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>

Advantages and limitations on combining radar dual - wavelength and polarimetric observations for ice microphysics retrievals

2021 ◽  
Author(s):  
Eleni Tetoni ◽  
Florian Ewald ◽  
Gregor Möller ◽  
Martin Hagen ◽  
Tobias Zinner ◽  
...  
Keyword(s):  
Dual Wavelength ◽  
Shape Estimation ◽  
Radar Observations ◽  
Microphysical Properties ◽  
Aspect Ratios ◽  
Retrieval Scheme ◽  
Mass Size ◽  
Ice Microphysics ◽  
German Aerospace ◽  
Size Relation

<p>The challenge of the ice microphysical processes representation in numerical weather models is a well-known phenomenon as it can lead to high uncertainty due to the variety of ice microphysics. As ice microphysical properties can strongly affect the initiation of precipitation as well as the type and amount of it, we need to better understand the complexity of ice processes. To accomplish this, better microphysics information through ice retrievals from measurements is needed. The multi-wavelength radar method is nowadays becoming more and more popular in such microphysics retrievals. Taking advantage of different scattering regimes (Rayleigh or Mie), information about the size of atmospheric hydrometeors can be inferred using different radar bands. For this study, dual-wavelength reflectivity ratio measurements were combined with polarimetric measurements to estimate the size of ice hydrometeors. The measurements were obtained by using the synergy of the C-band POLDIRAD weather radar from the German Aerospace Center, located in Oberpfaffenhofen, and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilian University of Munich. Along with the dual-wavelength dataset, the Differential Reflectivity (Z<sub>DR</sub>) from POLDIRAD was used as a polarimetric contribution for the shape estimation of the detected ice particles. The radar observations were compared with T-matrix scattering simulations for the development of a retrieval scheme of ice microphysics. In the course of these studies, different assumptions were considered in the simulations. To capture the size variability, a Gamma particle size distribution (PSD) with different values of median volume diameter (MVD) was used. The soft spheroid approximation was used to approximate the ice particle shapes and to simplify the calculation and variation of their aspect ratios and effective densities. The selection of the most representative mass-size relation was the most crucial for the scattering simulations. In this study, we explored the modified Brown and Francis as well as the aggregates mass-size relation. After comparing the simulations to radar observations, we selected the better fitting one, i.e. aggregates, excluding the Brown and Francis as the simulated particles appeared to be too fluffy. Using the aggregates formulas, Look-Up tables (LUTs) for MVD, aspect ratio, and IWC were developed and used in the ice microphysics retrieval scheme. Here, we present preliminary microphysics retrievals of the median size, shape, and IWC of the detected hydrometeors combining the simulations in LUTs with the radar observations from different precipitation events over the Munich area.</p>

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 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.

scholarly journals Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra

2021 ◽  
Author(s):  
Christopher R. Williams ◽  
Karen L. Johnson ◽  
Scott E. Giangrande ◽  
Joseph C. Hardin ◽  
Ruşen Öktem ◽  
...  
Keyword(s):  
Power Spectra ◽  
Department Of Energy ◽  
Cloud Base ◽  
Doppler Velocity ◽  
Polarimetric Radar ◽  
Ka Band ◽  
Ice Particles ◽  
Linear Depolarization Ratio ◽  
Velocity Spectra ◽  
Discrimination Method

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The insect-hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects versus cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra linear depolarization ratio (LDR) produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives this need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Comparison with a collocated ceilometer indicates that hydrometeor mask column bottoms are within +/-100 meters of simultaneous ceilometer cloud base heights. Forty-seven (47) summer-time days were processed with the insect-hydrometeor discrimination method using U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma (USA). All datasets and images are available on public repositories.

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 Microphysics Observations in Hurricane Humberto: Comparison with Non-Hurricane-Generated Ice Cloud Layers

2006 ◽  
Vol 63 (1) ◽  
pp. 288-308 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Aaron Bansemer ◽  
Stephen L. Durden ◽  
Robert L. Herman ◽  
T. Paul Bui
Keyword(s):  
Doppler Radar ◽  
Deep Convection ◽  
Particle Growth ◽  
Dual Wavelength ◽  
Size Distributions ◽  
Temperature Growth ◽  
Radar Observations ◽  
Ice Cloud ◽  
Ice Particles ◽  
High Concentrations

Abstract Measurements are presented that were acquired from the National Aeronautics and Space Administration (NASA) DC-8 aircraft during an intensive 3-day study of Tropical Storm/Hurricane Humberto on 22, 23, and 24 September 2001. Particle size distributions, particle image information, vertical velocities, and single- and dual-wavelength Doppler radar observations were obtained during repeated sampling of the eyewall and outer eye regions. Eyewall sampling temperatures ranged from −22° to −57°C and peak updraft velocities from 4 to 15 m s−1. High concentrations of small ice particles, in the order 50 cm−3 and above, were observed within and around the updrafts. Aggregates, some larger than 7 mm, dominated the larger sizes. The slope of the fitted exponential size distributions λ was distinctly different close to the eye than outside of that region. Even at low temperatures, λ was characteristic of warm temperature growth (λ < 30 cm−1) close to the eye and characteristic of low temperature growth outside of it as well (λ > 100 cm−1). The two modes found for λ are shown to be consistent with observations from nonhurricane ice cloud layers formed through deep convection, but differ markedly from ice cloud layers generated in situ. It is shown that the median, mass-weighted, terminal velocities derived for the Humberto data and from the other datasets are primarily a function of λ. Microphysical measurements and dual wavelength radar observations are used together to infer and interpret particle growth processes. Rain in the lower portions of the eyewall extended up to the 6- or 7-km level. In the outer eye regions, aggregation progressed downward from between 8.5 and 11.9 km to the melting layer, with some graupel noted in rainbands. Homogeneous ice nucleation is implicated in the high concentrations of small ice particles observed in the vicinity of the updrafts.

