scholarly journals Correction of Dual-PRF Doppler Velocity Outliers in the Presence of Aliasing

2017 ◽  
Vol 34 (7) ◽  
pp. 1529-1543 ◽  
Author(s):  
Patricia Altube ◽  
Joan Bech ◽  
Oriol Argemí ◽  
Tomeu Rigo ◽  
Nicolau Pineda ◽  
...  
Keyword(s):  
Prediction Models ◽  
Doppler Radar ◽  
Pulse Repetition Frequency ◽  
Weather Prediction ◽  
Velocity Fields ◽  
Circular Statistics ◽  
Doppler Velocity ◽  
Storm Events ◽  
Quality Issue ◽  
Improved Performance

AbstractIn Doppler weather radars, the presence of unfolding errors or outliers is a well-known quality issue for radial velocity fields estimated using the dual–pulse repetition frequency (PRF) technique. Postprocessing methods have been developed to correct dual-PRF outliers, but these need prior application of a dealiasing algorithm for an adequate correction. This paper presents an alternative procedure based on circular statistics that corrects dual-PRF errors in the presence of extended Nyquist aliasing. The correction potential of the proposed method is quantitatively tested by means of velocity field simulations and is exemplified in the application to real cases, including severe storm events. The comparison with two other existing correction methods indicates an improved performance in the correction of clustered outliers. The technique proposed is well suited for real-time applications requiring high-quality Doppler radar velocity fields, such as wind shear and mesocyclone detection algorithms, or assimilation in numerical weather prediction models.

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.

scholarly journals Implementation of polarization diversity pulse-pair technique using airborne W-band radar

2019 ◽  
Vol 12 (1) ◽  
pp. 253-269 ◽  
Author(s):  
Mengistu Wolde ◽  
Alessandro Battaglia ◽  
Cuong Nguyen ◽  
Andrew L. Pazmany ◽  
Anthony Illingworth
Keyword(s):  
Doppler Radar ◽  
Pulse Repetition Frequency ◽  
National Research Council ◽  
Doppler Velocity ◽  
Polarization Diversity ◽  
Pulse Pair ◽  
W Band ◽  
Standard Pulse ◽  
Very High

Abstract. This work describes the implementation of polarization diversity on the National Research Council Canada W-band Doppler radar and presents the first-ever airborne Doppler measurements derived via polarization diversity pulse-pair processing. The polarization diversity pulse-pair measurements are interleaved with standard pulse-pair measurements with staggered pulse repetition frequency, this allows a better understanding of the strengths and drawbacks of polarization diversity, a methodology that has been recently proposed for wind-focused Doppler radar space missions. Polarization diversity has the clear advantage of making possible Doppler observations of very fast decorrelating media (as expected when deploying Doppler radars on fast-moving satellites) and of widening the Nyquist interval, thus enabling the observation of very high Doppler velocities (up to more than 100 m s−1 in the present work). Crosstalk between the two polarizations, mainly caused by depolarization at backscattering, deteriorated the quality of the observations by introducing ghost echoes in the power signals and by increasing the noise level in the Doppler measurements. In the different cases analyzed during the field campaigns, the regions affected by crosstalk were generally associated with highly depolarized surface returns and depolarization of backscatter from hydrometeors located at short ranges from the aircraft. The variance of the Doppler velocity estimates can be well predicted from theory and were also estimated directly from the observed correlation between the H-polarized and V-polarized successive pulses. The study represents a key milestone towards the implementation of polarization diversity in Doppler space-borne radars.

Practical Uncertainties in the Limited Predictability of the Record-Breaking Intensification of Hurricane Patricia (2015)

2019 ◽  
Vol 147 (10) ◽  
pp. 3535-3556 ◽  
Author(s):  
Robert G. Nystrom ◽  
Fuqing Zhang
Keyword(s):  
Prediction Models ◽  
Doppler Radar ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Model Errors ◽  
Surface Drag ◽  
Maximum Wind ◽  
Peak Intensity ◽  
Secondary Circulations ◽  
Airborne Doppler Radar

