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Jason A. Milbrandt
and
Hugh Morrison

Abstract

A method to predict the bulk density of graupel ρg has been added to the two-moment Milbrandt–Yau bulk microphysics scheme. The simulation of graupel using the modified scheme is illustrated through idealized simulations of a mesoscale convective system using a 2D kinematic model with a prescribed flow field and different peak updraft speeds. To examine the relative impact of the various approaches to represent rimed ice, simulations were run for various graupel-only and graupel-plus-hail configurations.

Because of the direct feedback of ρg to terminal fall speeds, the modified scheme produces a much different spatial distribution of graupel, with more mass concentrated in the convective region resulting in changes to the surface precipitation at all locations. With a strong updraft, the model can now produce solid precipitation at the surface in the convective region without a separate hail category. It is shown that a single rimed-ice category is capable of representing a realistically wide range of graupel characteristics in various atmospheric conditions without the need for a priori parameter settings.

Sensitivity tests were conducted to examine various aspects of the scheme that affect the simulated ρg . Specific parameterizations pertaining to other hydrometeor categories now have a direct impact on the simulation of graupel, including the assumed aerosol distribution for droplet nucleation, which affects the drop sizes of both cloud and rain, and the mass–size relation for snow, which affects its density and hence the embryo density of graupel converted from snow due to riming.

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Hugh Morrison
and
Jason A. Milbrandt

Abstract

A method for the parameterization of ice-phase microphysics is proposed and used to develop a new bulk microphysics scheme. All ice-phase particles are represented by several physical properties that evolve freely in time and space. The scheme prognoses four ice mixing ratio variables, total mass, rime mass, rime volume, and number, allowing 4 degrees of freedom for representing the particle properties using a single category. This approach represents a significant departure from traditional microphysics schemes in which ice-phase hydrometeors are partitioned into various predefined categories (e.g., cloud ice, snow, and graupel) with prescribed characteristics. The liquid-phase component of the new scheme uses a standard two-moment, two-category approach.

The proposed method and a complete description of the new predicted particle properties (P3) scheme are provided. Results from idealized model simulations of a two-dimensional squall line are presented that illustrate overall behavior of the scheme. Despite its use of a single ice-phase category, the scheme simulates a realistically wide range of particle characteristics in different regions of the squall line, consistent with observed ice particles in real squall lines. Sensitivity tests show that both the prediction of the rime mass fraction and the rime density are important for the simulation of the squall-line structure and precipitation.

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Caroline Jouan
and
Jason A. Milbrandt

Abstract

Simulations of a well-observed squall line that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E) were conducted using a mesoscale model with a horizontal grid spacing of 1 km to examine the importance of parameterized ice-phase processes to changes in concentrations of activated cloud condensation nuclei (CCN) in a detailed two-moment bulk microphysics scheme. Numerical experiments showed that the simulated squall-line structure was sensitive to changes in activated CCN concentration not only from the direct impacts on cloud droplet sizes and autoconversion rates, but also because of changes in the growth rates and spatial distribution of ice-phase condensate. A microphysical budget analysis highlighted the importance of graupel in rain production and the sensitivity of graupel growth rates on changes to CCN concentrations. Sensitivity tests on the level of detail in the representation of graupel, specifically the treatment of its bulk density and the number of prognostic moments, indicated that changes in the reflectivity and precipitation structure of the simulated storm due to changes in CCN were sensitive to the graupel parameterization. The results suggest that the proper representation of graupel and possibly other ice-phase categories in microphysics schemes may be crucial for correctly simulating the effects of changes to CCN concentrations for continental deep convective systems.

