Two-moment Bulk Microphysics Scheme Research Articles

Influence of drop size distribution function on simulated ground precipitation for different cloud droplet number concentrations

A cloud-resolving mesoscale model with a two-moment bulk microphysical scheme is used to perform cloud simulations for two different modes of the liquid water spectrum: a unified Khrgian–Mazin size distribution for the entire spectrum of drops and the monodisperse size distribution for cloud droplets with the exponential Marshall–Palmer distribution for raindrops. The cloud model calculates the mixing ratios and number concentrations of the six microphysical categories: raindrops, cloud ice, snow, graupel, frozen raindrops and hail. The cloud droplet number concentration was prescribed. The main purpose of this sensitivity study was to analyse the differences in simulated surface precipitation (rain and hail) for the two assumed approaches with different values of cloud droplet number concentration. The study showed that there are significant differences in the occurrence, amount and spatial distribution of accumulated precipitation at the surface. It can be noted that the unified Khrgian–Mazin size distribution is generally more sensitive to changes in the cloud droplet number concentration than an alternative approach. The rain showers and cloud splitting are well simulated with the unified Khrgian–Mazin size distribution, especially for smaller values of cloud droplet number concentration.

A triple-moment hail bulk microphysics scheme. Part I: Description and initial evaluation

Hail processes in deep convection can have a substantial impact on precipitation characteristics as well as on dynamic and thermodynamic properties of convective downdrafts and cold pools, yet the realistic representation of hail in many cloud-resolving models employing bulk microphysical schemes is challenging. The limits imposed by fixing one or two of the distribution parameters in many one- and two-moment bulk microphysics schemes often lead to particularly poor representations of particles within the tails of size distribution spectra; an especially important consideration for hail, which covers a broad range of sizes in nature. In order to improve the representation of hail distributions in simulations of deep moist convection in cloud-resolving numerical models, a new triple-moment bulk hail microphysics scheme (3MHAIL) is presented and evaluated. The 3MHAIL scheme predicts the relative dispersion parameter for a gamma distribution function via prognostication of the sixth moment (related to the reflectivity factor) of the distribution in addition to the mass mixing ratio and number concentration (third and zeroeth moments, respectively) thereby allowing for a fully prognostic distribution function. Significant improvement in the representation of sedimentation, melting, and formation processes of hail are achieved with the 3MHAIL scheme compared to lower-order moment schemes.

Formulation and test of an ice aggregation scheme for two-moment bulk microphysics schemes

Abstract. A simple formulation of aggregation for two-moment bulk microphysical models is derived. The solution involves the evaluation of a double integral of the collection kernel weighted with the crystal size (or mass) distribution. This quantity is to be inserted into the differential equation for the crystal number concentration which has classical Smoluchowski form. The double integrals are evaluated numerically for log-normal size distributions over a large range of geometric mean masses. A polynomial fit of the results is given that yields good accuracy. Various tests of the new parameterisation are described: aggregation as stand-alone process, in a box-model, and in 2-D simulations of a cirrostratus cloud. These tests suggest that aggregation can become important for warm cirrus, leading even to higher and longer-lasting in-cloud supersaturation. Cold cirrus clouds are hardly affected by aggregation. The collection efficiency is taken from a parameterisation that assumes a dependence on temperature, a situation that might be improved when reliable measurements from cloud chambers suggests the necessary constraints for the choice of this parameter.

Numerical simulation of clouds and precipitation depending on different relationships between aerosol and cloud droplet spectral dispersion

ABSTRACTThe aerosol effects on clouds and precipitation in deep convective cloud systems are investigated using the Weather Research and Forecast (WRF) model with the Morrison two-moment bulk microphysics scheme. Considering positive or negative relationships between the cloud droplet number concentration (Nc) and spectral dispersion (ɛ), a suite of sensitivity experiments are performed using an initial sounding data of the deep convective cloud system on 31 March 2005 in Beijing under either a maritime (‘clean’) or continental (‘polluted’) background. Numerical experiments in this study indicate that the sign of the surface precipitation response induced by aerosols is dependent on the ɛ−Nc relationships, which can influence the autoconversion processes from cloud droplets to rain drops. When the spectral dispersion ɛ is an increasing function of Nc, the domain-average cumulative precipitation increases with aerosol concentrations from maritime to continental background. That may be because the existence of large-sized rain drops can increase precipitation at high aerosol concentration. However, the surface precipitation is reduced with increasing concentrations of aerosol particles when ɛ is a decreasing function of Nc. For the ɛ−Nc negative relationships, smaller spectral dispersion suppresses the autoconversion processes, reduces the rain water content and eventually decreases the surface precipitation under polluted conditions. Although differences in the surface precipitation between polluted and clean backgrounds are small for all the ɛ−Nc relationships, additional simulations show that our findings are robust to small perturbations in the initial thermal conditions.

