The Impact of Raindrop Collisional Processes on the Polarimetric Radar Variables

Abstract The impact of the collisional warm-rain microphysical processes on the polarimetric radar variables is quantified using a coupled microphysics–electromagnetic scattering model. A one-dimensional bin-microphysical rain shaft model that resolves explicitly the evolution of the drop size distribution (DSD) under the influence of collisional coalescence and breakup, drop settling, and aerodynamic breakup is coupled with electromagnetic scattering calculations that simulate vertical profiles of the polarimetric radar variables: reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, and specific differential phase KDP. The polarimetric radar fingerprint of each individual microphysical process is quantified as a function of the shape of the initial DSD and for different values of nominal rainfall rate. Results indicate that individual microphysical processes (collisional processes, evaporation) display a distinctive signature and evolve within specific areas of ZH–ZDR and ZDR–KDP space. Furthermore, a comparison of the resulting simulated vertical profiles of the polarimetric variables with radar and disdrometer observations suggests that bin-microphysical parameterizations of drop breakup most frequently used are overly aggressive for the largest rainfall rates, resulting in very “tropical” DSDs heavily skewed toward smaller drops.

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Polarimetric Signatures above the Melting Layer in Winter Storms: An Observational and Modeling Study

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-028.1 ◽

2013 ◽

Vol 52 (3) ◽

pp. 682-700 ◽

Cited By ~ 82

Author(s):

Jelena Andrić ◽

Matthew R. Kumjian ◽

Dušan S. Zrnić ◽

Jerry M. Straka ◽

Valery M. Melnikov

Keyword(s):

Electromagnetic Scattering ◽

Vertical Profiles ◽

Polarimetric Radar ◽

Winter Storm ◽

Differential Phase Shift ◽

Winter Storms ◽

One Dimensional ◽

Melting Layer ◽

Differential Reflectivity ◽

General Profile

AbstractPolarimetric radar observations above the melting layer in winter storms reveal enhanced differential reflectivity ZDR and specific differential phase shift KDP, collocated with reduced copolar correlation coefficient ρhv; these signatures often appear as isolated “pockets.” High-resolution RHIs and vertical profiles of polarimetric variables were analyzed for a winter storm that occurred in Oklahoma on 27 January 2009, observed with the polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman. The ZDR maximum and ρhv minimum are located within the temperature range between −10° and −15°C, whereas the KDP maximum is located just below the ZDR maximum. These signatures are coincident with reflectivity factor ZH that increases toward the ground. A simple kinematical, one-dimensional, two-moment bulk microphysical model is developed and coupled with electromagnetic scattering calculations to explain the nature of the observed polarimetric signature. The microphysics model includes nucleation, deposition, and aggregation and considers only ice-phase hydrometeors. Vertical profiles of the polarimetric radar variables (ZH, ZDR, KDP, and ρhv) were calculated using the output from the microphysical model. The base model run reproduces the general profile and magnitude of the observed ZH and ρhv and the correct shape (but not magnitude) of ZDR and KDP. Several sensitivity experiments were conducted to determine if the modeled signatures of all variables can match the observed ones. The model was incapable of matching both the observed magnitude and shape of all polarimetric variables, however. This implies that some processes not included in the model (such as secondary ice generation) are important in producing the signature.

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Microphysical and Polarimetric Radar Modeling of Hydrometeor Refreezing

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-20-0314.1 ◽

2021 ◽

Author(s):

Dana M. Tobin ◽

Matthew R. Kumjian

Keyword(s):

