Polarisation Radar Estimates of Rainfall: Correction of Errors Due to the Bright Band and to Anomalous Propagation

1992 ◽  
pp. 277-282 ◽  
Author(s):  
Anthony J. Illingworth ◽  
I. Jeff Caylor
Keyword(s):  
Bright Band ◽  
Anomalous Propagation

scholarly journals Bayesian Echo Classification for Australian Single-Polarization Weather Radar with Application to Assimilation of Radial Velocity Observations

2015 ◽  
Vol 32 (7) ◽  
pp. 1341-1355 ◽  
Author(s):  
S. J. Rennie ◽  
M. Curtis ◽  
J. Peter ◽  
A. W. Seed ◽  
P. J. Steinle ◽  
...  
Keyword(s):  
Weather Radar ◽  
Training Data ◽  
Training Dataset ◽  
Bayes Classifier ◽  
Threshold Method ◽  
Ground Clutter ◽  
Radar Network ◽  
Routine Monitoring ◽  
Single Polarization ◽  
Anomalous Propagation

AbstractThe Australian Bureau of Meteorology’s operational weather radar network comprises a heterogeneous radar collection covering diverse geography and climate. A naïve Bayes classifier has been developed to identify a range of common echo types observed with these radars. The success of the classifier has been evaluated against its training dataset and by routine monitoring. The training data indicate that more than 90% of precipitation may be identified correctly. The echo types most difficult to distinguish from rainfall are smoke, chaff, and anomalous propagation ground and sea clutter. Their impact depends on their climatological frequency. Small quantities of frequently misclassified persistent echo (like permanent ground clutter or insects) can also cause quality control issues. The Bayes classifier is demonstrated to perform better than a simple threshold method, particularly for reducing misclassification of clutter as precipitation. However, the result depends on finding a balance between excluding precipitation and including erroneous echo. Unlike many single-polarization classifiers that are only intended to extract precipitation echo, the Bayes classifier also discriminates types of nonprecipitation echo. Therefore, the classifier provides the means to utilize clear air echo for applications like data assimilation, and the class information will permit separate data handling of different echo types.

scholarly journals Anomalous Propagation Characteristics of Airy Beam in Nonlinear Kerr Media

Crystals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 879
Author(s):  
Li Shao ◽  
Yun-Long Wu ◽  
Qing Ye
Keyword(s):  
Bound States ◽  
Quasi Equilibrium ◽  
Spatial Solitons ◽  
Propagation Characteristics ◽  
Transform Method ◽  
Nonlinear Media ◽  
Kerr Media ◽  
Airy Beam ◽  
Normal Breathing ◽  
Anomalous Propagation

The propagation characteristics of a single Airy beam in nonlinear Kerr media were numerically investigated by utilizing the split-step Fourier transform method. We show that in addition to normal breathing solitons, the anomalous bound states of Airy spatial solitons can also be formed, which are similar to the states formed in the interaction between two Airy beams in nonlinear media. This quasi-equilibrium state is formed by the interaction of the main soliton beam and side lobes of Airy beam due to their different propagation trajectories in the nonlinear media. Moreover, it has been shown the Airy spatial solitons in tree structure can be formed by adjusting the initial parameters in the interaction between the Airy beam and Kerr media.

VISUAL ANALOGUE OF RADAR BRIGHT BAND PHENOMENON

Weather ◽  
1960 ◽  
Vol 15 (8) ◽  
pp. 277-279 ◽  
Author(s):  
B. Vonnegut ◽  
C. B. Moore ◽  
Arthur D. Little
Keyword(s):  
Bright Band

scholarly journals Correction of the bright band using dual-polarisation radar

2005 ◽  
Vol 6 (1) ◽  
pp. 40-46 ◽  
Author(s):  
M. A. Rico-Ramirez ◽  
I. D. Cluckie ◽  
D. Han
Keyword(s):  
Bright Band

Use of multifractals to detect anomalous propagation (AP) in weather radar

2000 ◽  
Author(s):  
Dimitrios Charalampidis ◽  
Takis Kasparis ◽  
Linwood Jones ◽  
Michael Georgiopoulos
Keyword(s):  
Weather Radar ◽  
Anomalous Propagation

scholarly journals Improved fuzzy logic method to distinguish between meteorological and non-meteorological echoes using C-band polarimetric radar data

2020 ◽  
Vol 13 (2) ◽  
pp. 537-551
Author(s):  
Shuai Zhang ◽  
Xingyou Huang ◽  
Jinzhong Min ◽  
Zhigang Chu ◽  
Xiaoran Zhuang ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Radar Data ◽  
Weak Signal ◽  
Post Processing ◽  
Algorithm Performance ◽  
Radar Echoes ◽  
Fuzzy Logic Method ◽  
Anomalous Propagation ◽  
Logic Method

