scholarly journals Clutter and rainfall discrimination by means of doppler-polarimetric measurements and vertical reflectivity profile analysis

2005 ◽  
Vol 2 ◽  
pp. 135-138 ◽  
Author(s):  
F. Silvestro ◽  
N. Rebora ◽  
L. Ferraris ◽  
M. Morando ◽  
P. Alberoni ◽  
...  
Keyword(s):  
Profile Analysis ◽  
Rainfall Rate ◽  
Propagation Condition ◽  
Preliminary Results ◽  
Ground Clutter ◽  
Radar Scattering ◽  
Clutter Removal ◽  
Anomalous Propagation ◽  
Scattering Volume ◽  
High Topography

Abstract. The estimation of rainfall rate and other parameters from radar scattering volume is heavily affected by the presence of intense sea and ground clutter and echoes which appears in anomalous propagation condition. To deal with these non meteorological echoes we present a new clutter removal algorithm which combines the results of previous works. The algorithm fully exploits both the Doppler and polarimetric capabilities of the radar used and the analysis of vertical reflectivity profile in order to achieve the better identification of the meteorological and non-meteorological targets. The algorithm has been applied to the C-band radar of Monte Settepani (Savona, Italy), which runs in a high-topography environment. Preliminary results are presented.

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.

Preliminary Results of Neutron Transport in Blanket Module by MCNP with Profile Analysis Using Imaging Plate

2019 ◽  
Vol 75 (6) ◽  
pp. 487-492 ◽  
Author(s):  
Yasuyuki Ogino ◽  
Keisuke Mukai ◽  
Juro Yagi ◽  
Satoshi Konishi
Keyword(s):  
Profile Analysis ◽  
Neutron Transport ◽  
Imaging Plate ◽  
Preliminary Results

scholarly journals A Deep JI Survey of the Pleiades for Freely-Floating Superplanets and Brown Dwarfs at the Deuterium Burning Limit

2003 ◽  
Vol 211 ◽  
pp. 185-186
Author(s):  
M. J. Schwartz ◽  
E. E. Becklin ◽  
B. Zuckerman
Keyword(s):  
Energy Distribution ◽  
Proper Motion ◽  
Near Infrared ◽  
Profile Analysis ◽  
Spectral Energy Distribution ◽  
Brown Dwarfs ◽  
Spectral Energy ◽  
Preliminary Results ◽  
Methane Absorption ◽  
Lower Limits

We present preliminary results from a deep near-infrared J-band and I-band photometric survey of the Pleiades for freely-floating superplanets and brown dwarfs (BD) near the deuterium burning limit (DBL). With limiting magnitudes of J=20.5 and I=23.5, we have selected candidate Pleiads on the basis of evolutionary tracks, color-magnitudes, and I-J color lower limits (non-detections at deep I-band). Likelihoods of membership will be ultimately determined by a combination of image profile analysis, spectral energy distribution, proper motion, and low-resolution measurements of near-infrared water and/or methane absorption slopes. If confirmed, our faintest candidates are predicted to have made the transition from L to T spectral types with temperatures down to 820 K, and masses approaching 10 MJup.

A VHF interferometry system for detecting anomalous propagation of FM radio broadcasting waves related to earthquakes and some preliminary results

2013 ◽  
Vol 183 (1) ◽  
pp. 16-24
Author(s):  
Nozomi Ohno ◽  
Yuka Tone ◽  
Katsumi Hattori ◽  
Isao Yamamoto ◽  
Shin Shimakura ◽  
...  
Keyword(s):  
Preliminary Results ◽  
Radio Broadcasting ◽  
Fm Radio ◽  
Anomalous Propagation

A Technique to Censor Biological Echoes in Radar Reflectivity Data

2010 ◽  
Vol 49 (3) ◽  
pp. 453-462 ◽  
Author(s):  
Valliappa Lakshmanan ◽  
Jian Zhang ◽  
Kenneth Howard
Keyword(s):  
Biological Species ◽  
Radar Reflectivity ◽  
Local Characteristic ◽  
Vertical Profiles ◽  
Biological Targets ◽  
Local Texture ◽  
Ground Clutter ◽  
Biological Contaminants ◽  
Anomalous Propagation ◽  
Reflectivity Data

Abstract Existing techniques of quality control of radar reflectivity data rely on local texture and vertical profiles to discriminate between precipitating echoes and nonprecipitating echoes. Nonprecipitating echoes may be due to artifacts such as anomalous propagation, ground clutter, electronic interference, sun strobe, and biological contaminants (i.e., birds, bats, and insects). The local texture of reflectivity fields suffices to remove most artifacts, except for biological echoes. Biological echoes, also called “bloom” echoes because of their circular shape and expanding size during the nighttime, have proven difficult to remove, especially in peak migration seasons of various biological species, because they can have local and vertical characteristics that are similar to those of stratiform rain or snow. In this paper, a technique is described that identifies candidate bloom echoes based on the range variance of reflectivity in areas of bloom and uses the global, rather than local, characteristic of the echo to discriminate between bloom and rain. Every range gate is assigned a probability that it corresponds to bloom using morphological (shape based) operations, and a neural network is trained using this probability as one of the input features. It is demonstrated that this technique is capable of identifying and removing echoes due to biological targets and other types of artifacts while retaining echoes that correspond to precipitation.

Prediction of radar coverage under anomalous propagation condition for a typical coastal site: A case study

Radio Science ◽  
1991 ◽  
Vol 26 (4) ◽  
pp. 909-919 ◽  
Author(s):  
Samir Hussain Abdul-Jauwad ◽  
Pervez Zahir Khan ◽  
Talal Omar Halawani
Keyword(s):  
Propagation Condition ◽  
Coastal Site ◽  
Anomalous Propagation

scholarly journals Dual-Polarized Radar Coverage in Terminal Airspaces and Its Effect on Interpretation of Winter Weather Signatures: Current Capabilities and Future Recommendations

2019 ◽  
Vol 58 (1) ◽  
pp. 165-183
Author(s):  
Heather Dawn Reeves ◽  
Jacqueline Waters
Keyword(s):  
Data Mining ◽  
Three Dimensional ◽  
Common Occurrence ◽  
Ground Clutter ◽  
Use Of Data ◽  
Dual Polarized ◽  
Anomalous Propagation ◽  
Good Coverage ◽  
Beam Broadening

AbstractThis is a feasibility study on the use of dual-polarized radars to infer icing in terminal airspaces (TASs) of commercial airports. The amount and quality of radar coverage in each TAS is quantified as a function of its location, traffic, and vulnerability to icing. No airport has 100% of the TAS covered, but most high-traffic or high-icing airports have comparatively good coverage (between 70% and 90%). A common occurrence during icing is anomalous propagation as 79% of events had an inversion within the TAS. This leads to overestimates in the elevations of icing layers and can cause significant ground-clutter contamination, which can overwhelm the echo produced by precipitation. The effects of beam broadening were also considered. Typical dendrite growth and melting layers can only be resolved in part of the TAS part of the time, or not at all, as these layers are often shallower than the radar beam. Because most airports have coverage from multiple radars, use of a three-dimensional mosaic was investigated. This allows for an increase in the TAS coverage (generally between 5% and 15%) and partly mitigates some of the resolution issues, but the maxima within individual layers are somewhat reduced in the interpolation process. A series of recommendations is made to address the concerns raised by this investigation. These include using only icing tops (not bottoms) to identify areas of icing, use of data mining to retrieve precipitation echo in the presence of ground clutter, and including the beamwidth in radar mosaics.

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