Polarimetric Radar ◽

Horizontal Polarization ◽

Radar Signature ◽

Liquid Portion ◽

Linear Depolarization Ratio ◽

Bin Microphysics ◽

Ice Shell ◽

Differential Reflectivity ◽

The Impact ◽

Polar Correlation

AbstractA unique polarimetric radar signature indicative of hydrometeor refreezing during ice pellet events has been documented in several recent studies, yet the underlying microphysical causes remain unknown. The signature is characterized by enhancements in differential reflectivity (ZDR), specific differential phase (KDP), and linear depolarization ratio (LDR), and a reduction in co-polar correlation coefficient (ρhv) within a layer of decreasing radar reflectivity factor at horizontal polarization (ZH). In previous studies, the leading hypothesis for the observed radar signature is the preferential refreezing of small drops. Here, a simplified, one-dimensional, explicit bin microphysics model is developed to simulate the refreezing of fully melted hydrometeors, and coupled with a polarimetric radar forward operator to quantify the impact of preferential refreezing on simulated radar signatures. The modeling results demonstrate that preferential refreezing is insufficient by itself to produce the observed signatures. In contrast, simulations considering an ice shell growing asymmetrically around a freezing particle (i.e., emulating a thicker ice shell on the bottom of a falling particle) produce realistic ZDR enhancements, and also closely replicate observed features in ZH, KDP, LDR, and ρhv. Simulations that assume no increase in particle wobbling with freezing produce an even greater ZDR enhancement, but this comes at the expense of reducing the LDR enhancement. It is suggested that the polarimetric refreezing signature is instead strongly related to both the distribution of the unfrozen liquid portion within a freezing particle, and the orientation of this liquid with respect to the horizontal.

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The Impact of Evaporation on Polarimetric Characteristics of Rain: Theoretical Model and Practical Implications

Journal of Applied Meteorology and Climatology ◽

10.1175/2010jamc2243.1 ◽

2010 ◽

Vol 49 (6) ◽

pp. 1247-1267 ◽

Cited By ~ 53

Author(s):

Matthew R. Kumjian ◽

Alexander V. Ryzhkov

Keyword(s):

Polarimetric Radar ◽

Simple Method ◽

Initial Shape ◽

Mountainous Regions ◽

Precipitation Estimates ◽

Microphysical Processes ◽

Bin Microphysics ◽

Quantitative Precipitation Estimates ◽

Differential Reflectivity ◽

The Impact

Abstract Soon, the National Weather Service’s Weather Surveillance Radar-1988 Doppler (WSR-88D) network will be upgraded to allow dual-polarization capabilities. Therefore, it is imperative to understand and identify microphysical processes using the polarimetric variables. Though melting and size sorting of hydrometeors have been investigated, there has been relatively little focus devoted to the impacts of evaporation on the polarimetric characteristics of rainfall. In this study, a simple explicit bin microphysics one-dimensional rainshaft model is constructed to quantify the impacts of evaporation (neglecting the collisional processes) on vertical profiles of polarimetric radar variables in rain. The results of this model are applicable for light to moderate rain (<10 mm h−1). The modeling results indicate that the amount of evaporation that occurs in the subcloud layer is strongly dependent on the initial shape of the drop size distribution aloft, which can be assessed with polarimetric measurements. Understanding how radar-estimated rainfall rates may change in height due to evaporation is important for quantitative precipitation estimates, especially in regions far from the radar or in regions of complex terrain where low levels may not be adequately sampled. In addition to quantifying the effects of evaporation, a simple method of estimating the amount of evaporation that occurs in a given environment based on polarimetric radar measurements of the reflectivity factor ZH and differential reflectivity ZDR aloft is offered. Such a technique may be useful to operational meteorologists and hydrologists in estimating the amount of precipitation reaching the surface, especially in regions of poor low-level radar coverage such as mountainous regions or locations at large distances from the radar.

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Freezing of Raindrops in Deep Convective Updrafts: A Microphysical and Polarimetric Model

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-12-067.1 ◽

2012 ◽

Vol 69 (12) ◽

pp. 3471-3490 ◽

Cited By ~ 49

Author(s):

Matthew R. Kumjian ◽

Scott M. Ganson ◽

Alexander V. Ryzhkov

Keyword(s):

