scholarly journals Distinguishing between Warm and Stratiform Rain Using Polarimetric Radar Measurements

2021 ◽  
Vol 13 (2) ◽  
pp. 214
Author(s):  
Sergey Y. Matrosov
Keyword(s):  
Logarithmic Scale ◽  
Polarimetric Radar ◽  
Stratiform Rain ◽  
Bright Band ◽  
Warm Rain ◽  
Independent Information ◽  
Radar Measurements ◽  
The Mean ◽  
Polarimetric Weather Radar ◽  
Differential Reflectivity

Modeled statistical differential reflectivity–reflectivity (i.e., ZDR–Ze) correspondences for no bright-band warm rain and stratiform bright-band rain are evaluated using measurements from an operational polarimetric weather radar and independent information about rain types from a vertically pointing profiler. It is shown that these relations generally fit observational data satisfactorily. Due to a relative abundance of smaller drops, ZDR values for warm rain are, on average, smaller than those for stratiform rain of the same reflectivity by a factor of about two (in the logarithmic scale). A ZDR–Ze relation, representing a mean of such relations for warm and stratiform rains, can be utilized to distinguish between warm and stratiform rain types using polarimetric radar measurements. When a mean offset of observational ZDR data is accounted for and reflectivities are greater than 16 dBZ, about 70% of stratiform rains and approximately similar amounts of warm rains are classified correctly using the mean ZDR–Ze relation when applied to averaged data. Since rain rate estimators for warm rain are quite different from other common rain types, identifying and treating warm rain as a separate precipitation category can lead to better quantitative precipitation estimations.

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

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.

scholarly journals A Variational Approach for Retrieving Raindrop Size Distribution from Polarimetric Radar Measurements in the Presence of Attenuation

2013 ◽  
Vol 52 (1) ◽  
pp. 169-185 ◽  
Author(s):  
Qing Cao ◽  
Guifu Zhang ◽  
Ming Xue
Keyword(s):  
Variational Approach ◽  
Simulated Data ◽  
Real Data ◽  
Radar Data ◽  
Polarimetric Radar ◽  
University Of Oklahoma ◽  
Raindrop Size Distribution ◽  
Radar Measurements ◽  
Raindrop Size ◽  
Differential Reflectivity

AbstractThis study presents a two-dimensional variational approach to retrieving raindrop size distributions (DSDs) from polarimetric radar data in the presence of attenuation. A two-parameter DSD model, the constrained-gamma model, is used to represent rain DSDs. Three polarimetric radar measurements—reflectivity ZH, differential reflectivity ZDR, and specific differential phase KDP—are optimally used to correct for the attenuation and retrieve DSDs by taking into account measurement error effects. Retrieval results with simulated data demonstrate that the proposed algorithm performs well. Applications to real data collected by the X-band Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radars and the C-band University of Oklahoma–Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) also demonstrate the efficacy of this approach.

On the Influence of Assumed Drop Size Distribution Form on Radar-Retrieved Thunderstorm Microphysics

2006 ◽  
Vol 45 (2) ◽  
pp. 259-268 ◽  
Author(s):  
Edward A. Brandes ◽  
Guifu Zhang ◽  
Juanzhen Sun
Keyword(s):  
Drop Size ◽  
Liquid Water Content ◽  
Polarimetric Radar ◽  
Stratiform Rain ◽  
Distribution Form ◽  
Median Volume ◽  
Strong Convection ◽  
Radar Measurements ◽  
Size Model ◽  
Drop Size Distributions

Abstract Polarimetric radar measurements are used to retrieve drop size distributions (DSD) in subtropical thunderstorms. Retrievals are made with the single-moment exponential drop size model of Marshall and Palmer driven by radar reflectivity measurements and with a two-parameter constrained-gamma drop size model that utilizes reflectivity and differential reflectivity. Results are compared with disdrometer observations. Retrievals with the constrained-gamma DSD model gave better representation of total drop concentration, liquid water content, and drop median volume diameter and better described their natural variability. The Marshall–Palmer DSD model, with a fixed intercept parameter, tended to underestimate the total drop concentration in storm cores and to overestimate significantly the concentration in stratiform regions. Rainwater contents in strong convection were underestimated by a factor of 2–3, and drop median volume diameters in stratiform rain were underestimated by 0.5 mm. To determine possible DSD model impacts on numerical forecasts, evaporation and accretion rates were computed using Kessler-type parameterizations. Rates based on the Marshall–Palmer DSD model were lower by a factor of 2–3 in strong convection and were higher by about a factor of 2 in stratiform rain than those based on the constrained-gamma model. The study demonstrates the potential of polarimetric radar measurements for improving the understanding of precipitation processes and microphysics parameterization in numerical forecast models.

