scholarly journals The Gradient Velocity Track Display (GrVTD) Technique for Retrieving Tropical Cyclone Primary Circulation from Aliased Velocities Measured by Single-Doppler Radar

2012 ◽  
Vol 29 (8) ◽  
pp. 1026-1041 ◽  
Author(s):  
Mingjun Wang ◽  
Kun Zhao ◽  
Wen-Chau Lee ◽  
Ben Jong-Dao Jou ◽  
Ming Xue
Keyword(s):  
Inner Core ◽  
Doppler Radar ◽  
Data Distribution ◽  
Circulation Pattern ◽  
Radar Data ◽  
Simplex Algorithm ◽  
Doppler Velocity ◽  
Hurricane Charley ◽  
Landfalling Tropical Cyclones ◽  
Good Agreement

Abstract The ground-based velocity track display (GBVTD) technique was developed to estimate the primary circulations of landfalling tropical cyclones (TCs) from single-Doppler radar data. However, GBVTD cannot process aliased Doppler velocities, which are often encountered in intense TCs. This study presents a new gradient velocity track display (GrVTD) algorithm that is essentially immune to the Doppler velocity aliasing. GrVTD applies the concept of gradient velocity–azimuth display (GVAD) to the GBVTD method. A GrVTD-simplex algorithm is also developed to accompany GrVTD as a self-sufficient algorithm suite. The results from idealized experiments demonstrate that the circulation center and winds retrieved from GrVTD with aliased velocity and GBVTD with dealiased velocity are in good agreement, but GrVTD is more sensitive to random observation errors. GrVTD was applied to Hurricane Charley (2004) where the majority of the Doppler velocities of the inner-core region were aliased. The GrVTD-retrieved circulation pattern and magnitude are nearly identical to those retrieved in GBVTD with manually dealiased velocities. Overall, the performance of GrVTD is comparable but is more sensitive to the data distribution than that of the original GBVTD using dealiased velocity. GrVTD can be used as a preprocessor for dealiasing velocity in TCs before the data are used in GBVTD or other algorithms.

The Improvement to the Environmental Wind and Tropical Cyclone Circulation Retrievals with the Modified GBVTD (MGBVTD) Technique

2013 ◽  
Vol 52 (11) ◽  
pp. 2493-2508 ◽  
Author(s):  
Xiaomin Chen ◽  
Kun Zhao ◽  
Wen-Chau Lee ◽  
Ben Jong-Dao Jou ◽  
Ming Xue ◽  
...  
Keyword(s):  
Inner Core ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Radar Data ◽  
Accurate Estimation ◽  
Doppler Radar Data ◽  
Tangential Wind ◽  
The Mean ◽  
Landfalling Tropical Cyclones ◽  
Beam Component

AbstractThe ground-based velocity track display (GBVTD) was developed to deduce a three-dimensional primary circulation of landfalling tropical cyclones from single-Doppler radar data. However, the cross-beam component of the mean wind cannot be resolved and is consequently aliased into the retrieved axisymmetric tangential wind . Recently, the development of the hurricane volume velocity processing method (HVVP) enabled the independent estimation of ; however, HVVP is potentially limited by the unknown accuracy of empirical assumptions used to deduce the modified Rankine-combined vortex exponent . By combing the GBVTD with HVVP techniques, this study proposes a modified GBVTD method (MGBVTD) to objectively deduce from the GBVTD technique and provide a more accurate estimation of and via an iterative procedure to reach converged and cross-beam component of solutions. MGBVTD retains the strength of both algorithms but avoids their weaknesses. The results from idealized experiments demonstrate that the MGBVTD-retrieved cross-beam component of is within 2 m s−1 of reality. MGBVTD was applied to Hurricane Bret (1999) whose inner core was captured simultaneously by two Weather Surveillance Radar-1988 Doppler (WSR-88D) instruments. The MGBVTD-retrieved cross-beam component of from single-Doppler radar data is very close to that from dual-Doppler radar synthesis using extended GBVTD (EGBVTD); their difference is less than 2 m s−1. The mean difference in the MGBVTD-retrieved from the two radars is ~2 m s−1, which is significantly smaller than that resolved in GBVTD retrievals (~5 m s−1).

