Doppler Velocity Bias Mitigation Through Sidelobe Whitening for Multistatic Weather Radar

2020 ◽  
pp. 1-13
Author(s):  
Andrew D. Byrd ◽  
Robert D. Palmer ◽  
Caleb J. Fulton
Keyword(s):  
Weather Radar ◽  
Doppler Velocity ◽  
Velocity Bias

scholarly journals Microphysical retrievals from simultaneous polarimetric and profiling radar observations

2009 ◽  
Vol 27 (12) ◽  
pp. 4435-4448 ◽  
Author(s):  
M. P. Morris ◽  
P. B. Chilson ◽  
T. J. Schuur ◽  
A. Ryzhkov
Keyword(s):  
Remote Sensing Data ◽  
Weather Radar ◽  
Ground Truth ◽  
Ambient Air ◽  
Exponential Model ◽  
Squall Line ◽  
Doppler Velocity ◽  
Wind Profiler ◽  
Polarimetric Weather Radar ◽  
Velocity Spectra

Abstract. The character of precipitation detected at the surface is the final product of many microphysical interactions in the cloud above, the combined effects of which may be characterized by the observed drop size distribution (DSD). This necessitates accurate retrieval of the DSD from remote sensing data, especially radar as it offers large areal coverage, high spatial resolution, and rigorous quality control and testing. Combined instrument observations with a UHF wind profiler, an S-band polarimetric weather radar, and a video disdrometer are analyzed for two squall line events occuring during the calendar year 2007. UHF profiler Doppler velocity spectra are used to estimate the DSD aloft, and are complemented by DSDs retrieved from an exponential model applied to polarimetric data. Ground truth is provided by the disdrometer. A complicating factor in the retrieval from UHF profiler spectra is the presence of ambient air motion, which can be corrected using the method proposed by Teshiba et al. (2009), in which a comparison between idealized Doppler spectra calculated from the DSDs retrieved from KOUN and those retrieved from contaminated wind profiler spectra is performed. It is found that DSDs measured using the distrometer at the surface and estimated using the wind profiler and polarimetric weather radar generally showed good agreement. The DSD retrievals using the wind profiler were improved when the estimates of the vertical wind were included into the analysis, thus supporting the method of Teshiba et al. (2009). Furthermore, the the study presents a method of investigating the time and height structure of DSDs.

Evaluation of the Simultaneous Multiple Pulse Repetition Frequency Algorithm for Weather Radar

2008 ◽  
Vol 25 (7) ◽  
pp. 1166-1181 ◽  
Author(s):  
Evan Ruzanski ◽  
John C. Hubbert ◽  
V. Chandrasekar
Keyword(s):  
Pulse Repetition Frequency ◽  
Weather Radar ◽  
Interval Data ◽  
Radar Data ◽  
Repetition Frequency ◽  
Pulse Repetition ◽  
Doppler Velocity ◽  
Mean Power ◽  
Mean Velocity ◽  
Multiple Pulse

Abstract Performance of the simultaneous multiple pulse repetition frequency algorithm (SMPRF) for recovery of mean power and mean Doppler velocity is investigated using simulated weather radar data. Operation and functionality of the algorithm is described; methods to estimate mean power values using statistical inversion and to estimate mean velocity from unevenly spaced autocorrelation function samples are presented and analyzed. A simulation technique for constructing multiple pulse repetition interval data is described and the algorithm performance results are presented for an example SMPRF code using three weather profiles. This leads to the development of an error structure related to factors influencing moment recovery, including finite-length time series effects, the effects of overlaid echoes that create an effective signal-to-noise ratio that limits moment recovery performance, and the effects of spectrum width and radar frequency related to coherence time.