scholarly journals Can a Unique Model Describe the Raindrop Shape–Size Relation? A Clue from Polarimetric Radar Measurements

2009 ◽  
Vol 26 (9) ◽  
pp. 1829-1842 ◽  
Author(s):  
Eugenio Gorgucci ◽  
V. Chandrasekar ◽  
Luca Baldini
Keyword(s):  
Axial Ratio ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Drop Shape ◽  
Climatic Regions ◽  
Unique Shape ◽  
Initial Drop ◽  
Radar Measurements ◽  
Differential Reflectivity ◽  
Size Relation

Abstract A method is proposed to retrieve raindrop shape–size relations from the radar measurements of reflectivity factor Zh, differential reflectivity Zdr, and specific differential phase Kdp at S band. This procedure is obtained using a domain defined by the two variables Kdp/Zh and Zdr where the drop size distribution (DSD) variability is collapsed onto a line and any variation is essentially due to the drop shape variability. To obtain information on the raindrop shape–size relation underlying a set of radar observations, this domain is studied in conjunction with another domain describing the relation between the drop axial ratio (or shape) and its equivolumetric diameter. Using an initial drop shape and choosing a set of DSDs described by a normalized gamma model, polarimetric radar measurements are produced by simulation. An averaged curve of Kdp/Zh versus Zdr is obtained and compared with the same curve obtained from the radar data. By changing the initial axial ratio relation, a procedure of minimization between the two curves is developed to derive the underlying drop shape–size relation governing the radar measurements under consideration. Three sets of radar data collected in different climatic regions are analyzed to evaluate whether there is a unique shape–size relation.

scholarly journals Hydrometeor Shape Variability in Snowfall as Retrieved from Polarimetric Radar Measurements

2020 ◽  
Vol 59 (9) ◽  
pp. 1503-1517
Author(s):  
Sergey Y. Matrosov ◽  
Alexander V. Ryzhkov ◽  
Maximilian Maahn ◽  
Gijs de Boer
Keyword(s):  
Aspect Ratio ◽  
Doppler Radar ◽  
Particle Model ◽  
Polarimetric Radar ◽  
Aspect Ratios ◽  
Air Temperatures ◽  
Radar Measurements ◽  
Differential Reflectivity ◽  
Particle Shapes

AbstractA polarimetric radar–based method for retrieving atmospheric ice particle shapes is applied to snowfall measurements by a scanning Ka-band radar deployed at Oliktok Point, Alaska (70.495°N, 149.883°W). The mean aspect ratio, which is defined by the hydrometeor minor-to-major dimension ratio for a spheroidal particle model, is retrieved as a particle shape parameter. The radar variables used for aspect ratio profile retrievals include reflectivity, differential reflectivity, and the copolar correlation coefficient. The retrievals indicate that hydrometeors with mean aspect ratios below 0.2–0.3 are usually present in regions with air temperatures warmer than approximately from −17° to −15°C, corresponding to a regime that has been shown to be favorable for growth of pristine ice crystals of planar habits. Radar reflectivities corresponding to the lowest mean aspect ratios are generally between −10 and 10 dBZ. For colder temperatures, mean aspect ratios are typically in a range between 0.3 and 0.8. There is a tendency for hydrometeor aspect ratios to increase as particles transition from altitudes in the temperature range from −17° to −15°C toward the ground. This increase is believed to result from aggregation and riming processes that cause particles to become more spherical and is associated with areas demonstrating differential reflectivity decreases with increasing reflectivity. Aspect ratio retrievals at the lowest altitudes are consistent with in situ measurements obtained using a surface-based multiangle snowflake camera. Pronounced gradients in particle aspect ratio profiles are observed at altitudes at which there is a change in the dominant hydrometeor species, as inferred by spectral measurements from a vertically pointing Doppler radar.

