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 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 Retrievals of ice microphysics using dual-wavelength polarimetric radar observations during stratiform precipitation events

2021 ◽  
Author(s):  
Eleni Tetoni ◽  
Florian Ewald ◽  
Martin Hagen ◽  
Gregor Köcher ◽  
Tobias Zinner ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Shape ◽  
Radar Reflectivity ◽  
Dual Wavelength ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Stratiform Precipitation ◽  
Mass Size ◽  
Ice Microphysics ◽  
Precipitation Events

Abstract. Ice growth processes within clouds affect the type as well as the amount of precipitation. Hence, the importance of an accurate representation of ice microphysics in numerical weather and numerical climate models has been confirmed by several studies. To better constrain ice processes in models, we need to study ice cloud regions before and during monitored precipitation events. For this purpose, two radar instruments facing each other were used to collect complementary measurements. The C-band POLDIRAD weather radar from the German Aerospace Center (DLR), Oberpfaffenhofen and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilians University of Munich (LMU) were used to monitor stratiform precipitation in the vertical cross-section area between both instruments. The logarithmic difference of radar reflectivities at two different wavelengths (54.5 and 8.5 mm), known as dual-wavelength ratio, was exploited to provide information about the size of the detected ice hydrometeors, taking advantage of the different scattering behavior in the Rayleigh and Mie regime. Along with the dual-wavelength ratio, differential radar reflectivity measurements from POLDIRAD provided information about the apparent shape of the detected ice hydrometeors. Scattering simulations using the T-matrix method were performed for oblate and horizontally aligned prolate ice spheroids of varying shape and size using a realistic particle size distribution and a well-established mass-size relationship. The combination of dual-wavelength ratio, radar reflectivity and differential radar reflectivity measurements as well as scattering simulations was used for the development of a novel retrieval for ice cloud microphysics. The development of the retrieval scheme also comprised a method to estimate the hydrometeor attenuation in both radar bands. To demonstrate this approach, a feasibility study was conducted on three stratiform snow events which were monitored over Munich in January 2019. The ice retrieval can obtain ice particle shape, size and mass which are in line with differential radar reflectivity, dual-wavelength ratio and radar reflectivity observations when a suitable mass-size relation is used and when ice hydrometeors are assumed to be represented by oblate ice spheroids. A furthermore finding was the importance of the differential radar reflectivity for the particle size retrieval directly above the MIRA-35 cloud radar. Especially for that observation geometry, the simultaneous slantwise observation from the polarimetric weather radar POLDIRAD could reduce ambiguities in retrieval of the ice particle size by constraining the ice particle shape.

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 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.

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>

scholarly journals A Study on the Feasibility of Dual-Wavelength Radar for Identification of Hydrometeor Phases

2011 ◽  
Vol 50 (2) ◽  
pp. 449-456 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini
Keyword(s):  
Size Distribution ◽  
Phase State ◽  
Cold Season ◽  
Radar Reflectivity ◽  
Mixed Phase ◽  
Dual Wavelength ◽  
Precipitation Event ◽  
Precipitation Radar ◽  
Ka Band ◽  
Ku Band

Abstract An important objective for the dual-wavelength Ku-/Ka-band precipitation radar (DPR) that will be on board the Global Precipitation Measurement (GPM) core satellite is to identify the phase state of hydrometeors along the range direction. To assess this, radar signatures are simulated in snow and rain to explore the relation between the differential frequency ratio (DFR), defined as the difference of radar reflectivity factors between Ku and Ka bands, and the radar reflectivity factor at Ku band ZKu for different hydrometeor types. Model simulations indicate that there is clear separation between snow and rain in the ZKu–DFR plane assuming that the snow follows the Gunn–Marshall size distribution and rain follows the Marshall–Palmer size distribution. In an effort to verify the simulated results, the data collected by the Airborne Second-Generation Precipitation Radar (APR-2) in the Wakasa Bay Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) campaign are employed. Using the signatures of linear depolarization ratio at Ku band, the APR-2 data can be easily divided into the regions of snow, mixed phase, and rain for stratiform storms. These results are then superimposed onto the theoretical curves computed from the model in the ZKu–DFR plane. For over 90% of the observations from a cold-season stratiform precipitation event, snow and rain can be distinguished if the Ku-band radar reflectivity exceeds 18 dBZ (the minimum detectable level of the GPM DPR at Ku band). This is also the case for snow and mixed-phase hydrometeors. Although snow can be easily distinguished from rain and melting hydrometeors by using Ku- and Ka-band radar, the rain and mixed-phase particles are not always separable. It is concluded that Ku- and Ka-band dual-wavelength radar might provide a potential means to identify the phase state of hydrometeors.

scholarly journals Jet Impingement Heat Transfer of Confined Single and Double Jets with Non-Newtonian Power Law Nanofluid under the Inclined Magnetic Field Effects for a Partly Curved Heated Wall

2021 ◽  
Vol 13 (9) ◽  
pp. 5086
Author(s):  
Fatih Selimefendigil ◽  
Hakan F. Oztop ◽  
Ali J. Chamkha
Keyword(s):  
Magnetic Field ◽  
Heat Transfer ◽  
Particle Size ◽  
Aspect Ratio ◽  
Power Law ◽  
Volume Fraction ◽  
Inclined Magnetic Field ◽  
Magnetic Field Effects ◽  
Power Law Nanofluid ◽  
Power Law Index

