A GIS-based methodology for the assessment of weather radar beam blockage in mountainous regions: two examples from the US NEXRAD network

Radar beam blockage is an important error source that affects the quality of weather radar data. An echo-filling network (EFnet) is proposed based on a deep learning algorithm to correct the echo intensity under the occlusion area in the Nanjing S-band new-generation weather radar (CINRAD/SA). The training dataset is constructed by the labels, which are the echo intensity at the 0.5° elevation in the unblocked area, and by the input features, which are the intensity in the cube including multiple elevations and gates corresponding to the location of bottom labels. Two loss functions are applied to compile the network: one is the common mean square error (MSE), and the other is a self-defined loss function that increases the weight of strong echoes. Considering that the radar beam broadens with distance and height, the 0.5° elevation scan is divided into six range bands every 25 km to train different models. The models are evaluated by three indicators: explained variance (EVar), mean absolute error (MAE), and correlation coefficient (CC). Two cases are demonstrated to compare the effect of the echo-filling model by different loss functions. The results suggest that EFnet can effectively correct the echo reflectivity and improve the data quality in the occlusion area, and there are better results for strong echoes when the self-defined loss function is used.

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Effects of Atmospheric Refraction on an Airborne Weather Radar Detection and Correction Method

Advances in Meteorology ◽

10.1155/2015/407867 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8

Author(s):

Lei Wang ◽

Ming Wei ◽

Tao Yang ◽

Ping Liu

Keyword(s):

Weather Radar ◽

Weather Conditions ◽

Refraction Index ◽

Correction Method ◽

Propagation Path ◽

Radar Detection ◽

Atmospheric Refraction ◽

Radar Beam ◽

Fitting Method ◽

Flight Parameters

This study investigates the effect of atmospheric refraction, affected by temperature, atmospheric pressure, and humidity, on airborne weather radar beam paths. Using three types of typical atmospheric background sounding data, we established a simulation model for an actual transmission path and a fitted correction path of an airborne weather radar beam during airplane take-offs and landings based on initial flight parameters and X-band airborne phased-array weather radar parameters. Errors in an ideal electromagnetic beam propagation path are much greater than those of a fitted path when atmospheric refraction is not considered. The rates of change in the atmospheric refraction index differ with weather conditions and the radar detection angles differ during airplane take-off and landing. Therefore, the airborne radar detection path must be revised in real time according to the specific sounding data and flight parameters. However, an error analysis indicates that a direct linear-fitting method produces significant errors in a negatively refractive atmosphere; a piecewise-fitting method can be adopted to revise the paths according to the actual atmospheric structure. This study provides researchers and practitioners in the aeronautics and astronautics field with updated information regarding the effect of atmospheric refraction on airborne weather radar detection and correction methods.

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Radar Quality Index for a Mosaic of Radar Reflectivity over Chao Phraya River Basin, Thailand

Applied Environmental Research ◽

10.35762/aer.2020.42.3.8 ◽

2020 ◽

pp. 92-104

Author(s):

Nattapon Mahavik ◽

Sarintip Tantanee

Keyword(s):