Abstract Hurricane Patricia (2015) was a record-breaking tropical cyclone that was difficult to forecast in real time by both operational numerical weather prediction models and operational forecasters. The current study examines the potential for improving intensity prediction for extreme cases like Hurricane Patricia. We find that Patricia’s intensity predictability is potentially limited by both initial conditions, related to the data assimilation, and model errors. First, convection-permitting assimilation of airborne Doppler radar radial velocity observations with an ensemble Kalman filter (EnKF) demonstrates notable intensity forecast improvements over assimilation of conventional observations alone. Second, decreasing the model horizontal grid spacing to 1 km and reducing the surface drag coefficient at high wind speed in the parameterization of the sea surface–atmosphere exchanges is also shown to notably improve intensity forecasts. The practical predictability of Patricia, its peak intensity, rapid intensification, and the underlying dynamics are further investigated through a high-resolution 60-member ensemble initialized with realistic initial condition uncertainties represented by the EnKF posterior analysis perturbations. Most of the ensemble members are able to predict the peak intensity of Patricia, but with greater uncertainty in the timing and rate of intensification; some members fail to reach the ultimate peak intensity before making landfall. Ensemble sensitivity analysis shows that initial differences in the region beyond the radius of maximum wind contributes the most to the differences between ensemble members in Patricia’s intensification. Ensemble members with stronger initial primary and secondary circulations beyond the radius of maximum wind intensify earlier, are able to maintain the intensification process for longer, and thus reach a greater and earlier peak intensity.

scholarly journals Implementation of Polarization Diversity Pulse Pair Technique using airborne W-band radar

2018 ◽  
Author(s):  
Mengistu Wolde ◽  
Alessandro Battaglia ◽  
Cuong Nguyen ◽  
Andrew L. Pazmany ◽  
Anthony Illingworth
Keyword(s):  
Cross Talk ◽  
Doppler Radar ◽  
Pulse Repetition Frequency ◽  
National Research Council ◽  
Doppler Velocity ◽  
Polarization Diversity ◽  
Pulse Pair ◽  
W Band ◽  
Standard Pulse

Abstract. This work describes the implementation of polarization diversity on the National Research Council Canada W-band Doppler radar and presents the first-ever airborne Doppler measurements derived via polarization diversity pulse pair processing. The polarization diversity pulse pair measurements are interleaved with standard pulse pair measurements with staggered pulse repetition frequency; this allows a better understanding of the strengths and drawbacks of polarization diversity, a methodology that has been recently proposed for wind-focussed Doppler radar space missions. Polarization diversity has the clear advantage of making possible Doppler observations of very fast de-correlating media (as expected when deploying Doppler radars on fast moving satellites) and of widening the Nyquist interval, thus enabling the observation of very high Doppler velocities (up to more than 100 m/s in present work). Cross-talk between the two polarizations, mainly caused by depolarization at backscattering deteriorated the quality of the observations by introducing ghost echoes in the power signals and by increasing the noise level in the Doppler measurements. In the different cases analyzed during the field campaigns, the regions affected by cross-talk were generally associated with highly depolarized surface returns and depolarization of backscatter from hydrometeors located at short ranges from the air craft. The variance of the Doppler velocity estimates can be well predicted from theory and were also estimated directly from the observed correlation between the H-polarized and V-polarized successive pulses. The study represents a key milestone towards the implementation of polarization diver sity in Doppler space-borne radars.

scholarly journals Typhoon rainstorm simulations with radar data assimilation on the southeast coast of China

2021 ◽  
Vol 21 (2) ◽  
pp. 723-742
Author(s):  
Jiyang Tian ◽  
Ronghua Liu ◽  
Liuqian Ding ◽  
Liang Guo ◽  
Bingyu Zhang
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Radar Data ◽  
Time Interval ◽  
Storm Events ◽  
Catchment Scale ◽  
Southeast Coast ◽  
Assimilation Time ◽  
Radar Data Assimilation

Abstract. As an effective technique to improve the rainfall forecast, data assimilation plays an important role in meteorology and hydrology. The aim of this study is to explore the reasonable use of Doppler radar data assimilation to correct the initial and lateral boundary conditions of the numerical weather prediction (NWP) systems. The Weather Research and Forecasting (WRF) model is applied to simulate three typhoon storm events on the southeast coast of China. Radar data from a Doppler radar station in Changle, China, are assimilated with three-dimensional variational data assimilation (3-DVar) model. Nine assimilation modes are designed by three kinds of radar data and at three assimilation time intervals. The rainfall simulations in a medium-scale catchment, Meixi, are evaluated by three indices, including relative error (RE), critical success index (CSI), and root mean square error (RMSE). Assimilating radial velocity at a time interval of 1 h can significantly improve the rainfall simulations, and it outperforms the other modes for all the three storm events. Shortening the assimilation time interval can improve the rainfall simulations in most cases, while assimilating radar reflectivity always leads to worse simulations as the time interval shortens. The rainfall simulations can be improved by data assimilation as a whole, especially for the heavy rainfall with strong convection. The findings provide references for improving the typhoon rainfall forecasts at catchment scale and have great significance on typhoon rainstorm warning.