The Life-Cycle of Cloud and Precipitation Microphysics in Radar Observation and Numerical Model

2021 ◽  
Author(s):  
Gregor Möller ◽  
Florian Ewald ◽  
Silke Groß ◽  
Martin Hagen ◽  
Christoph Knote ◽  
...  
Keyword(s):  
Prediction Models ◽  
Model Simulation ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Polarimetric Radar ◽  
Dual Frequency ◽  
Microphysics Scheme ◽  
Ka Band ◽  
Radar Observations ◽  
Conversion Rates

<p>The representation of microphysical processes in numerical weather prediction models remains a main source of uncertainty. To tackle this issue, we exploit the synergy of two polarimetric radars to provide novel observations of model microphysics parameterizations. In the framework of the IcePolCKa project (Investigation of the initiation of Convection and the Evolution of Precipitationusing simulatiOns and poLarimetric radar observations at C- and Ka-band) we use these observations to study the initiation of convection as well as the evolution of precipitation. At a distance of 23 km between the C-band PoldiRad radar of the German Aerospace Center (DLR) in Oberpfaffenhofen and the Ka-band Mira35 radar of the Ludwig-Maximilians-University of Munich (LMU), the two radar systems allow targeted observations and coordinated scan patterns. A second C-band radar located in Isen and operated by the German Weather Service (DWD) provides area coverage and larger spatial context. By tracking the precipitation movement, the dual-frequency and polarimetric radar observations allow us to characterize important microphysical parameters, such as predominant hydrometeor class or conversion rates between these classes over a significant fraction of the life time of a convective cell. A WRF (Weather Research and Forecasting Model) simulation setup has been established including a Europe-, a nested Germany- and a nested Munich- domain. The Munich domain covers the overlap area of our two radars Mira35 and Poldirad with a horizontal resolution of 400 m. For each of our measurement days we conduct a WRF hindcast simulation with differing microphysics schemes. To allow for a comparison between model world and observation space, we make use of the radar forward-simulator CR-SIM. The measurements so far include 240 coordinated scans of 36 different convective cells over 10 measurement days between end of April and mid July 2019 as well as 40 days of general dual-frequency volume scans between mid April and early October 2020. The performance of each microphysics scheme is analyzed through a comparison to our radar measurements on a statistical basis over all our measurements.</p>

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.

scholarly journals The Impact of the Radar-Sampling Volume on Multiwavelength Spaceborne Radar Measurements Using Airborne Radar Observations

2019 ◽  
Vol 11 (19) ◽  
pp. 2263 ◽  
Author(s):  
Lukas Pfitzenmaier ◽  
Alessandro Battaglia ◽  
Pavlos Kollias
Keyword(s):  
Moving Average ◽  
Particle Diameter ◽  
Dual Wavelength ◽  
Radar Observations ◽  
Airborne Measurements ◽  
Microphysical Properties ◽  
Characteristic Particle ◽  
Sampling Volume ◽  
The Impact ◽  
Spaceborne Radar

Multiwavelength radar observations have demonstrated great potential in improving microphysical retrievals of cloud properties especially in ice and snow precipitation systems. Advancements in spaceborne radar technology have already fostered the launch in 2014 of the first multiwavelength radar system in space, while several future spaceborne multiwavelength radar concepts are under consideration. However, due to antenna size limitations, the sampling volume of spaceborne radars is considerably larger than those achieved by surface- and airborne-based radars. Here, the impact of these large sampling volumes in the information content of the Dual-Wavelength Ratio estimates at Ka-W, Ku-Ka is investigated. High-resolution airborne multiwavelength radar observations during the Olympic Mountain Experiment (OLYMPEx) are used to perform retrievals of ice/snow characteristic particle size, such as mass-weighted particle diameter. To mimic the different satellite sampling volumes, a moving average is applied to the airborne measurements. The radar-observed variables (reflectivity and dual-wavelength ratios) and retrieved microphysical properties at the coarser resolution are compared against those at the original resolution. Our analysis indicates that future Ka-W spaceborne radar missions should take into account the impact of the radar resolution volume on the retrieval of microphysical properties and avoid footprints larger than 2–3 km.

scholarly journals Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

2021 ◽  
Vol 14 (6) ◽  
pp. 4425-4444
Author(s):  
Christopher R. Williams ◽  
Karen L. Johnson ◽  
Scott E. Giangrande ◽  
Joseph C. Hardin ◽  
Ruşen Öktem ◽  
...  
Keyword(s):  
Power Spectra ◽  
Department Of Energy ◽  
Cloud Base ◽  
Doppler Velocity ◽  
Polarimetric Radar ◽  
Ka Band ◽  
Ice Particles ◽  
Linear Depolarization Ratio ◽  
Velocity Spectra ◽  
Discrimination Method

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

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