Modeling the Phase Transition Associated with Melting Snow in a 1D Kinematic Framework: Sensitivity to the Microphysics

A simple 1D kinematic cloud model coupled to a two-moment bulk microphysics scheme is used to perform quasi-idealized simulations of snow, with a prescribed upper boundary snow field based on observed radar reflectivity and temperature, falling into a low-level melting layer. The model realistically simulates the formation of a nearly isothermal layer below the melting level, the surface precipitation rate, and the phase transition from liquid to solid, consistent with observations for this case. A series of test runs is performed to examine the sensitivity of modeling the timing and duration of the phase transition period to details of specific parameterization aspects related to snow in the microphysics scheme. The sensitivity tests include varying the number of prognostic moments, the mass–diameter relation, the fall velocity–diameter relation, the treatment of aggregation, and the lower limit for the slope of the size distribution. It is shown that the simulated transition period, for such a case with the initial melting level being close to the surface, can be quite sensitive to model parameters specified within realistic ranges and/or ranges within our physical understanding.

Sensitivity of Idealized Squall-Line Simulations to the Level of Complexity Used in Two-Moment Bulk Microphysics Schemes

AbstractThis paper investigates the level of complexity that is needed within bulk microphysics schemes to represent the essential features associated with deep convection. To do so, the sensitivity of surface precipitation is evaluated in two-dimensional idealized squall-line simulations with respect to the level of complexity in the bulk microphysics schemes of H. Morrison et al. and of J. A. Milbrandt and M. K. Yau. Factors examined include the number of predicted moments for each of the precipitating hydrometeors, the number and nature of ice categories, and the conversion term formulations. First, it is shown that simulations of surface precipitation and cold pools are not only a two-moment representation of rain, as suggested by previous research, but also by two-moment representations for all precipitating hydrometeors. Cold pools weakened when both rain and graupel number concentrations were predicted, because size sorting led to larger graupel particles that melted into larger raindrops and caused less evaporative cooling. Second, surface precipitation was found to be less sensitive to the nature of the rimed ice species (hail or graupel). Production of hail in experiments including both graupel and hail strongly depends on an unphysical threshold that converts small hail back to graupel, indicating the need for a more physical treatment of the graupel-to-hail conversion. Third, it was shown that the differences in precipitation extremes between the two-moment microphysics schemes are mainly related to the treatment of drop breakup. It was also shown that, although the H. Morrison et al. scheme is dominated by deposition growth and low precipitation efficiency, the J. A. Milbrandt and M. K. Yau scheme is dominated by riming processes and high precipitation efficiency.

Ensemble Kalman Filter Analyses of the 29–30 May 2004 Oklahoma Tornadic Thunderstorm Using One- and Two-Moment Bulk Microphysics Schemes, with Verification against Polarimetric Radar Data

AbstractThe performance of ensemble Kalman filter (EnKF) analysis is investigated for the tornadic supercell on 29–30 May 2004 in Oklahoma using a dual-moment (DM) bulk microphysics scheme in the Advanced Regional Prediction System (ARPS) model. The comparison of results using single-moment (SM) and DM microphysics schemes evaluates the benefits of using one over the other during storm analysis. Observations from a single operational Weather Surveillance Radar-1988 Doppler (WSR-88D) are assimilated and a polarimetric WSR-88D in Norman, Oklahoma (KOUN), is used to assess the quality of the analysis.Analyzed reflectivity and radial velocity in the SM and DM experiments compare favorably with independent radar observations in general. However, simulated polarimetric signatures obtained from analyses using a DM scheme agree significantly better with polarimetric signatures observed by KOUN in terms of the general structure, location, and intensity of the signatures than those generated from analyses using an SM scheme.These results demonstrate for the first time for a real supercell storm that EnKF data assimilation using a numerical model with an adequate microphysics scheme (i.e., a scheme that predicts at least two moments of the hydrometeor size distributions) is capable of producing polarimetric radar signatures similar to those seen in observations without directly assimilating polarimetric data. In such cases, the polarimetric data also serve as completely independent observations for the verification purposes.