Electromagnetic Scattering ◽

Drop Size ◽

Sharp Decrease ◽

Supercooled Liquid ◽

Freezing Process ◽

Polarimetric Radar ◽

Linear Depolarization Ratio ◽

Bin Microphysics ◽

Differential Reflectivity ◽

The Impact

Abstract Polarimetric radar observations of convective storms routinely reveal positive differential reflectivity ZDR extending above the 0°C level, indicative of the presence of supercooled liquid particles lofted by the storm’s updraft. The summit of such “ZDR columns” is marked by a zone of enhanced linear depolarization ratio LDR or decreased copolar cross-correlation coefficient ρhv and a sharp decrease in ZDR that together mark a particle freezing zone. To better understand the relation between changes in the storm updraft and the observed polarimetric variables, it is necessary to first understand the physics governing this freezing process and the impact of freezing on the polarimetric variables. A simplified, one-dimensional explicit bin microphysics model of stochastic drop nucleation by an immersed foreign particle and subsequent deterministic freezing is developed and coupled with an electromagnetic scattering model to explore the impact of the freezing process on the polarimetric radar variables. As expected, the height of the ZDR column is closely related to the updraft strength and initial drop size distribution. Additionally, the treatment of the stochastic nucleation process can also affect the depth of the freezing zone, underscoring the need to accurately depict this process in parameterizations. Representation of stochastic nucleation and deterministic freezing for each drop size bin yields better agreement between observations and the modeled vertical profiles of the surface reflectivity factor ZH and ZDR than bulk microphysics schemes. Further improvements in the representation of the LDR cap, the observed ZDR gradient in the freezing zone, and the magnitude of the ρhv minimum may require inclusion of accretion, which was not included in this model.

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A Polarimetric Radar Analysis of Ice Microphysical Processes in Melting Layers of Winter Storms Using S-Band Quasi-Vertical Profiles

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-19-0128.1 ◽

2020 ◽

Vol 59 (4) ◽

pp. 751-767 ◽

Cited By ~ 2

Author(s):

Erica M. Griffin ◽

Terry J. Schuur ◽

Alexander V. Ryzhkov

Keyword(s):

Cold Season ◽

Vertical Profiles ◽

Horizontal Polarization ◽

Winter Storms ◽

Differential Phase ◽

High Vertical Resolution ◽

Microphysical Processes ◽

Statistical Relationships ◽

Reflectivity Data ◽

Differential Reflectivity

AbstractQuasi-vertical profiles (QVPs) obtained from a database of U.S. WSR-88D data are used to document polarimetric characteristics of the melting layer (ML) in cold-season storms with high vertical resolution and accuracy. A polarimetric technique to define the top and bottom of the ML is first introduced. Using the QVPs, statistical relationships are developed to gain insight into the evolution of microphysical processes above, within, and below the ML, leading to a statistical polarimetric model of the ML that reveals characteristics that reflectivity data alone are not able to provide, particularly in regions of weak reflectivity factor at horizontal polarization ZH. QVP ML statistics are examined for two regimes in the ML data: ZH ≥ 20 dBZ and ZH < 20 dBZ. Regions of ZH ≥ 20 dBZ indicate locations of MLs collocated with enhanced differential reflectivity ZDR and reduced copolar correlation coefficient ρhv, while for ZH < 20 dBZ a well-defined ML is difficult to discern using ZH alone. Evidence of large ZDR up to 4 dB, backscatter differential phase δ up to 8°, and low ρhv down to 0.80 associated with lower ZH (from −10 to 20 dBZ) in the ML is observed when pristine, nonaggregated ice falls through it. Positive correlation is documented between maximum specific differential phase KDP and maximum ZH in the ML; these are the first QVP observations of KDP in MLs documented at S band. Negative correlation occurs between minimum ρhv in the ML and ML depth and between minimum ρhv in the ML and the corresponding enhancement of ZH (ΔZH = ZHmax − ZHrain).

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Polarimetric Radar Signatures of Dendritic Growth Zones within Colorado Winter Storms

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-15-0004.1 ◽

2015 ◽

Vol 54 (12) ◽

pp. 2365-2388 ◽

Cited By ~ 31

Author(s):

Robert S. Schrom ◽

Matthew R. Kumjian ◽

Yinghui Lu

Keyword(s):

Electromagnetic Scattering ◽

Polarimetric Radar ◽

Front Range ◽

Horizontal Polarization ◽

Winter Storms ◽

Radar Observations ◽

Colorado State University ◽

Radar Signature ◽

Radar Signatures ◽

Differential Reflectivity

AbstractX-band polarimetric radar observations of winter storms in northeastern Colorado on 20–21 February, 9 March, and 9 April 2013 are examined. These observations were taken by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU-CHILL) radar during the Front Range Orographic Storms (FROST) project. The polarimetric radar moments of reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, and specific differential phase KDP exhibited a range of signatures at different times near the −15°C temperature level favored for dendritic ice crystal growth. In general, KDP was enhanced in these regions with ZDR decreasing and ZH increasing toward the ground, suggestive of aggregation (or riming). The largest ZDR values (~3.5–5.5 dB) were observed during periods of significant low-level upslope flow. Convective features observed when the upslope flow was weaker had the highest KDP (>1.5° km−1) and ZH (>20 dBZ) values. Electromagnetic scattering calculations using the generalized multiparticle Mie method were used to determine whether these radar signatures were consistent with dendrites. Particle size distributions (PSDs) of dendrites were retrieved for a variety of cases using these scattering calculations and the radar observations. The PSDs derived using stratiform precipitation observations were found to be reasonably consistent with previous PSD observations. PSDs derived where riming may have occurred likely had errors and deviated significantly from these previous PSD observations. These results suggest that this polarimetric radar signature may therefore be useful in identifying regions of rapidly collecting dendrites, after considering the effects of riming on the radar variables.

