scholarly journals Polarimetric Radar Observation Operator for a Cloud Model with Spectral Microphysics

2011 ◽  
Vol 50 (4) ◽  
pp. 873-894 ◽  
Author(s):  
A. Ryzhkov ◽  
M. Pinsky ◽  
A. Pokrovsky ◽  
A. Khain
Keyword(s):  
Size Distribution ◽  
Cloud Model ◽  
Distribution Functions ◽  
Radar Observation ◽  
Polarimetric Radar ◽  
Observation Operator ◽  
Cloud Models ◽  
Hebrew University ◽  
The Relationship

AbstractThe radar observation operator for computation of polarimetric radar variables from the output of numerical cloud models is described in its most generic form. This operator is combined with the Hebrew University of Jerusalem cloud model with spectral microphysics. The model contains 7 classes of hydrometeors and each class is represented by size distribution functions in 43 size bins. The performance of the cloud model and radar observation operator has been evaluated for the case of a hailstorm in Oklahoma on 2 February 2009. It is shown that the retrieved fields of polarimetric radar variables at C and S microwave bands are generally consistent with results of observations. The relationship between microphysical and polarimetric signatures is illustrated.

Simulation of Effects of Atmospheric Aerosols on Deep Turbulent Convective Clouds Using a Spectral Microphysics Mixed-Phase Cumulus Cloud Model. Part I: Model Description and Possible Applications

2004 ◽  
Vol 61 (24) ◽  
pp. 2963-2982 ◽  
Author(s):  
A. Khain ◽  
A. Pokrovsky ◽  
M. Pinsky ◽  
A. Seifert ◽  
V. Phillips
Keyword(s):  
Distribution Function ◽  
Size Distribution ◽  
Cloud Model ◽  
Equation System ◽  
Size Distribution Function ◽  
Distribution Functions ◽  
Model Description ◽  
Convective Heating ◽  
Convective Clouds ◽  
Hebrew University

Abstract An updated version of the spectral (bin) microphysics cloud model developed at the Hebrew University of Jerusalem [the Hebrew University Cloud Model (HUCM)] is described. The model microphysics is based on the solution of the equation system for size distribution functions of cloud hydrometeors of seven types (water drops, plate-, columnar-, and branch-like ice crystals, aggregates, graupel, and hail/frozen drops) as well as for the size distribution function of aerosol particles playing the role of cloud condensational nuclei (CCN). Each size distribution function contains 33 mass bins. The conditions allowing numerical reproduction of a narrow droplet spectrum up to the level of homogeneous freezing in deep convective clouds developed in smoky air are discussed and illustrated using as an example Rosenfeld and Woodley's case of deep Texas clouds. The effects of breakup on precipitation are illustrated by the use of a new collisional breakup scheme. Variation of the microphysical structure of a melting layer is illustrated by using the novel melting procedure. It is shown that an increase in the aerosol concentration leads to a decrease in precipitation from single clouds both under continental and maritime conditions. To provide similar precipitation, a cloud developed in smoky air should have a higher top height. The mechanisms are discussed through which aerosols decrease precipitation efficiency. It is shown that aerosols affect the vertical profile of the convective heating caused by latent heat release.

scholarly journals What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 362 ◽  
Author(s):  
Alexander V. Ryzhkov ◽  
Jeffrey Snyder ◽  
Jacob T. Carlin ◽  
Alexander Khain ◽  
Mark Pinsky
Keyword(s):  
Cloud Model ◽  
Weather Prediction ◽  
Primary Source ◽  
Polarimetric Radar ◽  
Microphysical Process ◽  
Weather Radars ◽  
Cloud Models ◽  
Cloud Modeling ◽  
Bin Microphysics ◽  
The Impact

The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.

scholarly journals Towards a Better Representation of Fog Microphysics in Large-Eddy Simulations Based on an Embedded Lagrangian Cloud Model

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 466 ◽  
Author(s):  
Johannes Schwenkel ◽  
Björn Maronga
Keyword(s):  
Size Distribution ◽  
Cloud Model ◽  
Radiative Cooling ◽  
Diffusional Growth ◽  
Radiation Fog ◽  
Microphysics Scheme ◽  
Spatial And Temporal Scales ◽  
Fog Microphysics ◽  
Cloud Models ◽  
Large Eddy

