Improvement of the early detection and quantitative risk prediction method with the three-dimensional wind field from multiple-doppler radar analysis

2021 ◽  
Author(s):  
Hwa-yeon Kim ◽  
Eiichi Nakakita
Keyword(s):  
Early Detection ◽  
Risk Prediction ◽  
Wind Field ◽  
Heavy Rainfall ◽  
Doppler Radar ◽  
Prediction Method ◽  
Risk Level ◽  
Doppler Velocity ◽  
Maximum Rainfall ◽  
Vertical Vorticity

<p> The localized severe heavy rainfalls, which has not been experienced in the past, have frequently occurred in Japan due to the effects of climate change. Especially, the Guerrilla heavy rainfall (abbreviated as GHR) by isolated rapidly growing single cumulonimbus is triggering flash floods in a small river basin and has caused huge damage to human life and property. If we alert the hazardous rainfall in 5 to 10 min earlier for evacuation, we could minimize human injuries such as isolation, death, and disappearance. For hydrometeorological disaster prevention, a system of the early detection and quantitative risk prediction methods is necessary to detect the initial stage of a cumulonimbus cloud before it is generated into heavy rainfall. In previous research, by analyzing the volume scan with some heavy rainfall events, an important sign named as the first echo (Baby-rain cell) was verified. Also, the vertical vortex tubes with positive and negative pairs did exist in the GHR. Most of the severely developed storm had a certain criterion of vertical vorticity. By using those analyses, we developed the early detection and quantitative risk prediction method as follows. We collect the radar variables (i.e. the vorticity, doppler velocity, and reflectivity, etc.) at each event and set the risk level when the maximum rainfall reached the ground. Then, we select an appropriate set of explaining variables considering the risk level. With the Receiver Operating Characteristic (ROC) analysis, we could find the most appropriate method to predict the risk level. However, we would like to improve the early detection and quantitative risk prediction method by estimating vertical vorticity, divergence and convergence with real wind field data. So, we apply the multiple-doppler radar analysis to estimate the variables reflecting real phenomena. As a result, the improved early detection and quantitative risk prediction method could predict the risk of GHR development accurately by using only the observed radar data. It is expected that the quantitative risk prediction could represent realistic flood prediction system and increase the leading time enough to reduce disaster.</p>

Reducing Errors in Velocity–Azimuth Display (VAD) Wind and Deformation Retrievals from Airborne Doppler Radars in Convective Environments

2020 ◽  
Vol 37 (12) ◽  
pp. 2251-2266
Author(s):  
Charles N. Helms ◽  
Matthew L. Walker McLinden ◽  
Gerald M. Heymsfield ◽  
Stephen R. Guimond
Keyword(s):  
Wind Field ◽  
Doppler Radar ◽  
Weighting Function ◽  
Deep Convection ◽  
Absolute Error ◽  
Doppler Velocity ◽  
Wind Fields ◽  
Time Data ◽  
Single Antenna ◽  
Median Absolute Error

AbstractThe present study describes methods to reduce the uncertainty of velocity–azimuth display (VAD) wind and deformation retrievals from downward-pointing, conically scanning, airborne Doppler radars. These retrievals have important applications in data assimilation and real-time data processing. Several error sources for VAD retrievals are considered here, including violations to the underlying wind field assumptions, Doppler velocity noise, data gaps, temporal variability, and the spatial weighting function of the VAD retrieval. Specific to airborne VAD retrievals, we also consider errors produced due to the radar scans occurring while the instrument platform is in motion. While VAD retrievals are typically performed using data from a single antenna revolution, other strategies for selecting data can be used to reduce retrieval errors. Four such data selection strategies for airborne VAD retrievals are evaluated here with respect to their effects on the errors. These methods are evaluated using the second hurricane nature run numerical simulation, analytic wind fields, and observed Doppler radar radial velocities. The proposed methods are shown to reduce the median absolute error of the VAD wind retrievals, especially in the vicinity of deep convection embedded in stratiform precipitation. The median absolute error due to wind field assumption violations for the along-track and for the across-track wind is reduced from 0.36 to 0.08 m s−1 and from 0.35 to 0.24 m s−1, respectively. Although the study focuses on Doppler radars, the results are equally applicable to conically scanning Doppler lidars as well.

scholarly journals Nonlinear Wind Analysis of Single-Doppler Radar Observations within a DVAD Framework

2015 ◽  
Vol 54 (7) ◽  
pp. 1538-1555
Author(s):  
Xiaowen Tang ◽  
Wen-Chau Lee ◽  
Yuan Wang
Keyword(s):  
Least Squares ◽  
Wind Field ◽  
Traditional Method ◽  
Doppler Radar ◽  
Polynomial Function ◽  
Doppler Velocity ◽  
Robust Performance ◽  
Radar Observations ◽  
Least Squares Fitting ◽  
One Step