scholarly journals The Impact of Raindrop Collisional Processes on the Polarimetric Radar Variables

2014 ◽  
Vol 71 (8) ◽  
pp. 3052-3067 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Olivier P. Prat
Keyword(s):  
Electromagnetic Scattering ◽  
Vertical Profiles ◽  
Polarimetric Radar ◽  
Horizontal Polarization ◽  
One Dimensional ◽  
Microphysical Process ◽  
Warm Rain ◽  
Microphysical Processes ◽  
Differential Reflectivity ◽  
The Impact

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.

Shipborne Polarimetric Weather Radar: Impact of Ship Movement on Polarimetric Variables at C Band

2014 ◽  
Vol 31 (7) ◽  
pp. 1557-1563 ◽  
Author(s):  
M. Thurai ◽  
P. T. May ◽  
A. Protat
Keyword(s):  
Drop Size ◽  
Size Distributions ◽  
Correction Factors ◽  
Distribution Parameters ◽  
Radar Measurements ◽  
Nonzero Mean ◽  
Polarimetric Weather Radar ◽  
Drop Size Distributions ◽  
Differential Reflectivity ◽  
Ship Movement

Abstract The effect of ship motion on shipborne polarimetric radar measurements is considered at C band. Calculations are carried out by (i) varying the “effective” mean canting angle and (ii) separately examining the elevation dependence. Scattering from a single oblate hydrometeor is considered at first. Equations are derived (i) to convert the measured differential reflectivity for nonzero mean canting angles to those for zero mean canting angle and (ii) to do the corresponding corrections for nonzero elevation angles. Scattering calculations are also performed using the T-matrix method with measured drop size distributions as input. Dependence on mean volume diameter is examined as well as variations of the four main polarimetric parameters. The results show that as long as the ship movement is limited to a roll of less than about 10°–15°, the effects are tolerable. Furthermore, the results from the scattering simulations have been used to provide equations for correction factors that can be applied to compensate for the “apparent” nonzero canting angles and nonzero elevation angles, so that drop size distribution parameters and rainfall rates can be estimated without any bias.

scholarly journals Detection of the melting level with polarimetric weather radar

2021 ◽  
Vol 14 (4) ◽  
pp. 2873-2890
Author(s):  
Daniel Sanchez-Rivas ◽  
Miguel A. Rico-Ramirez
Keyword(s):  
Weather Radar ◽  
Radiosonde Data ◽  
Accurate Estimation ◽  
Vertical Profiles ◽  
Polarimetric Radar ◽  
Radar Rainfall ◽  
Radar Measurements ◽  
Polarimetric Weather Radar ◽  
Melting Level ◽  
Ml Detection

Abstract. Accurate estimation of the melting level (ML) is essential in radar rainfall estimation to mitigate the bright band enhancement, classify hydrometeors, correct for rain attenuation and calibrate radar measurements. This paper presents a novel and robust ML-detection algorithm based on either vertical profiles (VPs) or quasi-vertical profiles (QVPs) built from operational polarimetric weather radar scans. The algorithm depends only on data collected by the radar itself, and it is based on the combination of several polarimetric radar measurements to generate an enhanced profile with strong gradients related to the melting layer. The algorithm is applied to 1 year of rainfall events that occurred over southeast England, and the results were validated using radiosonde data. After evaluating all possible combinations of polarimetric radar measurements, the algorithm achieves the best ML detection when combining VPs of ZH, ρHV and the gradient of the velocity (gradV), whereas, for QVPs, combining profiles of ZH, ρHV and ZDR produces the best results, regardless of the type of rain event. The root mean square error in the ML detection compared to radiosonde data is ∼200 m when using VPs and ∼250 m when using QVPs.

scholarly journals Estimation of Melting-Layer Cooling Rate from Dual-Polarization Radar: Spectral Bin Model Simulations

