scholarly journals Prognostic Equation for Radar Radial Velocity Derived by Considering Atmospheric Refraction and Earth Curvature

2013 ◽  
Vol 70 (10) ◽  
pp. 3328-3338 ◽  
Author(s):  
Qin Xu ◽  
Li Wei
Keyword(s):  
Velocity Field ◽  
Radial Velocity ◽  
Doppler Radar ◽  
Slope Angle ◽  
Atmospheric Refraction ◽  
Prognostic Equation ◽  
Wind Analysis ◽  
Dynamic Constraint ◽  
Velocity Equation ◽  
Beam Height

Abstract The prognostic equation for the radial velocity field observed with a Doppler radar is derived to include the effects of atmospheric refraction and earth curvature on radar-beam height and slope angle. The derived equation, called the radial velocity equation, contains a high-order small term that can be truncated. The truncated radial velocity equation is shown to be much more accurate than its counterpart radial velocity equation derived without considering the effects of atmospheric refraction and earth curvature. The truncated equation has the same concise form as its counterpart radial velocity equation but remains to be sufficiently accurate as a useful dynamic constraint for radar wind analysis and assimilation (in normal situations) even up to the farthest 300-km radial range of operational Weather Surveillance Radar-1988 Doppler (WSR-88D) scans where its counterpart radial velocity equation becomes erroneous.

Impacts of 4DVAR Assimilation of Airborne Doppler Radar Observations on Numerical Simulations of the Genesis of Typhoon Nuri (2008)

2014 ◽  
Vol 53 (10) ◽  
pp. 2325-2343 ◽  
Author(s):  
Zhan Li ◽  
Zhaoxia Pu ◽  
Juanzhen Sun ◽  
Wen-Chau Lee
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Numerical Simulations ◽  
Doppler Radar ◽  
Initial Conditions ◽  
Radar Data ◽  
Radar Observations ◽  
Wind Analysis ◽  
The Impact ◽  
Airborne Doppler Radar

AbstractThe Weather Research and Forecasting Model and its four-dimensional variational data assimilation (4DVAR) system are employed to examine the impact of airborne Doppler radar observations on predicting the genesis of Typhoon Nuri (2008). Electra Doppler Radar (ELDORA) airborne radar data, collected during the Office of Naval Research–sponsored Tropical Cyclone Structure 2008 field experiment, are used for data assimilation experiments. Two assimilation methods are evaluated and compared, namely, the direct assimilation of radar-measured radial velocity and the assimilation of three-dimensional wind analysis derived from the radar radial velocity. Results show that direct assimilation of radar radial velocity leads to better intensity forecasts, as this process enhances the development of convective systems and improves the inner-core structure of Nuri, whereas assimilation of the radar-retrieved wind analysis is more beneficial for tracking forecasts, as it results in improved environmental flows. The assimilation of both the radar-retrieved wind and the radial velocity can lead to better forecasts in both intensity and tracking, if the radial velocity observations are assimilated first and the retrieved winds are then assimilated in the same data assimilation window. In addition, experiments with and without radar data assimilation led to developing and nondeveloping disturbances in numerical simulations of Nuri’s genesis. The improved initial conditions and forecasts from the data assimilation imply that the enhanced midlevel vortex and moisture conditions are favorable for the development of deep convection in the center of the pouch and eventually contribute to Nuri’s genesis. The improved simulations of the convection and associated environmental conditions produce enhanced upper-level warming in the core region and lead to the drop in sea level pressure.

Application of IVAP-Based Observation Operator in Radar Radial Velocity Assimilation: The Case of Typhoon Fitow

2017 ◽  
Vol 145 (10) ◽  
pp. 4187-4203 ◽  
Author(s):  
Feng Chen ◽  
Xudong Liang ◽  
Hao Ma
Keyword(s):  
Spatial Distribution ◽  
Radial Velocity ◽  
Doppler Radar ◽  
Tangential Velocity ◽  
Distribution Characteristics ◽  
Observation Operator ◽  
Spatial Distribution Characteristics ◽  
Tangential Wind ◽  
Analysis System ◽  
Background Fields