River Basin ◽

Quality Index ◽

Beam Propagation ◽

Weather Radar ◽

Radar Reflectivity ◽

Temporal Information ◽

Radar Beam ◽

Spatio Temporal ◽

Chao Phraya River ◽

Application Fields

The weather radar is one of the tools that can provide spatio-temporal information for nowcast which is useful for hydro-meteorological disasters warning and mitigation system. The ground-based weather radar can provide spatial and temporal information to monitor severe storm over the risky area. However, the usage of multiple radars can provide more effective information over large study area where single radar beam may be blocked by surrounding terrain Even though, the investigation of the sever storm physical characteristics needs the information from multiple radars, the mosaicked radar product has not been available for Thai researcher yet. In this study, algorithm of mosaicked radar reflectivity has been developed by using data from ground-based radar of Thai Meteorological Department over the Chao Phraya river basin in the middle of Thailand. The Python script associated with OpenCV and Wradlib libraries were used in our investigations of the mosaicking processes. The radar quality index (RQI) field has been developed by implementing an equation of a quality radar index to identify the reliability of each mosaicked radar reflectivity pixels. First, the percentage of beam blockage is computed to understand the radar beam propagation obstructed by surrounding topography in order to clarify the limitations of the observed beam on producing radar reflectivity maps. Second, the elevation of beam propagation associated with distance field has been computed. Then, these three parameters and the obtained percentage of beam blockage are utilized as the parameters in the equation of RQI. Finally, the detected radar flare, non-precipitating radar area, has been included to the RQI field. Then, the RQI field has been applied to the extracted radar reflectivity to evaluate the quality of mosaicked radar reflectivity to inform end user in any application fields over the Chao Phraya river basin.

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GuylinePC: An Interactive Guyline Tension Analysis Program for Guyed Logging Towers

Western Journal of Applied Forestry ◽

10.1093/wjaf/23.3.133 ◽

2008 ◽

Vol 23 (3) ◽

pp. 133-141

Author(s):

Matthew Thompson ◽

Henk Stander ◽

Sessions John

Keyword(s):

Pacific Northwest ◽

Optimization Methods ◽

Software Application ◽

Mountainous Regions ◽

The Us ◽

Cable Yarding ◽

Computer Based ◽

Steep Terrain ◽

Safety Considerations ◽

Tension Analysis

Abstract In the US Pacific Northwest and other mountainous regions, cable yarding using portable steel towers is a common harvesting system in steep terrain. These systems are expensive and can be unsafe if improperly rigged. For both economic and safety considerations, configurations are used that ensure that the system can sustain the forces applied during yarding operations. We present a computer-based application, GuylinePC, for evaluating the guyline and anchor loads resulting from an applied load. Our model extends the usability and scope of a model previously developed by other researchers. Specifically we (1) provide a more modern graphical user interface, (2) use optimization methods to determine equilibrium states, and (3) illustrate the capability of the program to be used in design. We briefly discuss the analytical model and software application and present a design problem. The program is intended to improve a forest engineer's understanding of cable yarding systems.

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The Sensitivity of Single Polarization Weather Radar Beam Blockage Correction to Variability in the Vertical Refractivity Gradient

Journal of Atmospheric and Oceanic Technology ◽

10.1175/1520-0426(2003)020<0845:tsospw>2.0.co;2 ◽

2003 ◽

Vol 20 (6) ◽

pp. 845-855 ◽

Cited By ~ 68

Author(s):

Joan Bech ◽

Bernat Codina ◽

Jeroni Lorente ◽

David Bebbington

Keyword(s):

Weather Radar ◽

Radar Beam ◽

Blockage Correction ◽

Single Polarization

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Detecting and Tracking Communal Bird Roosts in Weather Radar Data

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i01.5373 ◽

2020 ◽

Vol 34 (01) ◽

pp. 378-385

Author(s):

Zezhou Cheng ◽

Saadia Gabriel ◽

Pankaj Bhambhani ◽

Daniel Sheldon ◽

Subhransu Maji ◽

...

Keyword(s):

Latent Variable ◽

Weather Radar ◽

Radar Data ◽

Learning System ◽

Variable Model ◽

Detection Model ◽

Radar Images ◽

Biological Phenomena ◽

The Us ◽

Spatio Temporal

The US weather radar archive holds detailed information about biological phenomena in the atmosphere over the last 20 years. Communally roosting birds congregate in large numbers at nighttime roosting locations, and their morning exodus from the roost is often visible as a distinctive pattern in radar images. This paper describes a machine learning system to detect and track roost signatures in weather radar data. A significant challenge is that labels were collected opportunistically from previous research studies and there are systematic differences in labeling style. We contribute a latent-variable model and EM algorithm to learn a detection model together with models of labeling styles for individual annotators. By properly accounting for these variations we learn a significantly more accurate detector. The resulting system detects previously unknown roosting locations and provides comprehensive spatio-temporal data about roosts across the US. This data will provide biologists important information about the poorly understood phenomena of broad-scale habitat use and movements of communally roosting birds during the non-breeding season.

