Improving the Representation of Aggregation in a Two-moment Microphysical Scheme with Statistics of Multi-frequency Doppler Radar Observations

Abstract. The simulation of aggregation of ice particles is critical for precipitation prediction, but still a major challenge. Its simulation requires assumptions about numerous parameters, many of which are either not well known or difficult to represent accurately in bulk microphysics schemes. However, knowing the sensitivity of aggregation to various simplified assumptions can help to identify critical parameters. By comparison with suitable observations, these critical parameters can even be constrained. We investigate the sensitivity of the model variables, and the modeled multi-frequency and Doppler radar observables to different parameters in a two-moment microphysics scheme. Therefore, we revise hydrometeor parameters by using a recently published dataset of particle properties, modify the formulations of the aggregation process (which allows using an area-based differential sedimentation kernel) and update other ice microphysical parameters in the scheme such as the sticking efficiency Estick and the shape of the size distribution. Overall, particle properties, definition of the aggregation kernel, and size distribution width prove to be most important, while Estick and the cloud ice habit have less influence. Finally, we run multi-week simulations with the most promising parameter combinations. The statistical comparison between real and synthetic observables shows a reduction in the velocity and snow particle size. With this study, we show a possible way to revise processes in microphysical schemes by using statistics of detailed cloud radar observations.

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Improving the representation of aggregation in a two-moment microphysical scheme with statistics of multi-frequency Doppler radar observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-17133-2021 ◽

2021 ◽

Vol 21 (22) ◽

pp. 17133-17166

Author(s):

Markus Karrer ◽

Axel Seifert ◽

Davide Ori ◽

Stefan Kneifel

Keyword(s):

Size Distribution ◽

3D Model ◽

Doppler Radar ◽

Terminal Velocity ◽

Critical Parameters ◽

Distribution Width ◽

Radar Observations ◽

Functional Relationships ◽

Definition Of ◽

The Impact

Abstract. Aggregation is a key microphysical process for the formation of precipitable ice particles. Its theoretical description involves many parameters and dependencies among different variables that are either insufficiently understood or difficult to accurately represent in bulk microphysics schemes. Previous studies have demonstrated the valuable information content of multi-frequency Doppler radar observations to characterize aggregation with respect to environmental parameters such as temperature. Comparisons with model simulations can reveal discrepancies, but the main challenge is to identify the most critical parameters in the aggregation parameterization, which can then be improved by using the observations as constraints. In this study, we systematically investigate the sensitivity of physical variables, such as number and mass density, as well as the forward-simulated multi-frequency and Doppler radar observables, to different parameters in a two-moment microphysics scheme. Our approach includes modifying key aggregation parameters such as the sticking efficiency or the shape of the size distribution. We also revise and test the impact of changing functional relationships (e.g., the terminal velocity–size relation) and underlying assumptions (e.g., the definition of the aggregation kernel). We test the sensitivity of the various components first in a single-column “snowshaft” model, which allows fast and efficient identification of the parameter combination optimally matching the observations. We find that particle properties, definition of the aggregation kernel, and size distribution width prove to be most important, while the sticking efficiency and the cloud ice habit have less influence. The setting which optimally matches the observations is then implemented in a 3D model using the identical scheme setup. Rerunning the 3D model with the new scheme setup for a multi-week period revealed that the large overestimation of aggregate size and terminal velocity in the model could be substantially reduced. The method presented is expected to be applicable to constrain other ice microphysical processes or to evaluate and improve other schemes.

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On microphysical processes of noctilucent clouds (NLC): observations and modeling of mean and width of the particle size-distribution

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-10-3605-2010 ◽

2010 ◽

Vol 10 (2) ◽

pp. 3605-3625

Author(s):

G. Baumgarten ◽

J. Fiedler ◽

M. Rapp

Keyword(s):

Particle Size ◽

Linear Relationship ◽

Size Distribution ◽

Eddy Diffusion ◽

Particle Sizes ◽

Noctilucent Clouds ◽

Atmospheric Variability ◽

Distribution Width ◽

Particle Properties ◽

Microphysical Processes

Abstract. Noctilucent clouds (NLC) in the polar summer mesopause region have been observed in Norway (69° N, 16° E) between 1998 and 2009 by 3-color lidar technique. Assuming a mono-modal Gaussian size distribution we deduce mean and width of the particle sizes throughout the clouds. We observe a quasi linear relationship between distribution width and mean of the particle size at the top of the clouds and a deviation from this behavior for particle sizes larger than 40 nm, most often in the lower part of the layer. The vertically integrated particle properties show that 65% of the data follows the linear relationship with a slope of 0.42±0.02. For the vertically resolved particle properties (Δz=0.15 km) the slope is smaller and only 0.39±0.03. We compare our observations to microphysical modeling of noctilucent clouds and find that the distribution width depends on turbulence, the time that turbulence can act (cloud age), and the sampling volume/time (atmospheric variability). The model results nicely reproduce the measurements and show that the observed slope can be explained by eddy diffusion profiles as observed from rocket measurements.