Observed Near-Surface Wind Structure in the Inner Core of Typhoon Goni (2015)

2021 ◽  
Author(s):  
Wataru Mashiko ◽  
Udai Shimada
Keyword(s):  
Inner Core ◽  
Doppler Radar ◽  
Potential Temperature ◽  
Surface Wind ◽  
Radar Data ◽  
Doppler Velocity ◽  
Near Surface ◽  
Pressure Drops ◽  
Low Levels ◽  
And Shifts

AbstractThe very strong Typhoon Goni passed over the Yaeyama Islands in southwestern Japan during the rapid intensification stage on August 23, 2015. Surface data collected by the dense network of weather stations as well as Doppler radar observations over the islands revealed a finescale structure in the inner core of the typhoon near the surface.Goni had a clear eye surrounded by a square-shaped eyewall with intense convection. The surface observations revealed that several vortices with a diameter of ~7–10 km accompanied by a pressure deficit were present inside the eye. From the Doppler velocity field, mesovortices approximately 10 km in diameter were found at the apexes of the square-shaped eyewall. These mesovortices and the inner rainbands emanating outward from the apexes of the polygonal eyewall generally exhibited features typical of vortex Rossby waves. The mesovortices were accompanied by a pressure deficit at the surface and enhanced surface winds. The data also indicated the first observational evidence of near-surface mixing between the eye and eyewall through the mesovortices, that is, the transport of high equivalent potential temperature in the eye toward the eyewall.The radar data revealed that many radar-reflectivity filaments that had a pleated shape with lengths of a few kilometers extended perpendicularly from the inner edge of the eyewall at low levels. The filaments associated with wind perturbations at low levels caused significant wind gusts accompanied by sudden pressure drops and shifts in wind direction at the surface.

scholarly journals Constant Raindrop Fall Speed Profiles Derived from Doppler Radar Data Analyses for Steady Nonconvective Precipitation

2005 ◽  
Vol 62 (1) ◽  
pp. 220-230 ◽  
Author(s):  
Robert Nissen ◽  
Roland List ◽  
David Hudak ◽  
Greg M. McFarquhar ◽  
R. Paul Lawson ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Free Fall ◽  
Radar Data ◽  
Measuring System ◽  
Doppler Velocity ◽  
Light Rain ◽  
Fall Speed ◽  
Air Speed ◽  
Velocity Moments ◽  
Rain Rates

Abstract For nonconvective, steady light rain with rain rates <5 mm h−1 the mean Doppler velocity of raindrop spectra was found to be constant below the melting band, when the drop-free fall speed was adjusted for pressure. The Doppler radar–weighted raindrop diameters varied from case to case from 1.5 to 2.5 mm while rain rates changed from 1.2 to 2.9 mm h−1. Significant changes of advected velocity moments were observed over periods of 4 min. These findings were corroborated by three independent systems: a Doppler radar for establishing vertical air speed and mean terminal drop speeds [using extended Velocity Azimuth Display (EVAD) analyses], a Joss–Waldvogel disdrometer at the ground, and a Particle Measuring System (PMS) 2-DP probe flown on an aircraft. These measurements were supported by data from upper-air soundings. The reason why inferred raindrop spectra do not change with height is the negligible interaction rate between raindrops at low rain rates. At low rain rates, numerical box models of drop collisions strongly support this interpretation. It was found that increasing characteristic drop diameters are correlated with increasing rain rates.

A Variational Method for Filling in Missing Data in Doppler Velocity Fields

2021 ◽  
Author(s):  
VINCENT T. WOOD ◽  
ROBERT P. DAVIES-JONES ◽  
ALAN SHAPIRO
Keyword(s):  
Missing Data ◽  
Doppler Radar ◽  
Signal To Noise Ratio ◽  
Original Data ◽  
Radar Data ◽  
Velocity Fields ◽  
Doppler Velocity ◽  
Doppler Radar Data ◽  
Ground Clutter ◽  
Tornado Warnings

AbstractSingle-Doppler radar data are often missing in important regions of a severe storm due to low return power, low signal-to-noise ratio, ground clutter associated with normal and anomalous propagation, and missing radials associated with partial or total beam blockage. Missing data impact the ability of WSR-88D algorithms to detect severe weather. To aid the algorithms, we develop a variational technique that fills in Doppler velocity data voids smoothly by minimizing Doppler velocity gradients while not modifying good data. This method provides estimates of the analysed variable in data voids without creating extrema.Actual single-Doppler radar data of four tornadoes are used to demonstrate the variational algorithm. In two cases, data are missing in the original data, and in the other two, data are voided artificially. The filled-in data match the voided data well in smoothly varying Doppler velocity fields. Near singularities such as tornadic vortex signatures, the match is poor as anticipated. The algorithm does not create any velocity peaks in the former data voids, thus preventing false triggering of tornado warnings. Doppler circulation is used herein as a far-field tornado detection and advance-warning parameter. In almost all cases, the measured circulation is quite insensitive to the data that have been voided and then filled. The tornado threat is still apparent.

