clouds after the first few hours of integration, implying the existence of multiple states for this case. These two states are associated with distinctly different microphysical, thermodynamic, and radiative characteristics. Most but not all of the models produce a persistent mixed-phase cloud qualitatively similar to observations using the baseline IN/crystal concentration, while small increases in the IN/crystal concentration generally lead to rapid glaciation and conversion to the all-ice state. Budget analysis indicates that larger ice deposition rates associated with increased IN/crystal concentrations have a limited direct impact on dissipation of liquid in these simulations. However, the impact of increased ice deposition is greatly enhanced by several interaction pathways that lead to an increased surface precipitation flux, weaker cloud top radiative cooling and cloud dynamics, and reduced vertical mixing, promoting rapid glaciation of the mixed-phase cloud for deposition rates in the cloud layer greater than about 122610 –5 gk g –1 s –1 for this case. These results indicate the critical importance of precipitation-radiative-dynamical interactions in simulating cloud phase, which have been neglected in previous fixed-dynamical parcel studies of the cloud phase parameter space. Large sensitivity to the IN/crystal concentration also suggests the need for improved understanding of ice nucleation and its parameterization in models.

Radiative Impacts on the Growth of a Population of Drops within Simulated Summertime Arctic Stratus

The impact of solar heating and infrared cooling on the growth of a population of drops is studied with two numerical modeling frameworks. An eddy-resolving model (ERM) simulation of Arctic stratus clouds is used to generate a dataset of 500 parcel trajectories that follow the mean dynamic motions of the simulated cloud. The 500-parcel dataset is used to drive a trajectory ensemble model (TEM) coupled to an explicit microphysical model that includes the radiative term in the vapor growth equation. The second framework is that of the ERM itself. Results from the TEM show that the production of drizzle-sized drops is strongly dependent upon parcel cloud-top residence time for both radiative- and nonradiative-influenced growth. Drizzle-sized drops can be produced between 20 and 50 min earlier through the inclusion of the radiative term, which corroborates earlier results. The radiative effect may also cause drops with r , 10 mm to evaporate, producing a bimodal size spectrum. Parcel cloud-top residence times as short as 12 min can initiate this bimodal spectrum. TEM results show that the radiative effect increases drizzle drop mass predominately in parcels that tend to contribute to drizzle even in the absence of the radiative term. Activation of large cloud condensation nuclei appears to have a larger effect on drizzle production than does the radiative term. ERM simulations show a weak overall influence of the radiative term. Drizzle onset occurs earlier when the radiative term is included (about 20 min), but there is no strong change in the overall structure or evolution of the cloud.

Intercomparison of large‐eddy simulations of Arctic mixed‐phase clouds: Importance of ice size distribution assumptions

Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP), in agreement with earlier studies. In contrast to previous intercomparison studies, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSDs) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case. Sensitivity tests indicate LWP and IWP are much closer to the bin model simulations when a modified shape factor which is similar to that predicted by bin model simulation is used in bulk scheme. These results demonstrate the importance of representation of ice PSD in determining the partitioning of liquid and ice and the longevity of mixed-phase clouds.

Ice aspect ratio influences on mixed‐phase clouds: Impacts on phase partitioning in parcel models

[1]xa0The influences of evolving ice habit on the maintenance and glaciation of stratiform mixed-phase clouds are examined theoretically. Unlike most current modeling methods where a single axis length is predicted, the primary habits, or two axis lengths, are computed explicitly. The method produces a positive non-linear feedback between mass growth and crystal aspect ratio evolution. Furthermore, ice particle growth has a distinct initial-size dependence with smaller initial ice particles evolving into more extreme crystal shapes with greater overall mass. This feedback cannot be captured with simpler growth methods, leading to underestimates of ice growth and mixed-phase glaciation. Aspect ratio prediction is most critical for mixed-phase maintenance at temperatures where pronounced habits exist (dendritic growth, T = −15°C and needle growth, −6°C) and at ice concentrations between 1 L−1 and 100 L−1. At these temperatures and concentrations, rates of glaciation can be under-predicted by as much as an order of magnitude by equivalent density spheres. Habit prediction is less important for the maintenance of liquid at lower ice concentrations ( 100 L−1) the time-scale for liquid depletion is shorter (minutes), thus predicting crystal habit has only a small impact on liquid lifetime. Updraft strength also affects mixed-phase cloud maintenance primarily at ice concentrations between 1 L−1 and 100 L−1. It is theoretically possible for vertical oscillating motions to maintain stratiform mixed-phase clouds indefinitely when temperatures are relatively high (> −10°C) and ice concentrations are relatively low (<0.1 L−1).