Single and double impinging jets heat transfer of non-Newtonian power law nanofluid on a partly curved surface under the inclined magnetic field effects is analyzed with finite element method. The numerical work is performed for various values of Reynolds number (Re, between 100 and 300), Hartmann number (Ha, between 0 and 10), magnetic field inclination (γ, between 0 and 90), curved wall aspect ratio (AR, between 01. and 1.2), power law index (n, between 0.8 and 1.2), nanoparticle volume fraction (ϕ, between 0 and 0.04) and particle size in nm (dp, between 20 and 80). The amount of rise in average Nusselt (Nu) number with Re number depends upon the power law index while the discrepancy between the Newtonian fluid case becomes higher with higher values of power law indices. As compared to case with n = 1, discrepancy in the average Nu number are obtained as −38% and 71.5% for cases with n = 0.8 and n = 1.2. The magnetic field strength and inclination can be used to control the size and number or vortices. As magnetic field is imposed at the higher strength, the average Nu reduces by about 26.6% and 7.5% for single and double jets with n greater than 1 while it increases by about 4.78% and 12.58% with n less than 1. The inclination of magnetic field also plays an important role on the amount of enhancement in the average Nu number for different n values. The aspect ratio of the curved wall affects the flow field slightly while the average Nu variation becomes 5%. Average Nu number increases with higher solid particle volume fraction and with smaller particle size. At the highest particle size, it is increased by about 14%. There is 7% variation in the average Nu number when cases with lowest and highest particle size are compared. Finally, convective heat transfer performance modeling with four inputs and one output is successfully obtained by using Adaptive Neuro-Fuzzy Interface System (ANFIS) which provides fast and accurate prediction results.

scholarly journals Computational Geometry-Based Surface Reconstruction for Volume Estimation: A Case Study on Magnitude-Frequency Relations for a LiDAR-Derived Rockfall Inventory

2021 ◽  
Vol 10 (3) ◽  
pp. 157
Author(s):  
Paul-Mark DiFrancesco ◽  
David A. Bonneau ◽  
D. Jean Hutchinson
Keyword(s):  
Computational Geometry ◽  
Surface Reconstruction ◽  
Power Law ◽  
Point Cloud ◽  
Point Clouds ◽  
Volume Estimation ◽  
Estimation Methods ◽  
Small Scale ◽  
Reconstruction Methods ◽  
3D Volume

Key to the quantification of rockfall hazard is an understanding of its magnitude-frequency behaviour. Remote sensing has allowed for the accurate observation of rockfall activity, with methods being developed for digitally assembling the monitored occurrences into a rockfall database. A prevalent challenge is the quantification of rockfall volume, whilst fully considering the 3D information stored in each of the extracted rockfall point clouds. Surface reconstruction is utilized to construct a 3D digital surface representation, allowing for an estimation of the volume of space that a point cloud occupies. Given various point cloud imperfections, it is difficult for methods to generate digital surface representations of rockfall with detailed geometry and correct topology. In this study, we tested four different computational geometry-based surface reconstruction methods on a database comprised of 3668 rockfalls. The database was derived from a 5-year LiDAR monitoring campaign of an active rock slope in interior British Columbia, Canada. Each method resulted in a different magnitude-frequency distribution of rockfall. The implications of 3D volume estimation were demonstrated utilizing surface mesh visualization, cumulative magnitude-frequency plots, power-law fitting, and projected annual frequencies of rockfall occurrence. The 3D volume estimation methods caused a notable shift in the magnitude-frequency relations, while the power-law scaling parameters remained relatively similar. We determined that the optimal 3D volume calculation approach is a hybrid methodology comprised of the Power Crust reconstruction and the Alpha Solid reconstruction. The Alpha Solid approach is to be used on small-scale point clouds, characterized with high curvatures relative to their sampling density, which challenge the Power Crust sampling assumptions.

scholarly journals Analysis of Raindrop Size Distribution Characteristics in Permafrost Regions of the Qinghai–Tibet Plateau Based on New Quality Control Scheme

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2265 ◽  
Author(s):  
Ma ◽  
Zhao ◽  
Yang ◽  
Xiao ◽  
Zhang ◽  
...  
Keyword(s):  
Particle Size ◽  
Quality Control ◽  
Rain Rate ◽  
Tibet Plateau ◽  
Frozen Ground ◽  
Fall Velocity ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Qinghai Tibet Plateau ◽  
Permafrost Regions

Raindrop size distribution (DSD) can reflect the fundamental microphysics of precipitation and provide an accurate estimation of its amount and characteristics; however, there are few observations and investigations of DSD in cold, mountainous regions. We used the second-generation particle size and velocity disdrometer Parsivel2 to establish a quality control scheme for raindrop spectral data obtained for the Qinghai–Tibet Plateau in 2015. This scheme included the elimination of particles in the lowest two size classes, particles >10 mm in diameter and rain rates <0.01 mm∙h−1. We analyzed the DSD characteristics for different types of precipitation and rain rates in both permafrost regions and regions with seasonally frozen ground. The precipitation in the permafrost regions during the summer were mainly solid with a large particle size and slow fall velocity, whereas the precipitation in the regions with seasonally frozen ground were mainly liquid. The DSD of snow had a broader drop spectrum, the largest particle size, the slowest fall velocity, and the largest number of particles, followed by hail. Rain and sleet shared similar DSD characteristics, with a smaller particle size, slower velocity, and smaller number of particles. The particle concentration for different classes of rain rate decreased with an increase in particle size and decreased gradually with an increase in rain rate. Precipitation with a rain rate >2 mm∙h−1 was the main contributor to the annual precipitation. The dewpoint thresholds for snow and rain in permafrost regions were 0 and 1.5 °C, respectively. The dewpoint range 0–1.5 °C was characterized by mixed precipitation with a large proportion of hail. This study provides valuable DSD information on the Qinghai–Tibet Plateau and can be used as an important reference for the quality control of raindrop spectral data in regions dominated by solid precipitation.

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