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Dynamical Weather Radar Beam Blockage Correction

2010 International Conference on Digital Manufacturing & Automation ◽

10.1109/icdma.2010.404 ◽

2010 ◽

Author(s):

Yaping Zhang ◽

Minghu Cheng

Keyword(s):

Weather Radar ◽

Radar Beam ◽

Blockage Correction

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Objective Optimization of Weather Radar Networks for Low-Level Coverage Using a Genetic Algorithm

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-11-00076.1 ◽

2012 ◽

Vol 29 (6) ◽

pp. 807-821 ◽

Cited By ~ 12

Author(s):

James M. Kurdzo ◽

Robert D. Palmer

Keyword(s):

Genetic Algorithm ◽

Lifetime Cost ◽

Optimization Technique ◽

Weather Radar ◽

The United States ◽

Analysis Tool ◽

Low Level ◽

Mountainous Regions ◽

Radar Network ◽

Radar Networks

Abstract The current Weather Surveillance Radar-1988 Doppler (WSR-88D) radar network is approaching 20 years of age, leading researchers to begin exploring new opportunities for a next-generation network in the United States. With a vast list of requirements for a new weather radar network, research has provided various approaches to the design and fabrication of such a network. Additionally, new weather radar networks in other countries, as well as networks on smaller scales, must balance a large number of variables in order to operate in the most effective way possible. To offer network designers an objective analysis tool for such decisions, a coverage optimization technique, utilizing a genetic algorithm with a focus on low-level coverage, is presented. Optimization is achieved using a variety of variables and methods, including the use of climatology, population density, and attenuation due to average precipitation conditions. A method to account for terrain blockage in mountainous regions is also presented. Various combinations of multifrequency radar networks are explored, and results are presented in the form of a coverage-based cost–benefit analysis, with considerations for total network lifetime cost.

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Assessment and quantification of meteorological data for implementation of weather radar in mountainous regions

MAUSAM ◽

10.54302/mausam.v67i4.1408 ◽

2021 ◽

Vol 67 (4) ◽

pp. 789-802

Author(s):

ALBAN KURIQI

Keyword(s):

Vertical Structure ◽

Meteorological Data ◽

Weather Radar ◽

Precipitation Variability ◽

The Other ◽

Screening Effect ◽

Mountainous Regions ◽

Ground Clutter ◽

The Future ◽

The City

The scope of this paper is to improve observation and detection of hydro-meteorological hazard over the Grenoble region which is characterised by significant changes of terrain in altitude and geomorphology. The city of Grenoble is located at a height between 200 up to 500 m, installing the weather radar in this range of elevation leads to better quality measurements, but visibility and as well coverage capability will be reduced at the other sites of the affected region. Two locations are shortlisted for the implementation of the future weather radar in Grenoble; (i) Moucherotte (1920 m a.s.l.) and (ii) Saint Eynard (1365 m a.s.l.). Several simulation and data analysis are performed to get the clear picture about precipitation variability by considering meteorological data from individual ground stations and radio sounding data as well. Compared to previous work, in this study is considered climatology of the vertical structure of the rainfall. In this context, several statistical computations are done regarding 0°C isotherm altitude. Concerning rainfall error estimation, ground clutter and screening effect, statistical calculations by using VISHYDRO code, are performed by for different quintiles for several elevation angles in both shortlisted sites. The results obtained from calculations carried out on two locations are almost similar. Also, significant under and over-estimation of rainfall error due to screening and ground clutter effect are detected. To achieve more accurate results, other sites need to be tested for further simulation. On the other hand since ground clutter, and screening effect at the Moucherotte is not too high compare with Saint Eynard, this site may be considered for implementing the future weather radar for observation of the meteorological processes over the Grenoble region.

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