Abstract. To obtain better performance of meteorological applications, it is necessary to distinguish radar echoes from meteorological and non-meteorological targets. After a comprehensive analysis of the computational efficiency and radar system characteristics, we propose a fuzzy logic method that is similar to the MetSignal algorithm; the performance of this method is improved significantly in weak-signal regions where polarimetric variables are severely affected by noise. In addition, post-processing is adjusted to prevent anomalous propagation at a far range from being misclassified as meteorological echo. Moreover, an additional fuzzy logic echo classifier is incorporated into post-processing to suppress misclassification in the melting layer. An independent test set is selected to evaluate algorithm performance, and the statistical results show an improvement in the algorithm performance, especially with respect to the classification of meteorological echoes in weak-signal regions.

scholarly journals Modelling of weather radar echoes from anomalous propagation using a hybrid parabolic equation method and NWP model data

2007 ◽  
Vol 7 (3) ◽  
pp. 391-398 ◽  
Author(s):  
D. Bebbington ◽  
S. Rae ◽  
J. Bech ◽  
B. Codina ◽  
M. Picanyol
Keyword(s):  
Parabolic Equation ◽  
Weather Prediction ◽  
Weather Radar ◽  
Equation Method ◽  
Index Structure ◽  
Entire Area ◽  
Parabolic Equation Method ◽  
Radar Echoes ◽  
Anomalous Propagation ◽  
Nwp Model

Abstract. Contamination of weather radar echoes by anomalous propagation (anaprop) mechanisms remains a serious issue in quality control of radar precipitation estimates. Although significant progress has been made identifying clutter due to anaprop there is no unique method that solves the question of data reliability without removing genuine data. The work described here relates to the development of a software application that uses a numerical weather prediction (NWP) model to obtain the temperature, humidity and pressure fields to calculate the three dimensional structure of the atmospheric refractive index structure, from which a physically based prediction of the incidence of clutter can be made. This technique can be used in conjunction with existing methods for clutter removal by modifying parameters of detectors or filters according to the physical evidence for anomalous propagation conditions. The parabolic equation method (PEM) is a well established technique for solving the equations for beam propagation in a non-uniformly stratified atmosphere, but although intrinsically very efficient, is not sufficiently fast to be practicable for near real-time modelling of clutter over the entire area observed by a typical weather radar. We demonstrate a fast hybrid PEM technique that is capable of providing acceptable results in conjunction with a high-resolution terrain elevation model, using a standard desktop personal computer. We discuss the performance of the method and approaches for the improvement of the model profiles in the lowest levels of the troposphere.

scholarly journals Typhoon 9707 observations with the MU radar and L-band boundary layer radar

2001 ◽  
Vol 19 (8) ◽  
pp. 925-931 ◽  
Author(s):  
M. Teshiba ◽  
H. Hashiguchi ◽  
S. Fukao ◽  
Y. Shibagaki
Keyword(s):  
Boundary Layer ◽  
Maximum Speed ◽  
Bright Band ◽  
Mu Radar ◽  
Tangential Wind ◽  
Typhoon Center ◽  
Meteorological Radar ◽  
L Band ◽  
Precipitating Clouds ◽  
Wind Behaviour

Abstract. Typhoon 9707 (Opal) was observed with the VHF-band Middle and Upper atmosphere (MU) radar, an L-band boundary layer radar (BLR), and a vertical-pointing C-band meteorological radar at the Shigaraki MU Observatory in Shiga prefecture, Japan on 20 June 1997. The typhoon center passed about 80 km southeast from the radar site. Mesoscale precipitating clouds developed due to warm-moist airmass transport from the typhoon, and passed over the MU radar site with easterly or southeasterly winds. We primarily present the wind behaviour including the vertical component which a conventional meteorological Doppler radar cannot directly observe, and discuss the relationship between the wind behaviour of the typhoon and the precipitating system. To investigate the dynamic structure of the typhoon, the observed wind was divided into radial and tangential wind components under the assumption that the typhoon had an axi-symmetric structure. Altitude range of outflow ascended from 1–3 km to 2–10 km with increasing distance (within 80–260 km range) from the typhoon center, and in-flow was observed above and below the outflow. Outflow and inflow were associated with updraft and downdraft, respectively. In the tangential wind, the maximum speed of counterclockwise winds was confirmed at 1–2 km altitudes. Based on the vertical velocity and the reflectivity obtained with the MU radar and the C-band meteorological radar, respectively, precipitating clouds, accompanied by the wind behaviour of the typhoon, were classified into stratiform and convective precipitating clouds. In the stratiform precipitating clouds, a vertical shear of radial wind and the maximum speed of counterclockwise wind were observed. There was a strong reflectivity layer called a ‘bright band’ around the 4.2 km altitude. We confirmed strong updrafts and down-drafts below and above it, respectively, and the existence of a relatively dry layer around the bright band level from radiosonde soundings. In the convective precipitating clouds, the regions of strong and weak reflectivities were well associated with those of updraft and downdraft, respectively.Key words. Meteorology and atmospheric dynamics (mesoscale meteorology; precipitation) Radio science (remote sensing)

Sign in / Sign up

Export Citation Format

Share Document