scholarly journals Retrieval of Snow Properties for Ku- and Ka-Band Dual-Frequency Radar

2016 ◽  
Vol 55 (9) ◽  
pp. 1845-1858 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini ◽  
Ali Tokay ◽  
Larry F. Bliven
Keyword(s):  
Water Content ◽  
Full Range ◽  
Sensitivity Study ◽  
Dual Wavelength ◽  
Particle Sizes ◽  
Dual Frequency ◽  
Fall Velocity ◽  
Ka Band ◽  
Scattering Model ◽  
Snow Water

AbstractThe focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro-/macrophysical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow-scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager/Particle Image Probe (SVI/PIP) during the winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia.

Assessment of Ku- and Ka-band Dual-Frequency Radar for Snow Estimates

2020 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini ◽  
Ali Tokay ◽  
Hyokyung Kim
Keyword(s):  
Growth Models ◽  
Complex Nature ◽  
Dual Frequency ◽  
Fall Velocity ◽  
Ka Band ◽  
Scattering Model ◽  
Retrieval Accuracy ◽  
Mass Size ◽  
Bulk Parameters ◽  
Size Relation

<p>Dual-frequency radars have been increasingly used for detecting and retrieving cloud and precipitation, such as the Ku- and Ka-band Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) core satellite. The objective of this study is to evaluate performance of the standard dual-frequency technique, which uses the differential frequency ratio (DFR), defined as the difference of radar reflectivities between two wavelengths, for the estimation of snow microphysical properties and the associated bulk parameters from Ku- and Ka-band as well as Ka- and W-band dual-frequency radars. Although the DFR-based technique is effective in obtaining snow properties, its retrieval accuracy depends on the model assumptions, which include parameterization of particle size distribution (PSD), empirical mass-size relation that links the observed geometrical size of particle to its mass, and the radar scattering model. The complex nature of snowflakes regarding shape, structure, and the inability of the modeled PSD to represent actual snow spectra, lead to errors in the estimates of snow parameters. Additionally, uncertainties associated with scattering computations of snowflakes also affect the accuracy of the dual-wavelength radar retrieval of snow. Therefore, understanding the uncertainties in snow precipitation estimation that depend on PSD parameterizations and scattering models of individual particles is important in evaluating the overall performance of dual-frequency retrieval techniques. Furthermore, separation of the uncertainties associated with the PSD models and the scattering models and their respective contributions to overall uncertainties are useful for gaining insight into ways to improve the retrieval methods.</p><p>Snow PSD is usually modelled as a gamma distribution with 2 or 3 free parameters depending on whether its shape factor is fixed or taken as a function of D<sub>m</sub>. In this study, our focus is on an assessment of the uncertainties in snow estimates arising from the PSD parameterization and the mass-size relation. To do this, measured PSD data are employed. The snow mass spectra, which can be converted from measured PSD using an empirical mass-size relation, are used to obtain PSD parameters, e.g., the liquid-equivalent mass-weighted diameter (D<sub>m</sub>) and the normalized intercept of a gamma PSD (N<sub>w</sub>), and the snow bulk parameters, such as snow water content (SWC) and liquid-equivalent snowfall rate (R) if a measured fall velocity-size relationship is utilized. Coupling measured PSD with particle scattering model, measured radar parameters can be computed, which are subsequently used as inputs to the standard dual-frequency algorithm. An evaluation of the retrieval accuracy is conducted by comparing the radar estimates of D<sub>m</sub>, N<sub>w</sub>, SWC and R with the same quantities directly computed from the PSD spectra (or truth). In this study, measurements of the snow PSD and fall velocity acquired from the Snow Video Imager/Particle Image Probe (SVI/PIP) at the NASA Wallops flight facility site in Virginia are employed. There are several scattering databases available that provide the scattering properties of snow aggregates in accordance with various snow and ice crystal growth models. Variability of the snow estimates caused by the differences of various scattering tables will be analyzed to explore the uncertainties associated with the scattering tables.</p>

scholarly journals Dual-wavelength radar technique development for snow rate estimation: a case study from GCPEx