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

Atmosphere ◽

10.3390/atmos11040362 ◽

2020 ◽

Vol 11 (4) ◽

pp. 362 ◽

Cited By ~ 1

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.

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Comparisons of Electromagnetic Scattering Properties of Real Hailstones and Spheroids

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-17-0344.1 ◽

2019 ◽

Vol 58 (1) ◽

pp. 93-112 ◽

Cited By ~ 6

Author(s):

Zhiyuan Jiang ◽

Matthew R. Kumjian ◽

Robert S. Schrom ◽

Ian Giammanco ◽

Tanya Brown-Giammanco ◽

...

Keyword(s):

Electromagnetic Scattering ◽

3D Structure ◽

Laser Scanner ◽

The United States ◽

Dipole Approximation ◽

Horizontal Polarization ◽

Differential Phase ◽

Irregular Shapes ◽

Linear Depolarization Ratio ◽

Differential Reflectivity

AbstractSevere (>2.5 cm) hail causes >$5 billion in damage annually in the United States. However, radar sizing of hail remains challenging. Typically, spheroids are used to represent hailstones in radar forward operators and to inform radar hail-sizing algorithms. However, natural hailstones can have irregular shapes and lobes; these details significantly influence the hailstone’s scattering properties. The high-resolution 3D structure of real hailstones was obtained using a laser scanner for hail collected during the 2016–17 Insurance Institute for Business and Home Safety (IBHS) Hail Field Study. Plaster casts of several record hailstones (e.g., Vivian, South Dakota, 2010) were also scanned. The S-band scattering properties of these hailstones were calculated with the discrete dipole approximation (DDA). For comparison, scattering properties of spheroidal approximations of each hailstone (with identical maximum and minimum dimensions and mass) were calculated with the T matrix. The polarimetric radar variables have errors when using spheroids, even for small hail. Spheroids generally have smaller variations in the polarimetric variables than the real hailstones. This increased variability is one reason why the correlation coefficient tends to be lower in observations than in forward-simulated cases using spheroids. Backscatter differential phase δ also is found to have large variance, particularly for large hailstones. Irregular hailstones with a thin liquid layer produce enhanced and more variable values for reflectivity factor at horizontal polarization ZHH, differential reflectivity ZDR, specific differential phase KDP, linear depolarization ratio (LDR), and δ compared with dry hailstones; is also significantly reduced.

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Characteristics of the Bright Band Based on Quasi-Vertical Profiles of Polarimetric Observations from an S-Band Weather Radar Network

Remote Sensing ◽

10.3390/rs12244061 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4061

Author(s):

Jeong-Eun Lee ◽

Sung-Hwa Jung ◽

Soohyun Kwon

Keyword(s):