A Combined Wind Profiler and Polarimetric Weather Radar Method for the Investigation of Precipitation and Vertical Velocities

2009 ◽  
Vol 26 (9) ◽  
pp. 1940-1955 ◽  
Author(s):  
Michihiro S. Teshiba ◽  
Phillip B. Chilson ◽  
Alexander V. Ryzhkov ◽  
Terry J. Schuur ◽  
Robert D. Palmer
Keyword(s):  
Weather Radar ◽  
Terminal Velocity ◽  
Doppler Velocity ◽  
Drop Diameter ◽  
Wind Profiler ◽  
Rain Drop ◽  
Air Motion ◽  
Polarimetric Weather Radar ◽  
Uhf Wind Profiler ◽  
Differential Reflectivity

Abstract A method is presented by which combined S-band polarimetric weather radar and UHF wind profiler observations of precipitation can be used to extract the properties of liquid phase hydrometeors and the vertical velocity of the air through which they are falling. Doppler spectra, which contain the air motion and/or fall speed of hydrometeors, are estimated using the vertically pointing wind profiler. Complementary to these observations, spectra of rain drop size distribution (DSD) are simulated by several parameters as related to the DSD, which are estimated through the two polarimetric parameters of radar reflectivity (ZH) and differential reflectivity (ZDR) from the scanning weather radar. These DSDs are then mapped into equivalent Doppler spectra (fall speeds) using an assumed relationship between the equivolume drop diameter and the drop’s terminal velocity. The method is applied to a set of observations collected on 11 March 2007 in central Oklahoma. In areas of stratiform precipitation, where the vertical wind motion is expected to be small, it was found that the fall speeds obtained from the spectra of the rain DSD agree well with those of the Doppler velocity estimated with the profiler. For those cases when the shapes of the Doppler spectra are found to be similar in shape but shifted in velocity, the velocity offset is attributed to vertical air motion. In convective rainfall, the Doppler spectra of the rain DSD and the Doppler velocity can exhibit significant differences owing to vertical air motions together with atmospheric turbulence. Overall, it was found that the height dependencies of Doppler spectra measured by the profiler combined with vertical profiles of Z, ZDR, and the cross correlation (ρHV) as well as the estimated spectra of raindrop physical terminal fall speeds from the polarimetric radar provide unique insight into the microphysics of precipitation. Vertical air motions (updrafts/downdrafts) can be estimated using such combined measurements.

scholarly journals Observation and Real-Time Simulation of a Tornado Event in Hong Kong on 29 August 2018

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
K. K. Hon ◽  
S. M. Tse ◽  
P. W. Chan ◽  
Q. S. Li
Keyword(s):  
Hong Kong ◽  
Real Time ◽  
Model Simulation ◽  
Weather Prediction ◽  
Time Lag ◽  
Weather Radar ◽  
Doppler Velocity ◽  
Real Time Simulation ◽  
Time Simulation ◽  
Tornado Event

An observational and simulation study of a tornado event in Hong Kong that occurred in the morning of 29 August 2018 is documented in this paper. Rotating airflow associated with the tornado is well captured by the Doppler velocity from a Terminal Doppler Weather Radar (TDWR) in Hong Kong. The Doppler velocity patterns show the typical signature of a velocity couplet associated with a meso/microcyclone, and for most part of its lifetime, it captures clearly the evolution with time. Weather radar echoes of those thunderstorms inducing the current tornado, as well as the meso/microcyclone itself, are also successfully reproduced in a real-time simulation by a fine-resolution numerical weather prediction (NWP) model initialised 3 hours earlier, albeit with a time lag of about 15 minutes when compared to the actual event. The model simulation displays some interesting features of the cyclone, including the vertical structure of horizontal and vertical velocities and cloud liquid water content, which are consistent with literature that accounts in other parts of the world. The vertical profile of maximum radial velocity associated with the velocity couplet also compares well between the actual weather radar observation and numerical simulation. The results in this paper could serve as an interesting reference for both meteorologists and wind engineers, also demonstrating the power of very high-resolution NWP in predicting such events in a real-time fashion.

Wind Turbine Clutter Mitigation via Nonconvex Regularizers and Multidimensional Processing

2019 ◽  
Vol 36 (6) ◽  
pp. 1093-1104
Author(s):  
Yinan Hu ◽  
Faruk Uysal ◽  
Ivan Selesnick
Keyword(s):  
Wind Turbine ◽  
Weather Radar ◽  
Spectral Width ◽  
Previous Method ◽  
Weather Data ◽  
Doppler Velocity ◽  
Radar Systems ◽  
Previous Formulation ◽  
Clutter Mitigation

AbstractThis paper generalizes a previous formulation of signal separation problem for dynamic wind turbine clutter mitigation at weather radar systems. In this modified formulation, we use nonconvex regularizers together with multichannel overlapping group shrinkage (MOGS) to penalize weather signals and adopt multidimensional processing. We show the restored weather signals in plan position indicator (PPI) format and, to demonstrate the improvement, compare them with the ones produced by the previous method in reflectivity, spectral width, and Doppler velocity estimates of weather data. The improvement results from a better characterization of the sparsities of the weather radar returns. During the course of experiments, we observe that the proposed method successfully mitigates the wind turbine clutter and dramatically increases the signal-to-clutter ratio, even for different weather and wind turbine signatures. In addition, when the wind turbine clutter is weak in the mixture, our algorithm manages to attenuate the ground clutters and produces clutter-free weather signals favorable for further processing.