AbstractThe application of the distance velocity azimuth display (DVAD) method to the retrieval of vertical wind profiles from single-Doppler radar observations is presented in this study. It was shown that Doppler velocity observations at a constant altitude can be expressed as a single polynomial function for both linear and nonlinear wind fields in DVAD. Only a one-step least squares fitting of a polynomial function is required to obtain the vertical wind profile of a real wind field. The mathematic formulation of DVAD results in two advantages over the traditional nonlinear VAD method used for the nonlinear analysis of single-Doppler observations. First, the requirement of only one-step least squares fitting leads to robust performance when Doppler velocity observations are contaminated by unevenly distributed data noise and voids. Second, the degree of nonlinearity to properly represent a real wind field can be directly estimated in DVAD instead of being empirically determined in the traditional method. A proper nonlinear wind model for approximating the real wind field can be objectively derived using the DVAD method. The merits of DVAD as a quantitative single-Doppler analysis method were compared with the traditional method using both idealized and real datasets. Results show that the simplicity and robust performance of DVAD make it a good candidate for single-Doppler retrieval in operational use.

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.

scholarly journals VDRF: Sensing the defect information to risk level of vehicle recall based on bert communication model

2020 ◽  
Vol 17 (3) ◽  
pp. 795-817
Author(s):  
Xindong You ◽  
Jiangwei Ma ◽  
Yuwen Zhang ◽  
Xueqiang Lv ◽  
Junmei Han
Keyword(s):  
Product Quality ◽  
Risk Prediction ◽  
Traditional Method ◽  
Prediction Method ◽  
Risk Level ◽  
Communication Model ◽  
Dynamic Information ◽  
Personal A

The recall of defective automobile products is one of the important measures to promote the quality of product quality and protect consumers' pyhsical safety and property security. In order to assess the risk level of defect cases, automobile recall management experts need to analyze and discuss the defect information by personal. A risk level prediction method based on language pre-training Bert model is proposed in this paper, which can transform the defect information into rick level of the vehicle and then predict vehicle recall automatically, in which a seq2seq model is proposed to multi-label the vehicle complaint data. The outputs of the seq2seq model combined with other static and dynamic information are used as the input of the Bert communication model. Substantial comparative experiments of different feature combinations on different methods show that the proposed VDRF method achieves F1 value with 79% in vehicle recall risk prediction, which outperforms the traditional method.

A Variational Correction Method as an Alternative to Forced Rejection of Sidelobe-Contaminated Bistatic Doppler Measurements

2008 ◽  
Vol 25 (11) ◽  
pp. 1939-1954 ◽  
Author(s):  
Michel Chong ◽  
Nabil Lamrani ◽  
Martin Hagen
Keyword(s):  
Wind Field ◽  
Doppler Radar ◽  
Weighted Average ◽  
Correction Method ◽  
Field Analysis ◽  
Squall Line ◽  
Doppler Velocity ◽  
Line System ◽  
Radar Network ◽  
Individual Volume

Abstract The problem of sidelobe contamination of bistatic apparent Doppler velocity measurements involved in a bistatic Doppler radar network is examined. So far in the context of 3D wind field analysis, by combining a traditional Doppler radar with one or more bistatic receivers, identification and hence removal of regions of high degrees of contamination were necessarily crucial steps to obtaining reliable wind fields. This study proposes an alternative solution to the forced rejection of bistatic Doppler data suspected to be contaminated by sidelobe echoes, on the basis of restoring the nonmeasured “actual” (i.e., noncontaminated) bistatic Doppler velocity from both monostatic radar and bistatic receiver measurements. The correction method is based on a modeled expression of the observed bistatic apparent Doppler velocity defined as the reflectivity-weighted average of actual Doppler velocity of particles within individual volume samples, including the antenna gain pattern of both transmitting and receiving radars. The searched actual Doppler velocity is a solution of an underdetermined inverse problem that can be handled as a constrained linear inversion problem, through a variational least squares analysis method. The performances of the proposed method are analyzed, using simulated radar observations involving one remote receiver. An example of application to experimental data collected by the Deutsches Zentrum für Luft und Raumfahrt (DLR) bistatic Doppler radar network within a moderate precipitation system observed on 8 May 2000 in Germany is also presented. Pseudo-Doppler observations of a tropical squall-line system are used to quantify the effective improvement of the correction method on the bistatic Doppler velocity and hence the retrieved 3D wind field. Statistics of the differences are presented between observed and idealized (sidelobe free) velocity structures on the one hand, and corrected and idealized velocity structures on the other hand. Clearly shown is the very low level of the corrected minus idealized differences (mean and standard deviation) against the significantly high level of the observed minus idealized differences. As previously observed, maximum correction occurs in regions of potentially high gradients of reflectivity. It is also found that regions of low observed minus idealized differences remain unchanged after correction, which means that the sidelobe-correction method only acts on needed regions and does not introduce any artificial modification.

scholarly journals Single-Doppler Velocity Retrieval of the Wind Field in a Tornadic Supercell Using Mobile, Phased-Array, Doppler Radar Data

