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.

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

2013 ◽  
Vol 52 (3) ◽  
pp. 682-700 ◽  
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.

scholarly journals Examining Polarimetric Radar Observations of Bulk Microphysical Structures and Their Relation to Vortex Kinematics in Hurricane Arthur (2014)

2017 ◽  
Vol 145 (11) ◽  
pp. 4521-4541 ◽  
Author(s):  
Anthony C. Didlake ◽  
Matthew R. Kumjian
Keyword(s):  
Tropical Cyclone ◽  
Lower Layer ◽  
Polarimetric Radar ◽  
Arthur Prior ◽  
Radar Observations ◽  
Melting Layer ◽  
Ice Particles ◽  
Planar Crystal ◽  
Differential Reflectivity ◽  
Left Quadrant

Dual-polarization radar observations were taken of Hurricane Arthur prior to and during landfall, providing needed insight into the microphysics of tropical cyclone precipitation. A total of 30 h of data were composited and analyzed by annuli capturing storm features (eyewall, inner rainbands, and outer rainbands) and by azimuth relative to the deep-layer environmental wind shear vector. Polarimetric radar variables displayed distinct signatures indicating a transition from convective to stratiform precipitation in the downshear-right to downshear-left quadrants, which is an organization consistent with the expected kinematic asymmetry of a sheared tropical cyclone. In the downshear-right quadrant, vertical profiles of differential reflectivity ZDR and copolar correlation coefficient ρHV were more vertically stretched within and above the melting layer at all annuli, which is attributed to convective processes. An analysis of specific differential phase KDP indicated that nonspherical ice particles had an increased presence in two layers: just above the melting level and near 8-km altitude. Here, convective updrafts generated ice particles in the lower layer, which were likely columnar crystals, and increased the available moisture in the upper layer, leading to increased planar crystal growth. A sharp transition in hydrometeor population occurred downwind in the downshear-left quadrant where ZDR and ρHV profiles were more peaked within the melting layer. Above the melting layer, these signatures indicated reduced ice column counts and shape diversity owing to aggregation in a predominantly stratiform regime. The rainband quadrants exhibited a sharper transition compared to the eyewall quadrants owing to weaker winds and longer distances that decreased azimuthal mixing of ice hydrometeors.

scholarly journals From model to radar variables: a new forward polarimetric radar operator for COSMO

2018 ◽  
Vol 11 (7) ◽  
pp. 3883-3916 ◽  
Author(s):  
Daniel Wolfensberger ◽  
Alexis Berne
Keyword(s):  
Phase Shift ◽  
Solid Phase ◽  
Weather Prediction ◽  
Doppler Spectrum ◽  
Polarimetric Radar ◽  
Dual Frequency ◽  
Differential Phase Shift ◽  
Radar Observations ◽  
Differential Phase ◽  
Differential Reflectivity

Abstract. In this work, a new forward polarimetric radar operator for the COSMO numerical weather prediction (NWP) model is proposed. This operator is able to simulate measurements of radar reflectivity at horizontal polarization, differential reflectivity as well as specific differential phase shift and Doppler variables for ground based or spaceborne radar scans from atmospheric conditions simulated by COSMO. The operator includes a new Doppler scheme, which allows estimation of the full Doppler spectrum, as well a melting scheme which allows representing the very specific polarimetric signature of melting hydrometeors. In addition, the operator is adapted to both the operational one-moment microphysical scheme of COSMO and its more advanced two-moment scheme. The parameters of the relationships between the microphysical and scattering properties of the various hydrometeors are derived either from the literature or, in the case of graupel and aggregates, from observations collected in Switzerland. The operator is evaluated by comparing the simulated fields of radar observables with observations from the Swiss operational radar network, from a high resolution X-band research radar and from the dual-frequency precipitation radar of the Global Precipitation Measurement satellite (GPM-DPR). This evaluation shows that the operator is able to simulate an accurate Doppler spectrum and accurate radial velocities as well as realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the simulated differential reflectivity and specific differential phase shift upon propagation tend to be underestimated. This radar operator makes it possible to compare directly radar observations from various sources with COSMO simulations and as such is a valuable tool to evaluate and test the microphysical parameterizations of the model.

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.

The Utility of X-Band Polarimetric Radar for Quantitative Estimates of Rainfall Parameters

2005 ◽  
Vol 6 (3) ◽  
pp. 248-262 ◽  
Author(s):  
Sergey Y. Matrosov ◽  
David E. Kingsmill ◽  
Brooks E. Martner ◽  
F. Martin Ralph
Keyword(s):  
Rain Attenuation ◽  
Polarimetric Radar ◽  
Differential Phase Shift ◽  
Differential Phase ◽  
X Band ◽  
Drop Size Distributions ◽  
Russian River ◽  
Phase Shift Data ◽  
Reflectivity Data ◽  
Differential Reflectivity