Doppler Velocity Measurement of Portable X-Band Weather Radar Equipped with Magnetron Transmitter and IF Digital Receiver

2011 ◽  
Vol E94-B (6) ◽  
pp. 1716-1724 ◽  
Author(s):  
Masayuki K. YAMAMOTO ◽  
Tomoaki MEGA ◽  
Nobuyuki IKENO ◽  
Toyoshi SHIMOMAI ◽  
Hiroyuki HASHIGUCHI ◽  
...  
Keyword(s):  
Velocity Measurement ◽  
Weather Radar ◽  
Doppler Velocity ◽  
Digital Receiver ◽  
X Band

scholarly journals Assessment of radar reflectivity and Doppler velocity measured by Ka-band FMCW Doppler weather radar

2011 ◽  
Vol 31 (2) ◽  
pp. 85-94 ◽  
Author(s):  
Masayuki Yamamoto ◽  
Tomoaki Mega ◽  
Nobuyuki Ikeno ◽  
Toyoshi Shimomai ◽  
Hiroyuki Hashiguchi ◽  
...  
Keyword(s):  
Weather Radar ◽  
Radar Reflectivity ◽  
Doppler Velocity ◽  
Doppler Weather Radar ◽  
Ka Band

Laser Doppler velocity bias in separated turbulent flows

2004 ◽  
Vol 6 (2) ◽  
pp. 80-88 ◽  
Author(s):  
H. L. Petrie ◽  
M. Samimy ◽  
A. L. Addy
Keyword(s):  
Turbulent Flows ◽  
Laser Doppler ◽  
Doppler Velocity ◽  
Velocity Bias

scholarly journals Analysis of a Precipitation System that Exists above Freezing Level Using a Multi-Parameter Phased Array Weather Radar

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 755
Author(s):  
Nobuhiro Takahashi
Keyword(s):  
Vertical Velocity ◽  
Vertical Profile ◽  
Phased Array ◽  
Three Dimensional ◽  
Weather Radar ◽  
Cloud Base ◽  
Doppler Velocity ◽  
Freezing Level ◽  
Precipitation System ◽  
Fall Speed

An X-band multi-parameter phased array weather radar (MP-PAWR) was developed in 2017. The scan concept of the MP-PAWR is electronic scanning in elevation by combining fan beam transmissions and pencil beam receptions with digital beam-forming techniques and mechanical scanning along the azimuth. The MP-PAWR realized three-dimensional (60 km in radius and 15 km in height) observations without gaps of 30 s. Although the MP-PAWR is supposed to be suitable for observations of rapidly changing convective systems, it can be advantageous for observations of stratiform rainfall because of continuous vertical pointing observations and its ability to apply the Velocity Azimuth Display (VAD) method with a constant radius for a vertical profile of dynamic parameters such as divergence and deformation. In this study, a precipitation system that existed mainly above the freezing level (in this case, it was approximately 5 km in height) observed from 14:00 to 17:00 Japan Standard Time on 6 September 2018 was analyzed using MP-PAWR data. The averaged area of the vertical profile of Z, and the Doppler velocity with fixed elevation showed a stationary structure with time. The average differential reflectivity factor (ZDR) profile with fixed elevation angles showed values that were close to zero and increased with height. Similar characteristics were shown in the average Specific Differential Phase (KDP) profile. Vertical pointing data, especially for Z, ZDR, and Doppler velocity, were utilized when the echo passed over the radar site, and the Doppler velocity showed the acceleration of fall speed below the freezing level. The vertical profile of divergence with a fixed radius was calculated using the VAD method, and the vertical velocity was calculated using the fall speed profile from the vertical pointing data and by assuming the vertical velocity at the cloud base was zero. The results indicate that the updraft region corresponds to higher ZDR and KDP regions.

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