An improved Doppler radar radial velocity assimilation observation operator is proposed based on the integrating velocity–azimuth process (IVAP) method. This improved operator can ingest both radial wind and its spatial distribution characteristics to deduce the two components of the mean wind within a given area. With this operator, the system can be used to assimilate information from tangential wind and radial wind. On the other hand, because the improved observation operator is defined within a given area, which can be uniformly chosen in both the observation and analysis coordinate systems, it has a thinning function. The traditional observation operator and the improved observation operator, along with their corresponding data processing modules, were implemented in the community Gridpoint Statistical Interpolation analysis system (GSI) to demonstrate the superiority of the improved operator. The results of single analysis unit experiments revealed that the two operators are comparable when the analysis unit is small. When the analysis unit becomes larger, the analysis results of the improved operator are better than those of the traditional operator because the former can ingest more wind information than the latter. The results of a typhoon case study indicated that both operators effectively ingested radial wind information and produced more reasonable typhoon structures than those in the background fields. The tangential velocity relative to the radar was retrieved by the improved operator through ingesting tangential wind information from the spatial distribution characteristics of radial wind. Because of the improved vortex intensity and structure, obvious improvements were seen in both track and intensity predictions when the improved operator was used.

scholarly journals Assessment of Doppler Radar Radial Wind Observation Quality from Different Echo Sources for Assimilation during the Sydney 2014 Forecast Demonstration Project

2018 ◽  
Vol 35 (8) ◽  
pp. 1605-1620 ◽  
Author(s):  
Susan Rennie ◽  
Peter Steinle ◽  
Alan Seed ◽  
Mark Curtis ◽  
Yi Xiao
Keyword(s):  
Quality Control ◽  
Control System ◽  
Statistical Analysis ◽  
High Resolution ◽  
Radial Velocity ◽  
Numerical Weather Prediction ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Demonstration Project ◽  
Prediction System

AbstractA new quality control system, primarily using a naïve Bayesian classifier, has been developed to enable the assimilation of radial velocity observations from Doppler radar. The ultimate assessment of this system is the assimilation of observations in a pseudo-operational numerical weather prediction system during the Sydney 2014 Forecast Demonstration Project. A statistical analysis of the observations assimilated during this period provides an assessment of the data quality. This will influence how observations will be assimilated in the future, and what quality control and errors are applicable. This study compares observation-minus-background statistics for radial velocities from precipitation and insect echoes. The results show that with the applied level of quality control, these echo types have comparable biases. With the latest quality control, the clear air observations of wind are apparently of similar quality to those from precipitation and are therefore suitable for use in high-resolution NWP assimilation systems.

scholarly journals New light on the corrugation phenomenon in our Galaxy

1985 ◽  
Vol 106 ◽  
pp. 175-178
Author(s):  
J. V. Feitzinger ◽  
J. Spicker
Keyword(s):  
Velocity Field ◽  
Radial Velocity ◽  
Density Wave ◽  
Radial Expansion ◽  
Spiral Pattern ◽  
Mass Model ◽  
Wave Kinematics ◽  
Spiral Arm

This investigation presents a total picture of the well-known corrugation-phenomenon for the (heliocentric) longitude range 10° ≤ 1 ≤ 240° as derived from HI-studies. For each spiral arm of the spiral pattern of Simonson (1976), we derived the centroid of the HI distribution from the 21-cm line surveys of Weaver and Williams (1974), Sinha (1979), and Westerhout and Wendlandt (1982). The three-component mass model of Rohlfs and Kreitschmann (1981) was used to derive a radial-velocity field, which was supplemented by a radial expansion field and by density-wave kinematics. This combined field served to calculated kinematic distances. The warp was taken into account according to Henderson et al. (1982) and Kulkarni et al. (1982).

Accurate and Real-Time Pedestrian Classification Based on UWB Doppler Radar Images and Their Radial Velocity Features

2013 ◽  
Vol E96.B (10) ◽  
pp. 2563-2572 ◽  
Author(s):  
Kenshi SAHO ◽  
Takuya SAKAMOTO ◽  
Toru SATO ◽  
Kenichi INOUE ◽  
Takeshi FUKUDA
Keyword(s):  
Radial Velocity ◽  
Real Time ◽  
Doppler Radar ◽  
Radar Images

An Application of the Immersed Boundary Method for Recovering the Three-Dimensional Wind Fields over Complex Terrain Using Multiple-Doppler Radar Data