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Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part I: Scheme Description and Idealized Tests

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-14-0065.1 ◽

2015 ◽

Vol 72 (1) ◽

pp. 287-311 ◽

Cited By ~ 176

Author(s):

Hugh Morrison ◽

Jason A. Milbrandt

Keyword(s):

Degrees Of Freedom ◽

Cloud Microphysics ◽

Squall Line ◽

Microphysics Scheme ◽

Particle Properties ◽

Wide Range ◽

Single Category ◽

Ratio Variables ◽

Cloud Ice ◽

Ice Phase

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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On microphysical processes of noctilucent clouds (NLC): observations and modeling of mean and width of the particle size-distribution

Atmospheric Chemistry and Physics ◽

10.5194/acp-10-6661-2010 ◽

2010 ◽

Vol 10 (14) ◽

pp. 6661-6668 ◽

Cited By ~ 27

Author(s):

G. Baumgarten ◽

J. Fiedler ◽

M. Rapp

Keyword(s):

Particle Size ◽

Linear Relationship ◽

Size Distribution ◽

Eddy Diffusion ◽

Particle Sizes ◽

Noctilucent Clouds ◽

Atmospheric Variability ◽

Distribution Width ◽

Particle Properties ◽

Microphysical Processes

Abstract. Noctilucent clouds (NLC) in the polar summer mesopause region have been observed in Norway (69° N, 16° E) between 1998 and 2009 by 3-color lidar technique. Assuming a mono-modal Gaussian size distribution we deduce mean and width of the particle sizes throughout the clouds. We observe a quasi linear relationship between distribution width and mean of the particle size at the top of the clouds and a deviation from this behavior for particle sizes larger than 40 nm, most often in the lower part of the layer. The vertically integrated particle properties show that 65% of the data follows the linear relationship with a slope of 0.42±0.02 for mean particle sizes up to 40 nm. For the vertically resolved particle properties (Δz = 0.15 km) the slope is comparable and about 0.39±0.03. For particles larger than 40 nm the distribution width becomes nearly independent of particle size and even decreases in the lower part of the layer. We compare our observations to microphysical modeling of noctilucent clouds and find that the distribution width depends on turbulence, the time that turbulence can act (cloud age), and the sampling volume/time (atmospheric variability). The model results nicely reproduce the measurements and show that the observed slope can be explained by eddy diffusion profiles as observed from rocket measurements.

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A Triple-Moment Representation of Ice in the Predicted Particle Properties (P3) Microphysics Scheme

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-20-0084.1 ◽

2020 ◽

Author(s):

Jason A. Milbrandt ◽

Hugh Morrison ◽

Daniel T. Dawson ◽

Marco Paukert

Keyword(s):

Size Distribution ◽

Kinematic Model ◽

Model Framework ◽

Microphysics Scheme ◽

Moment Representation ◽

Particle Properties ◽

Physically Based ◽

Size Sorting ◽

Necessary Constraints ◽

Ice Phase

AbstractIn the original Predicted Particle Properties (P3) bulk microphysics scheme, all ice-phase hydrometeors are represented by one or more “free” ice categories, where the physical properties evolve smoothly through changes to the four prognostic variables (per category,) and with a 2-moment representation of the particle size distribution. As such, the spectral dispersion cannot evolve independently, which thus results in limitations in representation of ice – in particular hail – due to necessary constraints in the scheme to prevent excessive gravitational size sorting. To overcome this, P3 has been modified to include a 3-moment representation of the size distribution of each ice category through the addition of a fifth prognostic variable, the sixth moment of the size distribution.The details of the 3-moment ice parameterization in P3 are provided. The behavior of the modified scheme, with the single-ice-category configuration, is illustrated through simulations in a simple 1D kinematic model framework as well as with near large-eddy-resolving (250-m grid spacing) 3D simulations of a hail-producing supercell. It is shown that the 3-moment ice configuration controls size sorting in a physically-based way and leads to an improved capacity to simulate large, heavily-rimed ice (hail), including mean and maximum sizes and reflectivity, and thus an overall improvement in the representation of ice-phase particles in the P3 scheme.

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Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall Line: Comparison of One- and Two-Moment Schemes

Monthly Weather Review ◽

10.1175/2008mwr2556.1 ◽

2009 ◽

Vol 137 (3) ◽

pp. 991-1007 ◽

Cited By ~ 1057

Author(s):

H. Morrison ◽

G. Thompson ◽

V. Tatarskii

Keyword(s):

Size Distribution ◽

Cloud Microphysics ◽

Squall Line ◽

Cloud Droplets ◽

Microphysics Scheme ◽

Mixing Ratios ◽

Stratiform Region ◽

Stratiform Precipitation ◽

The One ◽

Cloud Ice

Abstract A new two-moment cloud microphysics scheme predicting the mixing ratios and number concentrations of five species (i.e., cloud droplets, cloud ice, snow, rain, and graupel) has been implemented into the Weather Research and Forecasting model (WRF). This scheme is used to investigate the formation and evolution of trailing stratiform precipitation in an idealized two-dimensional squall line. Results are compared to those using a one-moment version of the scheme that predicts only the mixing ratios of the species, and diagnoses the number concentrations from the specified size distribution intercept parameter and predicted mixing ratio. The overall structure of the storm is similar using either the one- or two-moment schemes, although there are notable differences. The two-moment (2-M) scheme produces a widespread region of trailing stratiform precipitation within several hours of the storm formation. In contrast, there is negligible trailing stratiform precipitation using the one-moment (1-M) scheme. The primary reason for this difference are reduced rain evaporation rates in 2-M compared to 1-M in the trailing stratiform region, leading directly to greater rain mixing ratios and surface rainfall rates. Second, increased rain evaporation rates in 2-M compared to 1-M in the convective region at midlevels result in weaker convective updraft cells and increased midlevel detrainment and flux of positively buoyant air from the convective into the stratiform region. This flux is in turn associated with a stronger mesoscale updraft in the stratiform region and enhanced ice growth rates. The reduced (increased) rates of rain evaporation in the stratiform (convective) regions in 2-M are associated with differences in the predicted rain size distribution intercept parameter (which was specified as a constant in 1-M) between the two regions. This variability is consistent with surface disdrometer measurements in previous studies that show a rapid decrease of the rain intercept parameter during the transition from convective to stratiform rainfall.

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