A Velocity Dealiasing Technique Using Rapidly Updated Analysis from a Four-Dimensional Variational Doppler Radar Data Assimilation System

2010 ◽  
Vol 27 (7) ◽  
pp. 1140-1152 ◽  
Author(s):  
Eunha Lim ◽  
Juanzhen Sun
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Radar Data ◽  
Objective Analysis ◽  
Doppler Velocity ◽  
Horizontal Shear ◽  
Data Assimilation System ◽  
Radar Data Assimilation ◽  
Assimilation System

Abstract A Doppler velocity dealiasing algorithm is developed within the storm-scale four-dimensional radar data assimilation system known as the Variational Doppler Radar Analysis System (VDRAS). The innovative aspect of the algorithm is that it dealiases Doppler velocity at each grid point independently by using three-dimensional wind fields obtained either from an objective analysis using conventional observations and mesoscale model output or from a rapidly updated analysis of VDRAS that assimilates radar data. This algorithm consists of three steps: preserving horizontal shear, global dealiasing using reference wind from the objective analysis or the VDRAS analysis, and local dealiasing. It is automated and intended to be used operationally for radar data assimilation using numerical weather prediction models. The algorithm was tested with 384 volumes of radar data observed from the Next Generation Weather Radar (NEXRAD) for a severe thunderstorm that occurred during 15 June 2002. It showed that the algorithm was effective in dealiasing large areas of aliased velocities when the wind from the objective analysis was used as the reference and that more accurate dealiasing was achieved by using the continuously cycled VDRAS analysis.

Assimilation of Doppler Radar Observations with a Regional 3DVAR System: Impact of Doppler Velocities on Forecasts of a Heavy Rainfall Case

2005 ◽  
Vol 44 (6) ◽  
pp. 768-788 ◽  
Author(s):  
Qingnong Xiao ◽  
Ying-Hwa Kuo ◽  
Juanzhen Sun ◽  
Wen-Chau Lee ◽  
Eunha Lim ◽  
...  
Keyword(s):  
Radial Velocity ◽  
Vertical Velocity ◽  
Short Range ◽  
Heavy Rainfall ◽  
Doppler Radar ◽  
Radar Data ◽  
Radial Velocities ◽  
Doppler Velocity ◽  
Rainfall Forecast ◽  
Background Fields

Abstract In this paper, the impact of Doppler radar radial velocity on the prediction of a heavy rainfall event is examined. The three-dimensional variational data assimilation (3DVAR) system for use with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is further developed to enable the assimilation of radial velocity observations. Doppler velocities from the Korean Jindo radar are assimilated into MM5 using the 3DVAR system for a heavy rainfall case that occurred on 10 June 2002. The results show that the assimilation of Doppler velocities has a positive impact on the short-range prediction of heavy rainfall. The dynamic balance between atmospheric wind and thermodynamic fields, based on the Richardson equation, is introduced to the 3DVAR system. Vertical velocity (w) increments are included in the 3DVAR system to enable the assimilation of the vertical velocity component of the Doppler radial velocity observation. The forecast of the hydrometeor variables of cloud water (qc) and rainwater (qr) is used in the 3DVAR background fields. The observation operator for Doppler radial velocity is developed and implemented within the 3DVAR system. A series of experiments, assimilating the Korean Jindo radar data for the 10 June 2002 heavy rainfall case, indicates that the scheme for Doppler velocity assimilation is stable and robust in a cycling mode making use of high-frequency radar data. The 3DVAR with assimilation of Doppler radial velocities is shown to improve the prediction of the rainband movement and intensity change. As a result, an improved skill for the short-range heavy rainfall forecast is obtained. The forecasts of other quantities, for example, winds, are also improved. Continuous assimilation with 3-h update cycles is important in producing an improved heavy rainfall forecast. Assimilation of Doppler radar radial velocities using the 3DVAR background fields from a cycling procedure produces skillful rainfall forecasts when verified against observations.

Improved Prediction of Landfalling Tropical Cyclone in China Based on Assimilation of Radar Radial Winds with New Super-Observation Processing

2020 ◽  
Vol 35 (6) ◽  
pp. 2523-2539
Author(s):  
Jianing Feng ◽  
Yihong Duan ◽  
Qilin Wan ◽  
Hao Hu ◽  
Zhaoxia Pu
Keyword(s):  
Data Assimilation ◽  
Inner Core ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Numerical Weather Prediction Model ◽  
Previous Method ◽  
Horizontal Wind ◽  
The Impact