scholarly journals Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advanced Research Hurricane WRF (AHW) Model

2009 ◽  
Vol 137 (9) ◽  
pp. 2758-2777 ◽  
Author(s):  
Qingnong Xiao ◽  
Xiaoyan Zhang ◽  
Christopher Davis ◽  
John Tuttle ◽  
Greg Holland ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Initial Time ◽  
Forecast Errors ◽  
Hurricane Wrf ◽  
The Impact ◽  
Airborne Doppler Radar

Abstract Initialization of the hurricane vortex in weather prediction models is vital to intensity forecasts out to at least 48 h. Airborne Doppler radar (ADR) data have sufficiently high horizontal and vertical resolution to resolve the hurricane vortex and its imbedded structures but have not been extensively used in hurricane initialization. Using the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation (3DVAR) system, the ADR data are assimilated to recover the hurricane vortex dynamic and thermodynamic structures at the WRF model initial time. The impact of the ADR data on three hurricanes, Jeanne (2004), Katrina (2005) and Rita (2005), are examined during their rapid intensification and subsequent weakening periods before landfall. With the ADR wind data assimilated, the three-dimensional winds in the hurricane vortex become stronger and the maximum 10-m winds agree better with independent estimates from best-track data than without ADR data assimilation. Through the multivariate incremental structure in WRF 3DVAR analysis, the central sea level pressures (CSLPs) for the three hurricanes are lower in response to the stronger vortex at initialization. The size and inner-core structure of each vortex are adjusted closer to observations of these attributes. Addition of reflectivity data in assimilation produces cloud water and rainwater analyses in the initial vortex. The temperature and moisture are also better represented in the hurricane initialization. Forty-eight-hour forecasts are conducted to evaluate the impact of ADR data using the Advanced Research Hurricane WRF (AHW), a derivative of the Advanced Research WRF (ARW) model. Assimilation of ADR data improves the hurricane-intensity forecasts. Vortex asymmetries, size, and rainbands are also simulated better. Hurricane initialization with ADR data is quite promising toward reducing intensity forecast errors at modest computational expense.

scholarly journals Retieving antenna miss-pointing for vertical pointing cloud radar and correcting the introduced Doppler velocity errors in the measurements

2021 ◽  
Author(s):  
Lukas Pfitzenmaier ◽  
Pavlos Kollias ◽  
Ulrich Löhnert
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Convective Motion ◽  
Doppler Velocity ◽  
Velocity Measurements ◽  
Wind Fields ◽  
Satellite Mission ◽  
Fall Velocity ◽  
Particle Sedimentation ◽  
Retrieval Technique

<p>In the last decades, Doppler velocity measurements from zenith pointing radars have evolved to a standard radar variable. Measuring Doppler velocities allow estimating particle sedimentation or fall velocity of hydrometeors and thus offer key information to evaluate micro-physical parametrizations in numerical weather prediction models. In the future, the joint ESA-JAXA satellite mission EarthCARE features the first Doppler capable 94-GHz Cloud Profiling Radar (CPR), with enhanced sensitivity and improved resolution compared to the CloudSat CPR. These features, especially the Doppler velocity measurements, are expected to improve the CPR-based microphysical retrievals in clouds and precipitation and for the first time provide information about convective motion in clouds.</p><p>To evaluate EarthCare CPR Doppler velocity from the ground, the Doppler velocity from five ground-based zenith pointing 94 GHz radar spread over Europa should be used in future. To increase the quality of the measured Doppler velocity the antenna miss-pointing has to be estimated. Unknown antenna miss-pointing is the main source of error in Doppler velocity measurements and can reach values on the same order as the fall velocity of pristine ice crystals. Knowing the angle of miss-pointing, the error in the measured Doppler velocity measurements can be corrected and the precision and quality improved. This is especially important for cases where Doppler velocity values are direct input for retrievals, which, e.g., employ multiple radar sensors with matching sampling(?) volumes.</p><p>Within this work we will present a retrieval technique to identify the angle of antenna miss-pointing for ground-based radar profilers and correct the measured Doppler velocity values. The retrieval technique is a statistical method requiring the uncorrected Doppler velocity measurements and additional wind information from reanalysis or in parallel measuring sensors. Evaluation of the retrieval was done using different wind input data sets, e.g., ECMWF IFS wind fields or retrieved wind information from Radar scans. Also, the retrieval was used to correct the miss-pointing angles of two in parallel measuring zenith pointing radars and, therefore, correct the velocity errors in dual Doppler velocity field.  </p>