The development of radiation fog is influenced by multiple physical processes such as radiative cooling and heating, turbulent mixing, and microphysics, which interact on different spatial and temporal scales with one another. Once a fog layer has formed, the number of fog droplets and their size distribution have a particularly large impact on the development of the fog layer due to their feedback on gravitational settling and radiative cooling at the fog top, which are key processes for fog. However, most models do not represent microphysical processes explicitly, or parameterize them rather crudely. In this study we simulate a deep radiation fog case with a coupled large-eddy simulation (LES)–Lagrangian cloud model (LCM) approach for the first time. By simulating several hundred million fog droplets as Lagrangian particles explicitly (using the so-called superdroplet approach), we include a size-resolved diffusional growth including Köhler theory and gravitational sedimentation representation. The results are compared against simulations using a state of the art bulk microphysics model (BCM). We simulate two different aerosol backgrounds (pristine and polluted) with each microphysics scheme. The simulations show that both schemes generally capture the key features of the deep fog event, but also that there are significant differences: the drop size distribution produced by the LCM is broader during the formation and dissipation phase than in the BCM. The LCM simulations suggest that its spectral shape, which is fixed in BCMs, exhibits distinct changes during the fog life cycle, which cannot be taken into account in BCMs. The picture of the overall fog droplet number concentration is twofold: For both aerosol environments, the LCM shows lower concentrations of larger fog droplets, while we observe a higher number of small droplets and swollen aerosols reducing the visibility earlier than in the BCM. As a result of the different model formulation we observe higher sedimentation rates and lower liquid water paths for the LCM. The present work demonstrates that it is possible to simulate fog with the computational demanding approach of LCMs to assess the advantages of high-resolution cloud models and further to estimate errors of traditional parameterizations.

The Anatomy and Physics of ZDR Columns: Investigating a Polarimetric Radar Signature with a Spectral Bin Microphysical Model

2014 ◽  
Vol 53 (7) ◽  
pp. 1820-1843 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Alexander P. Khain ◽  
Nir Benmoshe ◽  
Eyal Ilotoviz ◽  
Alexander V. Ryzhkov ◽  
...  
Keyword(s):  
Life Cycle ◽  
Cloud Model ◽  
Supercooled Liquid ◽  
Column Height ◽  
Polarimetric Radar ◽  
Liquid Drops ◽  
Practical Applications ◽  
Radar Signature ◽  
Hebrew University ◽  
Differential Reflectivity

AbstractPolarimetric radar observations of deep convective storms frequently reveal columnar enhancements of differential reflectivity ZDR. Such “ZDR columns” can extend upward more than 3 km above the environmental 0°C level, indicative of supercooled liquid drops being lofted by the updraft. Previous observational and modeling studies of ZDR columns are reviewed. To address remaining questions, the Hebrew University Cloud Model, an advanced spectral bin microphysical model, is coupled with a polarimetric radar operator to simulate the formation and life cycle of ZDR columns in a deep convective continental storm. In doing so, the mechanisms by which ZDR columns are produced are clarified, including the formation of large raindrops in the updraft by recirculation of smaller raindrops formed aloft back into the updraft at low levels. The internal hydrometeor structure of ZDR columns is quantified, revealing the transition from supercooled liquid drops to freezing drops to hail with height in the ZDR column. The life cycle of ZDR columns from early formation, through growth to maturity, to demise is described, showing how hail falling out through the weakening or ascending updraft bubble dominates the reflectivity factor ZH, causing the death of the ZDR column and leaving behind its “ghost” of supercooled drops. In addition, the practical applications of ZDR columns and their evolution are explored. The height of the ZDR column is correlated with updraft strength, and the evolution of ZDR column height is correlated with increases in ZH and hail mass content at the ground after a lag of 10–15 min.

scholarly journals Particle Size Distribution Based Occurrence Features of Organic Components in Printing and Dyeing Wastewater Under a Treatment Process