2012 ◽  
Vol 140 (5) ◽  
pp. 1603-1619 ◽  
Author(s):  
Yu-Chieng Liou ◽  
Shao-Fan Chang ◽  
Juanzhen Sun
Keyword(s):  
Radial Velocity ◽  
Immersed Boundary Method ◽  
Doppler Radar ◽  
Synthesis Method ◽  
Three Dimensional ◽  
Simulated Data ◽  
Radar Data ◽  
Immersed Boundary ◽  
Wind Fields ◽  
Boundary Method

This study develops an extension of a variational-based multiple-Doppler radar synthesis method to construct the three-dimensional wind field over complex topography. The immersed boundary method (IBM) is implemented to take into account the influence imposed by a nonflat surface. The IBM has the merit of providing realistic topographic forcing without the need to change the Cartesian grid configuration into a terrain-following coordinate system. Both Dirichlet and Neumann boundary conditions for the wind fields can be incorporated. The wind fields above the terrain are obtained by variationally adjusting the solutions to satisfy a series of weak constraints, which include the multiple-radar radial velocity observations, anelastic continuity equation, vertical vorticity equation, background wind, and spatial smoothness terms. Experiments using model-simulated data reveal that the flow structures over complex orography can be successfully retrieved using radial velocity measurements from multiple Doppler radars. The primary advantages of the original synthesis method are still maintained, that is, the winds along and near the radar baseline are well retrieved, and the resulting three-dimensional flow fields can be used directly for vorticity budget diagnosis. If compared with the traditional wind synthesis algorithm, this method is able to merge data from different sources, and utilize data from any number of radars. This provides more flexibility in designing various scanning strategies, so that the atmosphere may be probed more efficiently using a multiple-radar network. This method is also tested using the radar data collected during the Southwest Monsoon Experiment (SoWMEX), which was conducted in Taiwan from May to June 2008 with reasonable results being obtained.

scholarly journals Are there Giant Vortices near Solar Circle?

1996 ◽  
Vol 169 ◽  
pp. 597-604
Author(s):  
A.M. Fridman ◽  
O.V. Khoruzhii ◽  
V.V. Lyakhovich ◽  
V.S. Avedisova
Keyword(s):  
Velocity Field ◽  
Radial Velocity ◽  
Observational Data ◽  
Molecular Clouds ◽  
Young Stars ◽  
Solar Neighborhood ◽  
Line Of Sight ◽  
Spiral Arms ◽  
Corotation Radius ◽  
Theoretical Conception

The analysis of the observational line-of-sight radial velocity field of molecular clouds, connecting with young stars, has strengthened the Fridman's hypothesis (1994) on the possible existence of anticyclone in the solar neighborhood. Anticyclones are located near corotation radius of the observed spiral arms, a number of which is equal to a number of vortices. Our calculations show that the four-vortices model fits observational data fairly well.We shall not use any theoretical conception on the nature of spiral arms generation (bar, selfgravitational or hydrodynamical mechanisms, etc.). We shall base on the treatment of the observational data.

scholarly journals A Velocity Dealiasing Scheme Based on Minimization of Velocity Differences between Regions

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yue Yuan ◽  
Ping Wang ◽  
Di Wang ◽  
Junzhi Shi
Keyword(s):  
Radial Velocity ◽  
Wind Shear ◽  
Doppler Radar ◽  
Heavy Precipitation ◽  
Probability Of Detection ◽  
Strong Wind ◽  
Velocity Data ◽  
Step Velocity ◽  
Noise Data ◽  
Radial Velocity Data

The velocity dealiasing is an essential work of automatic weather phenomenon identification, nowcasting, and disaster monitoring based on radial velocity data. The noise data, strong wind shear, and isolated echo region in the Doppler radar radial velocity data severely interfere with the velocity dealiasing algorithm. This paper proposes a two-step velocity dealiasing algorithm based on the minimization of velocity differences between regions to solve this problem. The first step is to correct aliased velocities by minimizing the sum of gradients in every region to eliminate abnormal velocity gradients between points. The interference of noise data and strong wind shear can be reduced by minimizing the whole gradients in a region. The second step is to dealiase velocities by the velocity differences between different isolated regions. The velocity of an unknown isolated region is determined by the velocities of all known regions. This step improves the dealiasing results of isolated regions. In this paper, 604 volume scan samples, including typhoons, squall lines, and heavy precipitation, were used to test the algorithm. The statistical results and analysis show that the proposed algorithm can dealiase the velocity field with a high probability of detection and a low false alarm rate.

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.

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