2019 ◽  
Vol 58 (7) ◽  
pp. 1485-1508 ◽  
Author(s):  
Jacob T. Carlin ◽  
Alexander V. Ryzhkov
Keyword(s):  
Cooling Rate ◽  
Phase Changes ◽  
Strongly Correlated ◽  
Polarimetric Radar ◽  
Differential Phase Shift ◽  
Model Simulations ◽  
Melting Snow ◽  
Melting Layer ◽  
Bright Band ◽  
Differential Reflectivity

AbstractDiabatic cooling from hydrometeor phase changes in the stratiform melting layer is of great interest to both operational forecasters and modelers for its societal and dynamical consequences. Attempts to estimate the melting-layer cooling rate typically rely on either the budgeting of hydrometeor content estimated from reflectivity Z or model-generated lookup tables scaled by the magnitude of Z in the bright band. Recent advances have been made in developing methods to observe the unique polarimetric characteristics of melting snow and the additional microphysical information they may contain. However, to date no work has looked at the thermodynamic information available from the polarimetric radar brightband signature. In this study, a one-dimensional spectral bin model of melting snow and a coupled polarimetric operator are used to study the relation between the polarimetric radar bright band and the melting-layer cooling rate. Simulations using a fixed particle size distribution (PSD) and variable environmental conditions show that the height and thickness of the bright band and the maximum brightband Z and specific differential phase shift are all sensitive to the ambient environment, while the differential reflectivity is relatively insensitive. Additional simulations of 2700 PSDs based on in situ observations above the melting layer indicate that the maximum Z, , and within the melting layer are poorly correlated with the maximum cooling rate while is strongly correlated. Finally, model simulations suggest that, in addition to riming, concurrent changes in aggregation and precipitation intensity and the associated cooling may plausibly cause observed sagging brightband signatures.

Influence of Ground Clutter Contamination on Polarimetric Radar Parameters

2009 ◽  
Vol 26 (2) ◽  
pp. 251-269 ◽  
Author(s):  
Katja Friedrich ◽  
Urs Germann ◽  
Pierre Tabary
Keyword(s):  
Reference Data ◽  
Critical Level ◽  
Elevation Angle ◽  
Convective Precipitation ◽  
Polarimetric Radar ◽  
Mountain Ranges ◽  
Ground Clutter ◽  
The Mean ◽  
Rain Events ◽  
Differential Reflectivity

Abstract The influence of ground clutter contamination on the estimation of polarimetric radar parameters, horizontal reflectivity (Zh), differential reflectivity (Zdr), correlation coefficient (ρhυ), and differential propagation phase (ϕdp) was examined. This study aims to derive the critical level of ground clutter contamination for Zh, Zdr, ρhυ, and ϕdp at which ground clutter influence exceeds predefined precision thresholds. Reference data with minimal ground clutter contamination consist of eight precipitation fields measured during three rain events characterized by stratiform and convective precipitation. Data were collected at an elevation angle of 0.8° by the Météo-France operational, polarimetric Doppler C-band weather radar located in Trappes, France, ∼30 km southwest of Paris. Nine different ground clutter signatures, ranging from point targets to more complex signatures typical for mountain ranges or urban obstacles, were added to the precipitation fields. This is done at the level of raw in-phase and quadrature component data in the two polarimetric channels. For each ground clutter signature, 30 simulations were conducted in which the mean reflectivity of ground clutter within the resolution volume varied between being 30 dB higher to 30 dB lower than the mean reflectivity of precipitation. Differences in Zh, Zdr, ρυ, and ϕdp between simulation and reference were shown as a function of ratio between ground clutter and precipitation intensities. As a result of this study, horizontal reflectivity showed the lowest sensitivity to ground clutter contamination. Furthermore, a precision of 1.7 dBZ in Zh is achieved on average when the precipitation and ground clutter intensities are equal. Requiring a precision of 0.2 dB in Zdr and 3° in ϕdp, the reflectivity of precipitation needs to be on average ∼5.5 and ∼6 dB, respectively, higher compared to the reflectivity of ground clutter. The analysis also indicates that the highest sensitivity to the nine clutter signatures was derived for ρhυ. To meet a predefined precision threshold of 0.02, reflectivity of precipitation needs to be ∼13.5 dB higher than the reflectivity of ground clutter.

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