AbstractThis work explores the impact of assimilating radial winds from the Chinese coastal Doppler radar on track, intensity, and quantitative precipitation forecasts (QPF) of landfalling tropical cyclones (TCs) in a numerical weather prediction model, focusing mainly on two aspects: 1) developing a new coastal radar super-observation (SO) processing method, namely, an evenly spaced thinning method (ESTM) that is fit for landfalling TCs, and 2) evaluating the performance of the radar radial wind data assimilation in QPFs of landfalling TCs with multiple TC cases. Compared to a previous method of generating SOs (i.e., the radially spaced thinning method), in which the density of SOs is equal within the radial space of a radar scanning volume, the SOs created by ESTM are almost evenly distributed in the horizontal grids of the model background, resulting in more observations located in the TC inner-core region being involved in SOs. The use of SOs from ESTM leads to more cyclonic wind innovation, and larger analysis increments of height and horizontal wind in the lower level in an ensemble Kalman filter data assimilation experiment with TC Mujigae (2015). Overall, forecasts of a TC’s landfalling position, intensity, and QPF are improved by radar data assimilation for all cases, including Mujigae and the other eight TCs that made landfall on the Chinese mainland in 2017. Specifically, through assimilation, TC landing position error and intensity error are reduced by 33% and 25%, respectively. The mean equitable threat score of extreme rainfall [>80 mm (3 h)−1] forecasts is doubled on average over all cases.

scholarly journals Use of Cloud Radar Doppler Spectra to Evaluate Stratocumulus Drizzle Size Distributions in Large-Eddy Simulations with Size-Resolved Microphysics

2017 ◽  
Vol 56 (12) ◽  
pp. 3263-3283 ◽  
Author(s):  
J. Rémillard ◽  
A. M. Fridlind ◽  
A. S. Ackerman ◽  
G. Tselioudis ◽  
P. Kollias ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Cloud Base ◽  
Doppler Velocity ◽  
Sharp Reduction ◽  
Cloud Radar ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Formation And Evolution ◽  
Bin Microphysics

AbstractA case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated with an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 μm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely.

Finescale Vertical Structure of a Cold Front as Revealed by an Airborne Doppler Radar

2006 ◽  
Vol 134 (1) ◽  
pp. 251-271 ◽  
Author(s):  
Bart Geerts ◽  
Rick Damiani ◽  
Samuel Haimov
Keyword(s):  
Vertical Structure ◽  
Doppler Radar ◽  
Cold Front ◽  
Vertical Plane ◽  
Radar Data ◽  
Doppler Velocity ◽  
Density Current ◽  
Convective Boundary ◽  
Flight Level ◽  
Airborne Doppler Radar

Abstract In the afternoon of 24 May 2002, a well-defined and frontogenetic cold front moved through the Texas panhandle. Detailed observations from a series of platforms were collected near the triple point between this cold front and a dryline boundary. This paper primarily uses reflectivity and Doppler velocity data from an airborne 95-GHz radar, as well as flight-level thermodynamic data, to describe the vertical structure of the cold front as it intersected with the dryline. The prefrontal convective boundary layer was weakly capped, weakly sheared, and about 2.5 times deeper than the cold-frontal density current. The radar data depict the cold front as a fine example of an atmospheric density current at unprecedented detail (∼40 m). The echo structure and dual-Doppler-inferred airflow in the vertical plane reveal typical features such as a nose, a head, a rear-inflow current, and a broad current of rising prefrontal air that feeds the accelerating front-to-rear current over the head. The 2D cross-frontal structure, including the frontal slope, is highly variable in time or alongfront distance. Along this slope horizontal vorticity, averaging ∼0.05 s−1, is generated baroclinically, and the associated strong cross-front shear triggers Kelvin–Helmholtz (KH) billows at the density interface. Some KH billows occupy much of the depth of the density current, possibly even temporarily cutting off the head from its trailing body.

Quadrant Distribution of Tropical Cyclone Inner-Core Kinematics in Relation to Environmental Shear

2014 ◽  
Vol 71 (7) ◽  
pp. 2713-2732 ◽  
Author(s):  
Jennifer C. DeHart ◽  
Robert A. Houze ◽  
Robert F. Rogers
Keyword(s):  
Tropical Cyclone ◽  
Inner Core ◽  
Doppler Radar ◽  
Radar Data ◽  
Low Level ◽  
Strong Convection ◽  
Upper Level ◽  
Airborne Doppler Radar ◽  
The Vertical Distribution ◽  
Left Quadrant

Abstract Airborne Doppler radar data collected in tropical cyclones by National Oceanic and Atmospheric Administration WP-3D aircraft over an 8-yr period (2003–10) are used to statistically analyze the vertical structure of tropical cyclone eyewalls with reference to the deep-layer shear. Convective evolution within the inner core conforms to patterns shown by previous studies: convection initiates downshear right, intensifies downshear left, and weakens upshear. Analysis of the vertical distribution of radar reflectivity and vertical air motion indicates the development of upper-level downdrafts in conjunction with strong convection downshear left and a maximum in frequency upshear left. Intense updrafts and downdrafts both conform to the shear asymmetry pattern. While strong updrafts occur in the eyewall, intense downdrafts show far more radial variability, particularly in the upshear-left quadrant, though they concentrate along the eyewall edges. Strong updrafts are collocated with low-level inflow and upper-level outflow superimposed on the background flow. In contrast, strong downdrafts occur in association with low-level outflow and upper-level inflow.

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