Open access
Dominique Brunet
and
Jason A. Milbrandt

Abstract

The surface precipitation network in Canada suffers from large data gaps due to the challenge of covering a large country with a low population density. A proof-of-concept for an optimal network design is proposed to more efficiently estimate precipitation in Canada with the design goal of minimizing the interpolation uncertainty. The network design is based on a statistical model of precipitation that accounts for intermittency and non-Gaussianity of precipitation. Our results indicate that the greatest needs for new stations are in British Columbia, where coastal and mountain climate leads to more uncertainty in precipitation amounts, while the Prairie Provinces (Alberta, Saskatchewan, and Manitoba) could gain efficiencies by reducing their network size. Despite the current low density of stations in the territories north of Canada, these drier and colder regions only have a moderate need for more stations, mostly in the mountainous regions of Yukon. However, from a spatially varying wind undercatch measurement error model, it is shown that these northern regions have greatest need for higher-accuracy measurements.

Significance Statement

The proposed methodology can guide in the optimal placement of precipitation gauges across a large country such as Canada, which will provide value for money in how rain and snow are monitored.

Open access
Kwinten Van Weverberg
,
Andrew M. Vogelmann
,
Hugh Morrison
, and
Jason A. Milbrandt

Abstract

This 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.

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Daniel T. Dawson II
,
Ming Xue
,
Jason A. Milbrandt
, and
Alan Shapiro

Abstract

Numerical predictions of the 3 May 1999 Oklahoma City, Oklahoma, tornadic supercell are performed within a real-data framework utilizing telescoping nested grids of 3-km, 1-km, and 250-m horizontal spacing. Radar reflectivity and radial velocity from the Oklahoma City WSR-88D are assimilated using a cloud analysis procedure coupled with a cycled 3DVAR system to analyze storms on the 1-km grid for subsequent forecast periods. Single-, double-, and triple-moment configurations of a multimoment bulk microphysics scheme are used in several experiments on the 1-km and 250-m grids to assess the impact of varying the complexity of the microphysics scheme on the storm structure, behavior, and tornadic activity (on the 250-m grid). This appears to be the first study of its type to investigate single- versus multimoment microphysics within a real-data context.

It is found that the triple-moment scheme overall performs the best, producing the smallest track errors for the mesocyclone on the 1-km grid, and stronger and longer-lived tornado-like vortices (TLVs) on the 250-m grid, closest to the observed tornado. In contrast, the single-moment scheme with the default Marshall–Palmer rain intercept parameter performs poorly, producing a cold pool that is too strong, and only weak and short-lived TLVs. The results in the context of differences in latent cooling from evaporation and melting between the schemes, as well as implications for numerical prediction of tornadoes, are discussed. More generally, the feedbacks to storm thermodynamics and dynamics from increasing the prognostic detail of the hydrometeor size distributions are found to be important for improving the simulation and prediction of tornadic thunderstorms.

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Mélissa Cholette
,
Hugh Morrison
,
Jason A. Milbrandt
, and
Julie M. Thériault

Abstract

Bulk microphysics parameterizations that are used to represent clouds and precipitation usually allow only solid and liquid hydrometeors. Predicting the bulk liquid fraction on ice allows an explicit representation of mixed-phase particles and various precipitation types, such as wet snow and ice pellets. In this paper, an approach for the representation of the bulk liquid fraction into the predicted particle properties (P3) microphysics scheme is proposed and described. Solid-phase microphysical processes, such as melting and sublimation, have been modified to account for the liquid component. New processes, such as refreezing and condensation of the liquid portion of mixed-phase particles, have been added to the parameterization. Idealized simulations using a one-dimensional framework illustrate the overall behavior of the modified scheme. The proposed approach compares well to a Lagrangian benchmark model. Temperatures required for populations of ice crystals to melt completely also agree well with previous studies. The new processes of refreezing and condensation impact both the surface precipitation type and feedback between the temperature and the phase changes. Overall, prediction of the bulk liquid fraction allows an explicit description of new precipitation types, such as wet snow and ice pellets, and improves the representation of hydrometeor properties when the temperature is near 0°C.