2018 ◽  
Vol 35 (8) ◽  
pp. 1649-1663 ◽  
Author(s):  
Yu-Chieng Liou ◽  
Howard B. Bluestein ◽  
Michael M. French ◽  
Zachary B. Wienhoff
Keyword(s):  
Temporal Resolution ◽  
Wind Field ◽  
Phased Array ◽  
Doppler Radar ◽  
Radar Data ◽  
Moving Frame ◽  
Doppler Velocity ◽  
High Temporal Resolution ◽  
Wind Component ◽  
Using Data

AbstractA three-dimensional data assimilation (3DVar) least squares–type single-Doppler velocity retrieval (SDVR) algorithm is utilized to retrieve the wind field of a tornadic supercell using data collected by a mobile, phased-array, Doppler radar [Mobile Weather Radar (MWR) 05XP] with very high temporal resolution (6 s). It is found that the cyclonic circulation in the hook-echo region can be successfully recovered by the SDVR algorithm. The quality of the SDVR analyses is evaluated by dual-Doppler syntheses using data collected by two mobile Doppler radars [Doppler on Wheels 6 and 7 (DOW6 and DOW7, respectively)]. A comparison between the SDVR analyses and dual-Doppler syntheses confirms the conclusion reached by an earlier theoretical analysis that because of the temporally discrete nature of the radar data, the wind speed retrieved by single-Doppler radar is always underestimated, and this underestimate occurs more significantly for the azimuthal (crossbeam) wind component than for the radial (along beam) component. However, the underestimate can be mitigated by increasing the radar data temporal resolution. When the radar data are collected at a sufficiently high rate, the azimuthal wind component may be overestimated. Even with data from a rapid scan, phased-array, Doppler radar, our study indicates that it is still necessary to calculate the SDVR in an optimal moving frame of reference. Finally, the SDVR algorithm’s robustness is demonstrated. Even with a temporal resolution (2 min) much lower than that of the phased-array radar, the cyclonic flow structure in the hook-echo region can still be retrieved through SDVR using data observed by DOW6 or DOW7, although a difference in the retrieved fields does exist. A further analysis indicates that this difference is caused by the location of the radars.

Distance Velocity–Azimuth Display (DVAD)—New Interpretation and Analysis of Doppler Velocity

2014 ◽  
Vol 142 (2) ◽  
pp. 573-589 ◽  
Author(s):  
Wen-Chau Lee ◽  
Xiaowen Tang ◽  
Ben J.-D. Jou
Keyword(s):  
Wind Field ◽  
Doppler Radar ◽  
Flow Characteristics ◽  
Quadratic Equation ◽  
Doppler Velocity ◽  
Mathematical Framework ◽  
Conic Sections ◽  
Wind Fields ◽  
New Interpretation ◽  
Natural Way

Abstract The concept and mathematical framework of the distance velocity–azimuth display (DVAD) methodology is presented. DVAD uses rVd (Doppler velocity scaled by the distance from the radar to a gate, r) as the basis to display, interpret, and extract information from single Doppler radar observations. Both linear and nonlinear wind fields can be represented by the same Cartesian polynomial with different orders. DVAD is mathematically concise and superior to the velocity–azimuth display (VAD) in interpreting and deducing flow characteristics. The rVd pattern of a two-dimensional linear wind field is exclusively in the form of a bivariate quadratic equation representing conic sections (e.g., ellipse, parabola, and hyperbola) centered at the radar depending only on divergence and deformation. The presence of a constant background flow translates the conic sections to a different origin away from the radar. It is possible to graphically estimate the characteristics of a linear wind field from the conical sections without performing a VAD analysis. DVAD analysis can deduce quantitative flow characteristics by a least squares fitting and/or a derivative method, and is a natural way to account for nonlinearity. The rVd pattern behaves similar to a type of velocity potential in fluid mechanics where ∇(rVd) is a proxy of the true wind vector and is used to estimate the general flow pattern in the vicinity of the radar.

scholarly journals An Integrating Velocity–Azimuth Process Single-Doppler Radar Wind Retrieval Method

2007 ◽  
Vol 24 (4) ◽  
pp. 658-665 ◽  
Author(s):  
Xudong Liang
Keyword(s):  
Wind Field ◽  
Heavy Rainfall ◽  
Doppler Radar ◽  
Wind Profiler ◽  
Wind Fields ◽  
Retrieval Method ◽  
Wind Retrieval ◽  
Wind Analysis ◽  
Profiler Data ◽  
Surface Observations

Abstract Among the single-Doppler radar wind analysis methods, the velocity–azimuth display (VAD), velocity–azimuth process (VAP), and uniform-wind (UW) methods are widely used because of their simplicity. This paper shows that the VAD, VAP, and UW methods can all be derived from the same relationship based on the azimuthal uniform-wind assumption. Using this assumption, an integrating VAP (IVAP) method is developed that can provide a smoother wind field than the VAP and UW methods and a higher resolution than the VAD method. Using the IVAP technique, the wind fields associated with a heavy rainfall case in Shanghai, China, are retrieved and compared with those from surface observations and wind-profiler data.

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