2019 ◽  
Vol 118 ◽  
pp. 04009
Author(s):  
Yuan Li ◽  
Jie Liu ◽  
Yibiao Yu ◽  
Hao Zhu ◽  
Zheng Shen ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Reverse Osmosis ◽  
Treatment Process ◽  
Dyeing Wastewater ◽  
Wastewater Treatment Process ◽  
Printing And Dyeing Wastewater ◽  
Sedimentation Tank ◽  
The Relationship

A more detailed occurrence features of organic matters in the printing and dyeing wastewater, based on its particle size distribution (PSD) and along with a wastewater treatment process, was conducted to provide a support for advanced treatment. Results suggested that, (1) In the dyeing wastewater, the occurrence characteristic of COD was: soluble>supra colloidal>colloidal>settleable; However, for protein, the supra colloidal was dominant, followed by the soluble. The feature of the polysaccharide was consistent with COD’s. In the wastewater, 29.66% of COD could be attributed to proteins and 3.45% of the COD could be attributed to polysaccharides. (2) The relationship among the forms of COD in the primary sedimentation tank, aerobic tank, secondary sedimentation tank, and reverse osmosis-treated concentrated effluent was consistent, that was: soluble>colloidal>supra colloidal>settleable. (3) In the primary sedimentation tank, the settleable COD was almost completely removed; In the aerobic tank, the residual super colloidal COD was not much; After MBR-RO treatment, the COD in the reverse osmosis concentrated water was almost dissolved and only a little presented in other forms.

scholarly journals Experimental-numerical studies of the effect of cell structure on the mechanical properties of polypropylene foams

e-Polymers ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 713-723
Author(s):  
Wei Gong ◽  
Tuan-Hui Jiang ◽  
Xiang-Bu Zeng ◽  
Li He ◽  
Chun Zhang
Keyword(s):  
Mechanical Properties ◽  
Size Distribution ◽  
Cell Size ◽  
Cell Structure ◽  
Structure Parameters ◽  
Cell Size Distribution ◽  
Numerical Studies ◽  
Polypropylene Foam ◽  
The Impact ◽  
The Relationship

AbstractThe effects of the cell size and distribution on the mechanical properties of polypropylene foam were simulated and analyzed by finite element modeling with ANSYS and supporting experiments. The results show that the reduced cell size and narrow size distribution have beneficial influences on both the tensile and impact strengths. Decreasing the cell size or narrowing the cell size distribution was more effective for increasing the impact strength than the tensile strength in the same case. The relationship between the mechanical properties and cell structure parameters has a good correlation with the theoretical model.

Comparison of Ice-Phase Microphysical Parameterization Schemes Using Numerical Simulations of Tropical Convection

1991 ◽  
Vol 30 (7) ◽  
pp. 985-1004 ◽  
Author(s):  
Michale McCumber ◽  
Wei-Kuo Tao ◽  
Joanne Simpson ◽  
Richard Penc ◽  
Su-Tzai Soong
Keyword(s):  
Cloud Model ◽  
Type Systems ◽  
Two Dimensions ◽  
Tropical Convection ◽  
Three Dimensions ◽  
Microphysical Properties ◽  
Cloud Models ◽  
Optimal Mix ◽  
Cloud Ice ◽  
Microphysical Parameterization

Abstract A numerical cloud model is used to evaluate the performance of several ice parameterizations. Results from simulations using these schemes are contrasted with each other, with an ice-free control simulation, and with observations to determine to what extent ice physics affect the realism of these results. Two different types of tropical convection are simulated. Tropical squall-type systems are simulated in two dimensions so that a large domain can be used to incorporate a complete anvil. Nonsquall-type convective lines are simulated in three dimensions owing to their smaller horizontal scale. The inclusion of ice processes enhances the agreement of the simulated convection with some features of observed convection, including the proportion of surface rainfall in the anvil region, and the intensity and structure of the radar brightband near the melting level in the anvil. In the context of our experimental design, the use of three ice classes produces better results than two ice classes or ice-free conditions, and for the tropical cumuli, the optimal mix of the bulk ice hydrometeors is cloud ice-snow-graupel. We infer from our modeling results that application of bulk ice microphysics in cloud models might be case specific, which is a significant limitation. This can have serious ramifications for microwave interpretation of cloud microphysical properties. Generalization of ice processes may require a larger number of ice categories than we have evaluated and/or the prediction of hydrometeor concentrations or particle-size spectra.

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