2019 ◽  
Vol 12 (2) ◽  
pp. 1409-1427 ◽  
Author(s):  
Gwo-Jong Huang ◽  
Viswanathan N. Bringi ◽  
Andrew J. Newman ◽  
Gyuwon Lee ◽  
Dmitri Moisseev ◽  
...  
Keyword(s):  
Particle Size ◽  
Power Law ◽  
Radar Reflectivity ◽  
Dual Wavelength ◽  
Hydrodynamic Theory ◽  
Estimation Methods ◽  
Fall Velocity ◽  
Large Variability ◽  
Ka Band ◽  
Rate Estimation

Abstract. quantitative precipitation estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the prefactor of the power law due to changes in particle size distribution (PSD), density, and fall velocity, whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter), thus reducing the variability due to the prefactor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is falls in the Rayleigh region at Ku-band but in the Mie region at Ka-band. We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold-season Precipitation Experiment). Since the particle mass can be estimated using 2-D video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare it directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z–SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.

scholarly journals Ice Microphysical Properties near the Tops of Deep Convective Cores Implied by the GPM Dual-Frequency Radar Observations

2019 ◽  
Vol 76 (9) ◽  
pp. 2899-2917 ◽  
Author(s):  
Xiang Ni ◽  
Chuntao Liu ◽  
Edward Zipser
Keyword(s):  
Particle Size ◽  
Water Content ◽  
Deep Convection ◽  
Radar Reflectivity ◽  
Lookup Table ◽  
Dual Frequency ◽  
Ka Band ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
Ice Water

Abstract Using three years of observations from the Dual-Frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) Core Observatory, properties of the cores of deep convection are examined. First, deep convective systems are selected, defined as GPM precipitation features with maximum 20-dBZ echo-top heights above 10 km. The cores of deep convection are described by the profiles of Ku- and Ka-band radar reflectivity at the location of the highest echo top in each deep convective system. Then the dual-frequency ratio (DFR) profile is derived by subtracting Ka-band from Ku-band radar reflectivity. It is found that values of DFR are larger over land than over ocean in general near the top of the convection, which is consistent with larger ice particles in stronger updrafts in continental convection. The magnitude of DFR at 12 km is positively correlated with the convection intensity indicated by 20- and 30-dBZ echo tops. The microphysical properties including volume-weighted mean diameter, ice water content, and total ice particle number concentration are derived using a simple lookup table approach. Under the same particle size distribution assumption, the cores of deep convection over land have larger ice particle size, higher ice water content, and lower particle concentration than those over ocean at levels above 10 km, but with some distinct regional variations.

scholarly journals Dual-Wavelength Radar Technique Development for Snow Rate Estimation: A Case Study from GCPEx

2018 ◽  
Author(s):  
Gwo-Jong Huang ◽  
Viswanathan N. Bringi ◽  
Andrew J. Newman ◽  
GyuWon Lee ◽  
Dmitri Moisseev ◽  
...  
Keyword(s):  
Particle Size ◽  
Power Law ◽  
Radar Reflectivity ◽  
Dual Wavelength ◽  
Hydrodynamic Theory ◽  
Estimation Methods ◽  
Fall Velocity ◽  
Large Variability ◽  
Ka Band ◽  
Rate Estimation

Abstract. Quantitative Precipitation Estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the pre-factor of the power law due to changes in particle size distribution (PSD), density, and fall velocity whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter) thus reducing the variability due to the pre-factor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is such as to fall in the Rayleigh region at Ku-band but in the Mie region at Ka-band. We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold Season Precipitation Experiment). Since the particle mass can be estimated using 2D-video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z-SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.

