Error Estimation in Wind Fields Derived from Dual-Doppler Radar Measurement

Doviak, Richard J.; Ray, Peter S.; Strauch, R. G.; Miller, L. Jay

doi:10.1175/1520-0450(1976)015<0868:eeiwfd>2.0.co;2

Cited by 103 publications

(68 citation statements)

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“…(Doviak et al 1976). To evaluate the impact of random errors, an experiment series WR is conducted in which V d data contains both velocity aliasing and random errors.…”

Section: ) Sensitivity To Random Error (Wr Series)mentioning

confidence: 99%

“…where PRF is the pulse repetition frequency and l is the wavelength of the radar (Doviak and Zrnic 2006). The measured Doppler velocity V d is related to the true velocity V u by…”

Section: Introductionmentioning

confidence: 99%

“…There are two main methods to tackle the aliasing problem: 1) the staggered pulse repetition frequency (PRF) technique (e.g., Doviak and Zrnic 2006) and the multiple PRF technique (Zittel and Wiegman 2005) implemented in selected Weather Surveillance Radar-1988 Doppler (WSR-88D) volume coverage patterns (VCPs), and 2) automated dealiasing algorithms (e.g., Bargen and Brown 1980;Bergen and Albers 1988;and others). For the majority of the Doppler radars in the world, using various dealiasing algorithms remains the only viable option.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Wang

Zhao

Lee

et al. 2012

Journal of Atmospheric and Oceanic Technology

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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.

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“…(Doviak et al 1976). To evaluate the impact of random errors, an experiment series WR is conducted in which V d data contains both velocity aliasing and random errors.…”

Section: ) Sensitivity To Random Error (Wr Series)mentioning

confidence: 99%

“…where PRF is the pulse repetition frequency and l is the wavelength of the radar (Doviak and Zrnic 2006). The measured Doppler velocity V d is related to the true velocity V u by…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Wang

Zhao

Lee

et al. 2012

Journal of Atmospheric and Oceanic Technology

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“…Several studies have investigated multi-Doppler wind retrieval uncertainties by identifying or utilizing (i) the importance of Doppler radar measurement errors and beam geometry (e.g., Doviak et al, 1976;Nelson and Brown, 1987;Matejka and Bartels, 1998;Bousquet et al, 2008), (ii) the influence of radar data objective analysis (e.g., Clark et al, 1980;Gal-Chen, 1982;Testud and Chong, 1983;Given and Ray, 1994;Majcen et al, 2008;Shapiro et al, 2010;Collis et al, 2010), and (iii) OSSEs (e.g., Fanyou and Jietai, 1994;Gao et al, 1999;Liou and Chang, 2009;Potvin et al, 2012b;Potvin and Wicker, 2012). However, few studies have compared practical retrieval performance to other independent air motion estimates from aircraft or ground-based profiling radars (e.g., Collis et al, 2013;Newsom et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E

et al. 2017

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Abstract. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with those from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-meansquare differences between the two sources are of the order of 1 and 2 m s −1 , respectively, and time-height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s −1 . The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. The results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.

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“…This can be achieved via the retrieval of three-dimensional wind velocity using dual-or multiple-Doppler wind analysis. This method was first proposed by Armijo (1969) and various multiple-Doppler wind analysis procedures have been developed and evaluated subsequently (e.g., Ray et al 1975Ray et al , 1978Ray et al , 1980Doviak et al 1976;Bousquet and Chong 1998;Shapiro and Mewes 1999;Gao et al 1999Gao et al , 2004Liou and Chang 2009;Shapiro et al 2009;Liou et al 2012;Potvin et al 2012a, b, c). Potvin et al (2012c) reported that the variational multiple-Doppler wind analysis proposed by Gao et al (1999) is more accurate than the multiple-Doppler wind analysis that explicitly integrates the continuity equation vertically, such as that by Ray et al (1980).…”

Section: Introductionmentioning

confidence: 99%

Impact of Observation Operators on Low-Level Wind Speed Retrieved by Variational Multiple-Doppler Analysis

Shimose

Shimizu

Maesaka

et al. 2016

SOLA

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This study investigated the impact of observation operators on low-level wind speed analysis. An evaluation of wind speeds retrieved by variational multiple-Doppler analyses using radial velocities (V r ) based on the formats of both a Plan Position Indicator (PPI) (hereafter, PPI-VAR) and a Constant Altitude Plan Position Indicator (CAPPI) (hereafter, CAPPI-VAR) was performed for comparison with wind speeds observed by a wind profiler during the warm season of three consecutive years. The statistical analysis showed that PPI-VAR was more accurate than CAPPI-VAR at 500 m above ground level (AGL). The error of CAPPI-VAR at 500 m AGL was caused by a representative error of CAPPI-formatted V r derived from a certain radar whose beam height was far from the analysis level, and this error became more obvious the greater the vertical difference in wind speed across the analysis level. CAPPI-VAR uses CAPPI-formatted V r from each radar equally; thus, the representative error might cause performance degradation of CAPPI-VAR at 500 m AGL. Conversely, PPI-VAR uses PPI-formatted V r from each radar with appropriate weighting based on the beam height distance from the analysis level. PPI-VAR showed better results at 500 m AGL because the observation grid points were dense around 500 m AGL.

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Error Estimation in Wind Fields Derived from Dual-Doppler Radar Measurement

Cited by 103 publications

References 0 publications

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

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

Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E

Impact of Observation Operators on Low-Level Wind Speed Retrieved by Variational Multiple-Doppler Analysis

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