Long-term impacts of aerosols on precipitation and lightning over the Pearl River Delta megacity area in China

Abstract. Seven-year measurements of precipitation, lightning flashes, and visibility from 2000 to 2006 have been analyzed in the Pearl River Delta (PRD) region, China, with a focus on the Guangzhou megacity area. Statistical analysis shows that the occurrence of heavy rainfall (>25 mm per day) and frequency of lightning strikes are reversely correlated to visibility during this period. To elucidate the effects of aerosols on cloud processes, precipitation, and lightning activity, a cloud resolving – Weather Research and Forecasting (CR-WRF) model with a two-moment bulk microphysical scheme is employed to simulate a mesoscale convective system occurring on 28 Match 2009 in the Guangzhou megacity area. The model predicted evolutions of composite radar reflectivity and accumulated precipitation are in agreement with measurements from S-band weather radars and automatic gauge stations. The calculated lightning potential index (LPI) exhibits temporal and spatial consistence with lightning flashes recorded by a local lightning detection network. Sensitivity experiments have been performed to reflect aerosol conditions representative of polluted and clean cases. The simulations suggest that precipitation and LPI are enhanced by about 16% and 50%, respectively, under the polluted aerosol condition. Our results suggest that elevated aerosol loading suppresses light and moderate precipitation (less than 25 mm per day), but enhances heavy precipitation. The responses of hydrometeors and latent heat release to different aerosol loadings reveal the physical mechanism for the precipitation and lightning enhancement in the Guangzhou megacity area, showing more efficient mixed phase processes and intensified convection under the polluted aerosol condition.

A two-moment bulk microphysics coupled with a mesoscale model WRF: Model description and first results

The Chinese Academy of Meteorological Sciences (CAMS) two-moment bulk microphysics scheme was adopted in this study to investigate the representation of cloud and precipitation processes under different environmental conditions. The scheme predicts the mixing ratio of water vapor as well as the mixing ratios and number concentrations of cloud droplets, rain, ice, snow, and graupel. A new parameterization approach to simulate heterogeneous droplet activation was developed in this scheme. Furthermore, the improved CAMS scheme was coupled with the Weather Research and Forecasting model (WRF v3.1), which made it possible to simulate the microphysics of clouds and precipitation as well as the cloud-aerosol interactions in selected atmospheric condition.

Comparison of Two-Moment Bulk Microphysics Schemes in Idealized Supercell Thunderstorm Simulations

Idealized three-dimensional supercell simulations were performed using the two-moment bulk microphysics schemes of Morrison and Milbrandt–Yau in the Weather Research and Forecasting (WRF) model. Despite general similarities in these schemes, the simulations were found to produce distinct differences in storm structure, precipitation, and cold pool strength. In particular, the Morrison scheme produced much higher surface precipitation rates and a stronger cold pool, especially in the early stages of storm development. A series of sensitivity experiments was conducted to identify the primary differences between the two schemes that resulted in the large discrepancies in the simulations. Different approaches in treating graupel and hail were found to be responsible for many of the key differences between the baseline simulations. The inclusion of hail in the baseline simulation using the Milbrant–Yau scheme with two rimed-ice categories (graupel and hail) had little impact, and therefore resulted in a much different storm than the baseline run with the single-category (hail) Morrison scheme. With graupel as the choice of the single rimed-ice category, the simulated storms had considerably more frozen condensate in the anvil region, a weaker cold pool, and reduced surface precipitation compared to the runs with only hail, whose higher terminal fall velocity inhibited lofting. The cold pool strength was also found to be sensitive to the parameterization of raindrop breakup, particularly for the Morrison scheme, because of the effects on the drop size distributions and the corresponding evaporative cooling rates. The use of a more aggressive implicit treatment of drop breakup in the baseline Morrison scheme, by limiting the mean–mass raindrop diameter to a maximum of 0.9 mm, opposed the tendency of this scheme to otherwise produce large mean drop sizes and a weaker cold pool compared to the hail-only run using the Milbrandt–Yau scheme.

On Sedimentation and Advection in Multimoment Bulk Microphysics

AbstractIn two-moment bulk microphysics schemes, the practice of using different weighted fall velocities for the various moments is known to lead to artificial growth in reflectivity values for fast-falling particles, particularly at the downward leading edge of a precipitation column. Two simple correction schemes that prevent these artifacts while still allowing some effects of size sorting are presented. The corrections are obtained by comparing particle number concentrations that result from two or three different sedimentation calculations. The corrections do not conserve particle number concentrations but do prevent spurious reflectivity growth automatically without the need to place ad hoc limits on mean particle size.Multimoment bulk microphysics schemes often have used inconsistent variables in terms of the appropriate advection equation (e.g., mass mixing ratio and particle number concentration). A brief review of consistent advection and turbulent mixing for such variables is presented to provide clarification.