Open access
Marcus Johnson
,
Youngsun Jung
,
Jason A. Milbrandt
,
Hugh Morrison
, and
Ming Xue

Abstract

Many flavors of multicategory, multimoment bulk microphysics schemes (BMPs) have various treatments of rimed ice. In this study, we compare three two-moment schemes available in the WRF Model—Milbrandt–Yau (MY2), National Severe Storms Laboratory (NSSL), and the two-category configuration of the Predicted Particle Properties (P3) scheme—focusing on differences in rimed-ice representation and their impacts on surface rain and ice. Idealized supercell simulations are performed. A polarimetric radar data simulator is used to evaluate their ability to reproduce the Z DR arc and hail signature in the forward-flank downdraft, well-known supercell polarimetric signatures that are potentially sensitive to rimed-ice parameterization. Both the MY2 and NSSL schemes simulate enhanced surface Z DR bands, but neither scheme simulates a Z DR arc commonly identified in observation-based studies. Surface Z DR in the default P3 scheme is homogeneous in the supercell’s forward flank, and is due to the scheme’s restrictive minimum rain particle size distribution (PSD) slope bound preventing the presence of larger drops creating a Z DR arc. The NSSL scheme simulates the location of the hail signature in the forward-flank downdraft more consistent with observations than the other two schemes. Large hail in MY2 sediments well downstream of the updraft (atypically compared to observations) near the surface. The sedimentation of large ice in the default P3 scheme is limited by a restrictive maximum ice number-weighted mean diameter limit within the scheme, precluding the scheme’s ability to reduce Z DR (and ρ HV compared to the MY2 and NSSL schemes) near the surface.

Free access
Mélissa Cholette
,
Julie M. Thériault
,
Jason A. Milbrandt
, and
Hugh Morrison

Abstract

A prognostic equation for the liquid fraction of mixed-phase particles has been recently added to the Predicted Particle Properties (P3) bulk microphysics scheme. Mixed-phase particles are necessary to simulate key microphysical processes leading to various winter precipitation types, such as ice pellets and freezing rain. To illustrate the impacts of predicting the bulk liquid fraction, the 1998 North American Ice Storm is simulated using the Weather Research and Forecasting (WRF) Model with the modified P3 scheme. It is found that simulating partial melting by predicting the bulk liquid fraction produces higher mass and number mixing ratios of rain. This leads to smaller rain sizes reaching the refreezing layer as well as a decrease in the freezing rain accumulation at the surface by up to 30% in some locations compared to when no liquid fraction is predicted. The increase in fall speed and density and decrease of particle diameter during partial melting combined with an improved representation of the refreezing process in the modified P3 leads to generally higher total solid surface precipitation rates than using the original P3 scheme. There is also an increase of solid precipitation in regions of ice pellet accumulation. Overall, the simulation of mixed-phase particles notably impacts the vertical and spatial distributions of precipitation properties.

Open access
Agnieszka Barszcz
,
Jason A. Milbrandt
, and
Julie M. Thériault

Abstract

A freezing rain event, in which the Meteorological Centre of Canada’s 2.5-km numerical weather prediction system significantly underpredicted the quantity of freezing rain, is examined. The prediction system models precipitation types explicitly, directly from the Milbrandt–Yau microphysics scheme. It was determined that the freezing rain underprediction for this case was due primarily to excessive refreezing of rain, originating from melting snow and graupel, in and under the temperature inversion of the advancing warm front ultimately depleting the supply of rain reaching the surface. The refreezing was caused from excessive collisional freezing between rain and graupel. Sensitivity experiments were conducted to examine the effects of a temperature threshold for collisional freezing and on varying the values of the collection efficiencies between rain and ice-phase hydrometeors. It was shown that by reducing the rain–graupel collection efficiency and by imposing a temperature threshold of −5°C, above which collisional freezing is not permitted, excessive rain–graupel collection and graupel formation can be controlled in the microphysics scheme, leading to an improved simulation of freezing rain at the surface.

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