Abstract The utility of X-band polarimetric radar for quantitative retrievals of rainfall parameters is analyzed using observations collected along the U.S. west coast near the mouth of the Russian River during the Hydrometeorological Testbed project conducted by NOAA’s Environmental Technology and National Severe Storms Laboratories in December 2003 through March 2004. It is demonstrated that the rain attenuation effects in measurements of reflectivity (Ze) and differential attenuation effects in measurements of differential reflectivity (ZDR) can be efficiently corrected in near–real time using differential phase shift data. A scheme for correcting gaseous attenuation effects that are important at longer ranges is introduced. The use of polarimetric rainfall estimators that utilize specific differential phase and differential reflectivity data often provides results that are superior to estimators that use fixed reflectivity-based relations, even if these relations were derived from the ensemble of drop size distributions collected in a given geographical region. Comparisons of polarimetrically derived rainfall accumulations with data from the high-resolution rain gauges located along the coast indicated deviation between radar and gauge estimates of about 25%. The ZDR measurements corrected for differential attenuation were also used to retrieve median raindrop sizes, D0. Because of uncertainties in differential reflectivity measurements, these retrievals are typically performed only for D0 > 0.75 mm. The D0 estimates from an impact disdrometer located at 25 km from the radar were in good agreement with the radar retrievals. The experience of operating the transportable polarimetric X-band radar in the coastal area that does not have good coverage by the National Weather Service radar network showed the value of such radar in filling the gaps in the network coverage. The NOAA X-band radar was effective in covering an area up to 40–50 km in radius offshore adjacent to a region that is prone to flooding during wintertime landfalling Pacific storms.

scholarly journals Melting Layer Detection and Characterization based on Range Height Indicator–Quasi Vertical Profiles

2019 ◽  
Vol 11 (23) ◽  
pp. 2848 ◽  
Author(s):  
Shaik Allabakash ◽  
Sanghun Lim ◽  
Bong-Joo Jang
Keyword(s):  
Correlation Coefficient ◽  
Detection Algorithm ◽  
Typical Feature ◽  
Horizontal Polarization ◽  
Differential Phase Shift ◽  
Melting Layer ◽  
Surface Precipitation ◽  
Important Region ◽  
X Band ◽  
Differential Reflectivity

The melting layer (ML) is an important region used to describe the transition of hydrometeors from the solid to the liquid phase. It is a typical feature used to characterize the vertical structure of the stratiform precipitation. The present study implements a new automatic melting-layer detection algorithm based on the range-height-indicator–quasi-vertical profile (R-QVP) in the X-band dual-polarization radars. The algorithm uses the gradients of the polarimetric radar variables reflectivity factor at horizontal polarization (Zh), differential reflectivity (Zdr), and copolar correlation coefficient (ρhv), and their combinations to describe the ML characteristics. The melting layer heights derived from the radar were compared and validated with the heights of the 0 °C wet-bulb temperature derived from the Modern-Era retrospective analysis for research and applications (MERRA) reanalysis datasets and obtained high correlation coefficient 0.96. The R-QVP combined with this algorithm led to spatial and temporal variabilities of the melting layer thickness. The thickness of the melting layer was independent of the seasonal, spatial, and temporal variabilities of the precipitations. Intriguing polarimetric signatures have been observed inside, above, and below the ML, based on the phase of the precipitation particles. The statistics of the polarimetric variables were evaluated for ML, rain, and snow. Further, the linkage between enhanced specific differential phase shift (Kdp) and Zdr in the dendritic growth layer (DGL) and surface precipitation was also described.

scholarly journals Winter Precipitation Liquid–Ice Phase Transitions Revealed with Polarimetric Radar and 2DVD Observations in Central Oklahoma

2017 ◽  
Vol 56 (5) ◽  
pp. 1345-1363 ◽  
Author(s):  
Petar Bukovčić ◽  
Dušan Zrnić ◽  
Guifu Zhang
Keyword(s):  
Radar Data ◽  
Winter Precipitation ◽  
Precipitation Event ◽  
Vertical Profiles ◽  
Polarimetric Radar ◽  
Phase Precipitation ◽  
Local Enhancement ◽  
Model Simulations ◽  
Differential Reflectivity ◽  
Ice Phase

AbstractObservations and analysis of an ice–liquid phase precipitation event, collected with an S-band polarimetric KOUN radar and a two-dimensional video disdrometer (2DVD) in central Oklahoma on 20 January 2007, are presented. Using the disdrometer measurements, precipitation is classified either as ice pellets or rain/freezing rain. The disdrometer observations showed fast-falling and slow-falling particles of similar size. The vast majority (>99%) were fast falling with observed velocities close to those of raindrops with similar sizes. In contrast to the smaller particles (<1 mm in diameter), bigger ice pellets (>1.5 mm) were relatively easy to distinguish because their shapes differ from the raindrops. The ice pellets were challenging to detect by looking at conventional polarimetric radar data because of the localized and patchy nature of the ice phase and their occurrence close to the ground. Previously published findings referred to cases in which ice pellet areas were centered on the radar location and showed a ringlike structure of enhanced differential reflectivity ZDR and reduced copolar correlation coefficient ρhv and horizontal reflectivity ZH in PPI images. In this study, a new, unconventional way of looking at polarimetric radar data is introduced: slanted vertical profiles (SVPs) at low (0°–1°) radar elevations. From the analysis of the localized and patchy structures using SVPs, the polarimetric refreezing signature, reflected in local enhancement in ZDR and reduction in ZH and ρhv, became much more evident. Model simulations of sequential drop freezing using Marshall–Palmer DSDs along with the observations suggest that preferential freezing of small drops may be responsible for the refreezing polarimetric signature, as suggested in previous studies.