scholarly journals A Quality Control Concept for Radar Reflectivity, Polarimetric Parameters, and Doppler Velocity

2006 ◽  
Vol 23 (7) ◽  
pp. 865-887 ◽  
Author(s):  
Katja Friedrich ◽  
Martin Hagen ◽  
Thomas Einfalt
Keyword(s):  
Quality Control ◽  
Quality Index ◽  
Prediction Models ◽  
Weather Prediction ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Doppler Velocity ◽  
Control Procedure ◽  
End User ◽  
Weather Situation

Abstract Over the last few years the use of weather radar data has become a fundamental part of various applications like rain-rate estimation, nowcasting of severe weather events, and assimilation into numerical weather prediction models. The increasing demand for radar data necessitates an automated, flexible, and modular quality control. In this paper a quality control procedure is developed for radar reflectivity factors, polarimetric parameters, and Doppler velocity. It consists of several modules that can be extended, modified, and omitted depending on the user requirement, weather situation, and radar characteristics. Data quality is quantified on a pixel-by-pixel basis and encoded into a quality-index field that can be easily interpreted by a nontrained end user or an automated scheme that generates radar products. The quality-index algorithms detect and quantify the influence of beam broadening, the height of the first radar echo, ground clutter contamination, return from non-weather-related objects, and attenuation of electromagnetic energy by hydrometeors on the quality of the radar measurement. The quality-index field is transferred together with the radar data to the end user who chooses the amount of data and the level of quality used for further processing. The calculation of quality-index fields is based on data measured by the polarimetric C-band Doppler radar (POLDIRAD) located in the Alpine foreland in southern Germany.

scholarly journals An Observational Case for the Prevalence of Roll Vortices in the Hurricane Boundary Layer*

2005 ◽  
Vol 62 (8) ◽  
pp. 2662-2673 ◽  
Author(s):  
Ian Morrison ◽  
Steven Businger ◽  
Frank Marks ◽  
Peter Dodge ◽  
Joost A. Businger
Keyword(s):  
Boundary Layer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Doppler Velocity ◽  
Velocity Data ◽  
Roll Vortices ◽  
Secondary Circulations ◽  
Velocity Anomalies ◽  
The Mean ◽  
Hurricane Boundary Layer

Abstract Doppler velocity data from Weather Surveillance Radar-1988 Doppler (WSR-88D) radars during four hurricane landfalls are analyzed to investigate the presence of organized vortices in the hurricane boundary layer (HBL). The wavelength, depth, magnitude, and track of velocity anomalies were compiled through analysis of Doppler velocity data. The analysis reveals alternating bands of enhanced and reduced azimuthal winds closely aligned with the mean wind direction. Resulting statistics provide compelling evidence for the presence of organized secondary circulations or boundary layer rolls across significant areas during four hurricane landfalls. The results confirm previous observations of the presence of rolls in the HBL. A potential limitation of the study presented here is the resolution of the WSR-88D data. In particular, analysis of higher-resolution data (e.g., from the Doppler on Wheels) is needed to confirm that data aliasing has not unduly impacted the statistics reported here. Momentum fluxes associated with the secondary circulations are estimated using the covariance between the horizontal and vertical components of the wind fluctuations in rolls, with resulting fluxes 2–3 times greater than estimated by parameterizations in numerical weather prediction models. The observational analysis presented here, showing a prevalence of roll vortices in the HBL, has significant implications for the vertical transport of energy in hurricanes, for the character of wind damage, and for improvements in numerical simulations of hurricanes.

Sign in / Sign up

Export Citation Format

Share Document