Signal To Noise Ratio ◽

Vertical Profiles ◽

Bright Band ◽

Weather Radars ◽

Radar Network ◽

Temperature Zero ◽

The Mean ◽

Microphysical Processes ◽

Differential Reflectivity ◽

Self Consistency

Bright band (BB) characteristics obtained via dual-polarization weather radars elucidate thermodynamic and microphysical processes within precipitation systems. This study identified BB using morphological features from quasi-vertical profiles (QVPs) of polarimetric observations, and their geometric, thermodynamic, and polarimetric characteristics were statistically examined using nine operational S-band weather radars in South Korea. For comparable analysis among weather radars in the network, the calibration biases in reflectivity (ZH) and differential reflectivity (ZDR) were corrected based on self-consistency. The cross-correlation coefficient (ρHV) bias in the weak echo regions was corrected using the signal-to-noise ratio (SNR). First, we analyzed the heights of BBPEAK derived from the ZH as a function of season and compared the heights of BBPEAK derived from the ZH, ZDR, and ρHV. The heights of BBPEAK were highest in the summer season when the surface temperature was high. However, they showed distinct differences depending on the location (e.g., latitude) within the radar network, even in the same season. The height where the size of melting particles was at a maximum (BBPEAK from the ZH) was above that where the oblateness of these particles maximized (BBPEAK from ZDR). The height at which the inhomogeneity of hydometeors was at maximum (BBPEAK from the ρHV) was also below that of BBPEAK from the ZH. Second, BB thickness and relative position of BBPEAK were investigated to characterize the geometric structure of the BBs. The BB thickness increased as the ZH at BBBOTTOM increased, which indicated that large snowflakes melt more slowly than small snowflakes. The geometrical structure of the BBs was asymmetric, since the melting particles spent more time forming the thin shell of meltwater around them, and they rapidly collapsed to form a raindrop at the final stage of melting. Third, the heights of BBTOP, BBPEAK, and BBBOTTOM were compared with the zero-isotherm heights. The dry-temperature zero-isotherm heights were between BBTOP and BBBOTTOM, while the wet-bulb temperature zero-isotherm heights were close to the height of BBPEAK. Finally, we examined the polarimetric observations to understand the involved microphysical processes. The correlation among ZH at BBTOP, BBPEAK, and BBBOTTOM was high (>0.94), and the ZDR at BBBOTTOM was high when the BB’s intensity was strong. This proved that the size and concentration of snowflakes above the BB influence the size and concentration of raindrops below the BB. There was no depression in the ρHV for a weak BB. Finally, the mean profile of the ZH and ZDR depended on the ZH at BBBOTTOM. In conclusion, the growth process of snowflakes above the BB controls polarimetric observations of BB.

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Automatic identification of the dominant microphysical processes in snowfall over the Antarctic coast using polarimetric radar observations

10.5194/egusphere-egu2020-21653 ◽

2020 ◽

Author(s):

Noémie Planat ◽

Josué Gehring ◽

Etienne Vignon ◽

Alexis Berne

Keyword(s):

Vapor Deposition ◽

Radar Signal ◽

Polar Regions ◽

Atmospheric Models ◽

Altitudinal Distribution ◽

Microphysical Process ◽

Microphysical Processes ◽

Differential Reflectivity ◽

The Antarctic ◽

Expected Increase

Microphysical processes in cold precipitating clouds are not fully understood and their parametrization in atmospheric models remains challenging&#160;. In particular the lack of evaluation and validation of the microphysical parameterizations in polar regions questions the reliability of the ice sheet surface mass balance assessments. Recently, strong&#160;discrepancies have been found in the precipitation structure between simulations with different microphysical parameterizations over the Antarctic coast.The dissimilarities between simulations seem to be due to different treatments of the riming, aggregation and sublimation processes.&#160;Evaluating the representation of a particular microphysical process in a model is delicate, especially because it is difficult to obtain in situ estimations, even qualitative, of a given microphysical process. In this study, we developed a method to identify&#160;the&#160;regions in radar scans where either aggregation and riming, vapor deposition or sublimation are the dominant microphysical processes.This method is based on the vertical (downward) gradients of reflectivity and differential reflectivity computed over columns extracted from range height indicator scans. Because of the expected increase in size and decrease in oblateness of the particles, aggregation and riming are identified as regions with positive gradients of reflectivity and negative gradients of differential reflectivity. Because of the expected increase in size and oblateness, vapor deposition is identified as regions with positive gradients of reflectivity and positive gradients of differential reflectivity. Because of the expected decrease in size and in concentration, snowflake sublimation, and possibly snowflake breakup, are defined as regions with negative gradients of reflectivity.&#160;The method was employed on two frontal precipitation events, which took place during the austral summer APRES3 campaign (2015-2016) in Dumont d&#8217;Urville (DDU) station, Antarctic coast. Significant differences appear&#160;in&#160;the mean altitudinal distribution where each process takes place.&#160;Given that the radar signal extends up to 4500 m a.g.l., we could show that crystal growth dominates around 2800 m while aggregation and riming prevail around 1500 m. Sublimation mostly occurs below 900 m, concurring with previous studies stating that snowflakes preferentially sublimate in the relatively dry katabatic boundary layer.Moreover the&#160;statistical&#160;distributions of different radar variables provides quantitative information to further characterize the microphysical processes of interest.This method could be further used to assess the ability of atmospheric models to reproduce the correct microphysical processes at the correct locations.

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