Simulations of Polarimetric Radar Signatures of a Supercell Storm Using a Two-Moment Bulk Microphysics Scheme

Abstract A new general polarimetric radar simulator for nonhydrostatic numerical weather prediction (NWP) models has been developed based on rigorous scattering calculations using the T-matrix method for reflectivity, differential reflectivity, specific differential phase, and copolar cross-correlation coefficient. A continuous melting process accounts for the entire spectrum of varying density and dielectric constants. This simulator is able to simulate polarimetric radar measurements at weather radar frequency bands and can take as input the prognostic variables of high-resolution NWP model simulations using one-, two-, and three-moment microphysics schemes. The simulator was applied at 10.7-cm wavelength to a model-simulated supercell storm using a double-moment (two moment) bulk microphysics scheme to examine its ability to simulate polarimetric signatures reported in observational studies. The simulated fields exhibited realistic polarimetric signatures that include ZDR and KDP columns, ZDR arc, midlevel ZDR and ρhυ rings, hail signature, and KDP foot in terms of their general location, shape, and strength. The authors compared the simulation with one employing a single-moment (SM) microphysics scheme and found that certain signatures, such as ZDR arc, midlevel ZDR, and ρhυ rings, cannot be reproduced with the latter. It is believed to be primarily caused by the limitation of the SM scheme in simulating the shift of the particle size distribution toward larger/smaller diameters, independent of mixing ratio. These results suggest that two- or higher-moment microphysics schemes should be used to adequately describe certain important microphysical processes. They also demonstrate the utility of a well-designed radar simulator for validating numerical models. In addition, the simulator can also serve as a training tool for forecasters to recognize polarimetric signatures that can be reproduced by advanced NWP models.

Silver iodide seeding impact on the microphysics and dynamics of convective clouds in the high plains

The concept of dynamic seeding is a physically plausible hypothesis but has not yet been confirmed by observations or numerical simulations. To verify the hypothesis of dynamic seeding, a three-dimensional nonhydrostatic cloud model with two-moment bulk microphysics scheme has been used to investigate the effects of silver iodide seeding on cloud microphysics, dynamics and precipitation of convective storms. Eight species of water are included in the model: vapor, cloud water, rain, cloud ice, snow, graupel, frozen drops and hail. A High Plains hailstorm case developed on 1 August 1981 during the Cooperative Convective Precipitation Experiment season is used for the simulations. The simulated cloud system consists of two cloud cycles during the period of integration. The second-cycle clouds are the dominant precipitation producer of the simulation, contributes about 80% of the total surface precipitation, which are caused by interactions of the downdraft outflow induced by falling precipitation from the first cycle cloud in the boundary layer and the southeasterly relative inflow at low level. The model results show that the cold microphysical processes dominate the hydrometeor production in the simulated storms. The ice hydrometeors account for ~ 70% of the total hydrometeor mass. Accretion of cloud water is the dominant growth mechanism for precipitating ice hydrometeors. Melting of graupel and accretion of cloud water by rain are the major sources of rain water. Conversion of graupel is the largest source of hail formation, contributing about 80%. Four seeding tests have been carried out to investigate the effects of seeding at a different release mode (instantaneous or continuous, one grid point or several grid points), and with different amounts of the seeding agent. All of cases are seeded in the region of the strongest updraft when the model cloud top was passing the − 10 °C level at 10 min, and produce significant effects. The cloud seeding results in substantial increases in accumulated precipitation at the surface in all seeded cases (by 20–30%). Moreover, both rainfall and hailfall have increased due to seeding. The most important contribution to the increase in hail is due to conversion of graupel to hail and accretion of cloud water by hail. Increase of graupel melting and subsequent accretion of cloud water by rain contribute mostly to rain enhancement. The seeding enhances the unloading effect of precipitation mass mainly in the form of graupel, leads to a stronger downdraft outflow and enhanced convergence in the boundary layer, further causes the secondary clouds to form earlier and grow larger. The enhanced updraft increases the inflow and causes the cloud to process more water vapor and thereby cloud water, resulting in increase of accretional growth of cloud water by precipitating particles, finally the precipitation enhancement. These results indicate that silver iodide seeding could significantly influence the cloud dynamics, microphysics and further precipitation of convective storms in the High Plains. The simulation not only supports the hypothesis of dynamic seeding, but also demonstrates that the convective cloud with a cold base but a long lifetime has dynamic seeding potential as well.

A comparison of spectral bin and two-moment bulk mixed-phase cloud microphysics

This numerical study investigates the representation of cloud microphysical processes in cloud resolving models and the effects of different characteristics of cloud condensation nuclei (CCN) on the evolution of deep convective storms. A comparison of several simulations is presented obtained by applying a spectral bin method and a two-moment bulk microphysical scheme to a deep convective cloud and a squall line. Both modeling approaches show similar results regarding the vertical structure of the clouds, updraft velocities and surface precipitation as well as the sensitivity of these parameters to changes in CCN characteristics. The simulated isolated cell reveals a strong effect to the variation of CCN concentration on the amount of surface precipitation, while the results for the squall line system depend on the specific treatment of the nucleation process.

Mesoscale Modeling of Springtime Arctic Mixed-Phase Stratiform Clouds Using a New Two-Moment Bulk Microphysics Scheme

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.