A Method for Adaptive Habit Prediction in Bulk Microphysical Models. Part I: Theoretical Development

AbstractBulk microphysical schemes use the capacitance model for ice vapor growth in combination with mass–size relationships to determine the evolution of ice water content (IWC) and ice particle maximum dimension in time. These approaches are limited since a single axis length is used, the aspect ratio is usually held constant and mass–size relations have many available coefficients for similar ice types. Fixing the crystal aspect ratio severs the nonlinear link between aspect ratio changes and increased growth rates that occur during crystal growth. A method is presented here for predicting two crystal axes and the crystal aspect ratio in bulk models. Evolution of the ice mass mixing ratio is tied to the evolution of two axis length mixing ratios through the use of a historical axis ratio parameter containing memory of crystal shape. This parameter links the distributions of the two axes, allowing characterization of particle lengths using a single distribution. The method uses four prognostic variable...

A method for adaptive habit prediction in bulk microphysical models. Part II: Parcel model corroboration

AbstractIt is common for cloud microphysical models to use a single axis length to characterize ice crystals. These methods use either the diameter of an equivalent sphere or mass–size equations in conjunction with the capacitance model to close the equations for ice vapor diffusion. Single-axis methods unnaturally constrain growth because real crystals evolve along at least two axis directions. Thus, they are unable to reproduce the simultaneous variation in mass mixing ratio, maximum dimension, and mass-weighted fall speeds. While mass–size relations can at times capture the evolution of one of these with relatively low errors, the other properties are generally under- or overpredicted by 20%–40%. Part I of this study describes an adaptive habit method that evolves two axis dimensions, allowing feedbacks between aspect ratio changes and mass mixing-ratio evolution. The adaptive habit method evolves particle habit by prognosing number and mass mixing ratios along with two axis length mixing ratios. Compa...

The impact of microphysical parameters, ice nucleation mode, and habit growth on the ice/liquid partitioning in mixed‐phase Arctic clouds

[1]xa0The fundamental physical processes that maintain supercooled liquid in observed Arctic mixed-phase clouds are poorly constrained. To isolate the factors that control ice/liquid partitioning during the ascent of an air parcel, we apply an adiabatic parcel model that includes ice nucleation by deposition and immersion freezing and ice habit evolution. Simulations are performed for two different temperature regimes that resemble those observed during the Mixed-Phase Arctic Cloud Experiment (−13°C < T < −9°C) and the Surface Heat Budget of the Arctic Ocean (−22°C < T < −17°C). Effects on ice and liquid water evolution in an updraft are explored as a function of ice nucleus (IN) concentration and nucleation mode, updraft velocity, properties of cloud condensation nuclei, and assumption about ice particle shape (habit). For most conditions, ice and liquid coexist and increase simultaneously, and only at high IN concentrations or low updraft velocities do ice particles grow at the expense of droplets. The impact of the ice nucleation mode on ice/liquid distribution depends on the temperature and supersaturation regime. The assumption of spherical ice particles instead of nonspherical habits leads to an underestimate of ice growth. It is concluded that updraft velocity, IN concentrations, and particle shape can impact ice/liquid distribution to similar extents.

Modeling Ice Crystal Aspect Ratio Evolution during Riming: A Single-Particle Growth Model

AbstractThis paper describes and tests a single-particle ice growth model that evolves both ice crystal mass and shape as a result of vapor growth and riming. Columnar collision efficiencies in the model are calculated using a new theoretical method derived from spherical collision efficiencies. The model is able to evolve mass, shape, and fall speed of growing ice across a range of temperatures, and it compares well with wind tunnel data. The onset time of riming and the effects of riming on mass and fall speed between −3° and −16°C are modeled, as compared with wind tunnel data for a liquid water content of 0.4 g m−3. Under these conditions, riming is constrained to the more isometric habits near −10° and −4°C. It is shown that the mass and fall speed of riming dendrites depend on the liquid drop distribution properties, leading to a range of mass–size and fall speed–size relationships. Riming at low liquid water contents is shown to be sensitive to ice crystal habit and liquid drop size. Moreover, very...

Dynamical and Microphysical Evolution during Mixed-Phase Cloud Glaciation Simulated Using the Bulk Adaptive Habit Prediction Model

AbstractA bulk microphysics scheme predicting ice particle habit evolution has been implemented in the Weather Research and Forecasting Model. Large-eddy simulations are analyzed to study the effects of ice habit and number concentration on the bulk ice and liquid masses, dynamics, and lifetime of Arctic mixed-phase boundary layer clouds. The microphysical and dynamical evolution simulated using the adaptive habit scheme is compared with that assuming spherical particles with a density of bulk ice or a reduced density and with mass–dimensional parameterizations. It is found that the adaptive habit method returns an increased (decreased) ice (liquid) mass as compared to spheres and provides a more accurate simulation as compared to dendrite mass–size relations.Using the adaptive habit method, simulations are then completed to understand the microphysical and dynamical interactions within a single-layer mixed-phase stratocumulus cloud observed during flight 31 of the Indirect and Semi-Direct Aerosol Campaig...