scholarly journals Classification of ice crystals at C-band

2009 ◽  
Vol 7 ◽  
pp. 273-277 ◽  
Author(s):  
J. Steinert ◽  
M. Chandra
Keyword(s):  
Ice Crystals ◽  
Polarimetric Radar ◽  
Ice Crystal ◽  
Melting Layer ◽  
Ice Particles ◽  
Crystal Class ◽  
The Creation ◽  
Differential Reflectivity ◽  
Backscattered Signals

Abstract. Clouds consist of water particles (hydrometeors) in different aggregate states. Above the melting layer these hydrometeors are formed mainly as ice crystals and other completely or partly frozen particles. With measurements from the C-band dual polarimetric radar POLDIRAD (Oberpfaffenhofen, Germany) the backscattered signals of the ice particles in the horizontal/vertical polarisation base were analysed. The focus is lying on the co-polar reflectivities and therefore the differential reflectivity. In the next step a simulation of the backscattered signals deliver the physical ansatz for the creation of an ice crystal class. Finally the comparison of this class with a raindrop classification is shown.

scholarly journals From model to radar variables: a new forward polarimetric radar operator for COSMO

2017 ◽  
Author(s):  
Daniel Wolfensberger ◽  
Alexis Berne
Keyword(s):  
Phase Shift ◽  
Solid Phase ◽  
Weather Prediction ◽  
Doppler Spectrum ◽  
Polarimetric Radar ◽  
Dual Frequency ◽  
Differential Phase Shift ◽  
Radar Observations ◽  
Differential Phase ◽  
Differential Reflectivity

Abstract. In this work, a new forward polarimetric radar operator for the COSMO numerical weather prediction (NWP) model is proposed. This operator is able to simulate measurements of radar reflectivity at horizontal polarization, differential reflectivity as well as specific differential phase shift and Doppler variables for ground based or spaceborne radar scans from atmospheric conditions simulated by COSMO. The operator includes a new Doppler scheme, which allows to estimate the full Doppler spectrum, as well a melting scheme which allows to represent the very specific polarimetric signature of melting hydrometeors. In addition, the operator is adapted to both the operational one-moment microphysical scheme of COSMO and its more advanced two-moment scheme. The parameters of the relationships between the microphysical and scattering properties of the various hydrometeors are derived either from the literature or, in the case of graupel and aggregates, from observations collected in Switzerland. The operator is evaluated by comparing the simulated fields of radar observables with observations from the Swiss operational radar network, from a high resolution X-band research radar and from the dual-frequency precipitation radar of the Global Precipitation Measurement satellite (GPM-DPR). This evaluation shows that the operator is able to simulate an accurate Doppler spectrum and accurate radial velocities as well as realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the simulated differential reflectivity and specific differential phase shift upon propagation tend to be underestimated. This radar operator makes it possible to compare directly radar observations from various sources with COSMO simulations and as such is a valuable tool to evaluate and test the microphysical parameterizations of the model.

scholarly journals Polarimetric Radar Characteristics of Tornadogenesis Failure in Supercell Thunderstorms

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 581
Author(s):  
Matthew Van Den Broeke
Keyword(s):  
Polarimetric Radar ◽  
Low Level ◽  
Supercell Storms ◽  
Supercell Thunderstorms ◽  
Near Term ◽  
Tornadic Storms ◽  
Differential Reflectivity

Many nontornadic supercell storms have times when they appear to be moving toward tornadogenesis, including the development of a strong low-level vortex, but never end up producing a tornado. These tornadogenesis failure (TGF) episodes can be a substantial challenge to operational meteorologists. In this study, a sample of 32 pre-tornadic and 36 pre-TGF supercells is examined in the 30 min pre-tornadogenesis or pre-TGF period to explore the feasibility of using polarimetric radar metrics to highlight storms with larger tornadogenesis potential in the near-term. Overall the results indicate few strong distinguishers of pre-tornadic storms. Differential reflectivity (ZDR) arc size and intensity were the most promising metrics examined, with ZDR arc size potentially exhibiting large enough differences between the two storm subsets to be operationally useful. Change in the radar metrics leading up to tornadogenesis or TGF did not exhibit large differences, though most findings were consistent with hypotheses based on prior findings in the literature.

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