scholarly journals The Dual Wavelength Ratio Knee: A Signature of Multiple Scattering in Airborne Ku–Ka Observations

2014 ◽  
Vol 53 (7) ◽  
pp. 1790-1808 ◽  
Author(s):  
Alessandro Battaglia ◽  
Simone Tanelli ◽  
Gerald M. Heymsfield ◽  
Lin Tian
Keyword(s):  
Multiple Scattering ◽  
Scattering Theory ◽  
Lower Troposphere ◽  
Single Scattering ◽  
Dual Wavelength ◽  
Dual Frequency ◽  
Ka Band ◽  
Convective Systems ◽  
Scattering Effects ◽  
Multiple Scattering Effects

AbstractDeep convective systems observed by the High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) radar during the 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) field campaign in Oklahoma provide the first evidence of multiple-scattering effects simultaneously at Ku and Ka band. One feature is novel and noteworthy: often, in correspondence to shafts with strong convection and when moving from the top of the cloud downward, the dual wavelength ratio (DWR) first increases as usual in Ku–Ka-band observations, but then it reaches a maximum and after that point it steadily decreases all the way to the surface, forming what will be hereinafter referred to as a knee. This DWR knee cannot be reproduced by single-scattering theory under almost any plausible cloud microphysical profile. On the other hand, it is explained straightforwardly with the help of multiple-scattering theory when simulations involving hail-bearing convective cores with large horizontal extents are performed. The DWR reduction in the lower troposphere (i.e., DWR increasing with altitude) is interpreted as the result of multiple-scattering pulse stretching caused by the highly diffusive hail layer positioned high up in the atmosphere, with Ka multiple scattering typically exceeding that occurring in the Ku channel. Since the effects of multiple scattering increase with increasing footprint size, if multiple-scattering effects are present in the aircraft measurements, they are likely to be more pronounced in the spaceborne dual-frequency Ku–Ka radar observations, envisaged for the NASA–Japan Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) Mission, launched in February 2014. This notional study supports the idea that DWR knees will be observed by the GPM radar when overflying high-density ice shafts embedded in large convective systems and suggests that their explanation must not be sought in differential attenuation or differential Mie effects but via multiple-scattering effects.

Investigating the contribution of polarimetry in retrieving ice microphysical properties using Dual-Wavelength radar observations

2020 ◽  
Author(s):  
Eleni Tetoni ◽  
Florian Ewald ◽  
Gregor Möller ◽  
Martin Hagen ◽  
Tobias Zinner ◽  
...  
Keyword(s):  
Radar Reflectivity ◽  
Dual Wavelength ◽  
Dual Frequency ◽  
Ka Band ◽  
Radar Observations ◽  
Microphysical Properties ◽  
Ice Particles ◽  
T Matrix ◽  
Linear Depolarization Ratio ◽  
German Aerospace

<p>Many studies have shown that multi-wavelength radar measurements can be valuable in inferring information about the size of observed hydrometeors in the atmosphere. Dual-wavelength radar method is widely known in such retrievals as it takes advantage of the different scattering behavior of hydrometeors in Rayleigh and MIE regime. Hydrometeors with sizes much smaller than the radar wavelength, act like Rayleigh scatterers and their radar reflectivity Z is proportional to the sixth power of their size. While these particles become larger due to riming or aggregation processes, with sizes comparable or larger than the radar wavelength, MIE effects can occur and thus, Z is proportional to the second power of their size. In the framework of IcePolCKa (Investigation of the initiation of Convection and the Evolution of Precipitation using simulatiOns and poLarimetric radar observations at C- and Ka-band) project, the evolution of ice in the precipitation formation will be studied exploiting these differences in both scattering regimes. Except for the logarithmic radar reflectivity difference, known as Dual-Wavelength Ratio (DWR) or Dual-Frequency Ratio (DFR), between C-band POLDIRAD weather radar from German Aerospace Center (DLR) in Oberpfaffenhofen and the Ka-band MIRA-35 cloud radar from Ludwig Maximilian University of Munich (LMU), other measured polarimetric variables from both radars, i.e. Differential Reflectivity (Z<sub>DR</sub>), Reflectivity Difference (Z<sub>DP</sub>), Linear Depolarization Ratio (LDR) will be also used. In addition to observations, scattering algorithms, i.e. T-matrix, will provide scattering simulations for a variety of ice particles shapes, sizes and mass-size relations. Combining DWR, polarimetric measurements and simulations the shape and/or the density of the observed ice particles will be retrieved. In this presentation, we will describe the instrumentation setup as well as the measuring methods in detail. Furthermore, we will present preliminary results of the retrieval approach using T-matrix calculations and measurements. Our first dataset consist of observations during snow events over Munich in January 2019 in order to avoid strong attenuation effects in the Ka-band.</p>

Dual-Polarized Dual-Frequency Ka-band Transmitarray Lens

2020 ◽  
Author(s):  
Enrique G. Plaza ◽  
German Leon ◽  
Susana Loredo ◽  
Luis F. Herran
Keyword(s):  
Dual Frequency ◽  
Ka Band ◽  
Dual Polarized

Dual frequency polarizing surfaces: For Ka-band applications

2012 ◽  
Author(s):  
E. Doumanis ◽  
G. Goussetis ◽  
R. Cahill ◽  
V. Fusco ◽  
H. Legay
Keyword(s):  
Dual Frequency ◽  
Ka Band

scholarly journals A Robust Dual-Frequency Radar Profiling Algorithm

2011 ◽  
Vol 50 (7) ◽  
pp. 1543-1557 ◽  
Author(s):  
Mircea Grecu ◽  
Lin Tian ◽  
William S. Olson ◽  
Simone Tanelli
Keyword(s):  
Synthetic Data ◽  
Optimization Procedure ◽  
Correction Method ◽  
Single Frequency ◽  
Retrieval Algorithm ◽  
Dual Frequency ◽  
Ka Band ◽  
Radar Observations ◽  
Distribution Shape ◽  
Ku Band

AbstractIn this study, an algorithm to retrieve precipitation from spaceborne dual-frequency (13.8 and 35.6 GHz, or Ku/Ka band) radar observations is formulated and investigated. Such algorithms will be of paramount importance in deriving radar-based and combined radar–radiometer precipitation estimates from observations provided by the forthcoming NASA Global Precipitation Measurement (GPM) mission. In GPM, dual-frequency Ku-/Ka-band radar observations will be available only within a narrow swath (approximately one-half of the width of the Ku-band radar swath) over the earth’s surface. Therefore, a particular challenge is to develop a flexible radar retrieval algorithm that can be used to derive physically consistent precipitation profile estimates across the radar swath irrespective of the availability of Ka-band radar observations at any specific location inside that swath, in other words, an algorithm capable of exploiting the information provided by dual-frequency measurements but robust in the absence of Ka-band channel. In the present study, a unified, robust precipitation retrieval algorithm able to interpret either Ku-only or dual-frequency Ku-/Ka-band radar observations in a manner consistent with the information content of the observations is formulated. The formulation is based on 1) a generalized Hitschfeld–Bordan attenuation correction method that yields generic Ku-only precipitation profile estimates and 2) an optimization procedure that adjusts the Ku-band estimates to be physically consistent with coincident Ka-band reflectivity observations and surface reference technique–based path-integrated attenuation estimates at both Ku and Ka bands. The algorithm is investigated using synthetic and actual airborne radar observations collected in the NASA Tropical Composition, Cloud, and Climate Coupling (TC4) campaign. In the synthetic data investigation, the dual-frequency algorithm performed significantly better than a single-frequency algorithm; dual-frequency estimates, however, are still sensitive to various assumptions such as the particle size distribution shape, vertical and cloud water distributions, and scattering properties of the ice-phase precipitation.

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