scholarly journals Rainfall Information System Based on Weather Radar for Debris Flow Disaster Mitigation

2018 ◽  
Vol 7 (4.44) ◽  
pp. 165 ◽  
Author(s):  
Ratih Indri Hapsari ◽  
Gerard Aponno ◽  
Rosa Andrie Asmara ◽  
Satoru Oishi
Keyword(s):  
Information System ◽  
Debris Flow ◽  
Weather Radar ◽  
Active Volcano ◽  
Radar Data ◽  
Disaster Mitigation ◽  
Web Based ◽  
X Band ◽  
Secondary Hazards ◽  
Debris Flow Disaster

Rainfall-triggered debris flow has caused multiple impacts to the environment. It. is regarded as the most severe secondary hazards of volcanic eruption. However, limited access to the active volcano slope restricts the ground rain measurement as well as the direct delivery of risk information. In this study, an integrated information system is proposed for volcanic-related disaster mitigation under the framework of X-Plore/X-band Polarimetric Radar for Prevention of Water Disaster. In the first part, the acquisition and processing of high-resolution X-band dual polarimetric weather/X-MP radar data in real-time scheme for demonstrating the disaster-prone region are described. The second part presents the design of rainfall resource database and extensive maps coverage of predicted hazard information in GIS web-based platform accessible both using internet and offline. The proposed platform would be useful for communicating the disaster risk prediction based on weather radar in operational setting.  

scholarly journals Naïve Bayes Classifier for Debris Flow Disaster Mitigation in Mount Merapi Volcanic Rivers, Indonesia, Using X-band Polarimetric Radar

2020 ◽  
Vol 11 (6) ◽  
pp. 776-789
Author(s):  
Ratih Indri Hapsari ◽  
Bima Ahida Indaka Sugna ◽  
Dandung Novianto ◽  
Rosa Andrie Asmara ◽  
Satoru Oishi
Keyword(s):  
Debris Flow ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Disaster Mitigation ◽  
Naive Bayes Classifier ◽  
Bayes Classifier ◽  
Naïve Bayes Classifier ◽  
X Band ◽  
System Verification ◽  
Debris Flow Disaster

AbstractDebris flow triggered by rainfall that accompanies a volcanic eruption is a serious secondary impact of a volcanic disaster. The probability of debris flow events can be estimated based on the prior information of rainfall from historical and geomorphological data that are presumed to relate to debris flow occurrence. In this study, a debris flow disaster warning system was developed by applying the Naïve Bayes Classifier (NBC). The spatial likelihood of the hazard is evaluated at a small subbasin scale by including high-resolution rainfall measurements from X-band polarimetric weather radar, a topographic factor, and soil type as predictors. The study was conducted in the Gendol River Basin of Mount Merapi, one of the most active volcanoes in Indonesia. Rainfall and debris flow occurrence data were collected for the upper Gendol River from October 2016 to February 2018 and divided into calibration and validation datasets. The NBC was used to estimate the status of debris flow incidences displayed in the susceptibility map that is based on the posterior probability from the predictors. The system verification was performed by quantitative dichotomous quality indices along with a contingency table. Using the validation datasets, the advantage of the NBC for estimating debris flow occurrence is confirmed. This work contributes to existing knowledge on estimating debris flow susceptibility through the data mining approach. Despite the existence of predictive uncertainty, the presented system could contribute to the improvement of debris flow countermeasures in volcanic regions.

scholarly journals X-Band Polarimetric Weather Radar Observations of a Hailstorm

2013 ◽  
Vol 30 (9) ◽  
pp. 2143-2151 ◽  
Author(s):  
Jordi Figueras i Ventura ◽  
Françoise Honoré ◽  
Pierre Tabary
Keyword(s):  
Weather Radar ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Complementary Information ◽  
Radar Observations ◽  
National Network ◽  
X Band ◽  
Polarimetric Weather Radar

Abstract This paper presents an analysis of a hail event that occurred 27 May 2012 over Brignoles, located in southeastern France. The event was observed by an X-band polarimetric radar located in Mont Maurel, 75 km northeast of the hailstorm. Lightning data from the French national network (owned and operated by Météorage) are also used in the study. The analysis highlights that the lightning and radar data provide complementary information that may allow a better microphysical interpretation of the hailstorm and potentially increase the probability of its detection.

Design of Lifting Electromechanical System for Onboard X-Band Weather Radar Antenna and Data Filtering Analysis

2013 ◽  
Vol 579-580 ◽  
pp. 740-744
Author(s):  
Xu Hui Wei ◽  
Bin Hua Yang ◽  
Wei Dong Lu ◽  
Ling Wen Kong
Keyword(s):  
Modular Design ◽  
Weather Radar ◽  
Radar Data ◽  
Object Oriented Programming ◽  
Electromechanical System ◽  
System Stability ◽  
Data Management System ◽  
Data Filtering ◽  
X Band ◽  
Radar Antenna

Onboard X-Band Weather Radar and data filter prediction is one of core services of the Xinjiang meteorological emergency system. Based on installation conditions provided by IVECO trunk, the structure of X-band radar antenna, lifting height and antenna work requirements, combined with the modular design concept, this paper developed the X-band weather radar antenna dedicated lifting system. This system consists of radar antenna base platform, lifting rack rails, rollers, sprockets, cylinder etc. when working, the system can not only utilize the synchronizing control strategy to ensure the system stability but also quickly set up an antenna. Based on the design of Onboard X-band Weather radar antenna lifting electromechanical system, we developed the radar data management system. In this software, Object-oriented programming language, multi-threaded programming methods and software modularity method is utilized to design the platform architecture, GIS controls and dynamic mesh technology are used to make the radar map, and based on the principle of Kalman filtering, intelligent prediction approaches are studied. Computer numerical simulation and experimental results show that the electromechanical system developed by this paper has good performance and utilized the data filtering technology to provide the reliable method for meteorological warning.

scholarly journals Clear-Air Turbulence (CAT) Identification with X-Band Dual Polarimetric Radar Based on Bayesian Approach

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1691
Author(s):  
Jianli Ma ◽  
Li Luo ◽  
Mingxuan Chen ◽  
Siteng Li
Keyword(s):  
Frequency Distribution ◽  
Removal Rate ◽  
Low Frequency ◽  
Weather Radar ◽  
Radar Data ◽  
Probability Density Distribution ◽  
Air Turbulence ◽  
X Band ◽  
Differential Reflectivity

The echo of weather radar is seriously disturbed by clear-air turbulence echo (CAT) which needs identifying and eliminating to improve the data quality of weather radar. Using the data observed with the five X-band dual polarimetric radars in Changping, Fangshan, Miyun, Shunyi, and Tongzhou, Beijing in 2018, the probability density distribution (PDD) of the horizontal texture of four radar moments reflectively factor (ZH), differential reflectivity (ZDR), correlation coefficient (ρHV), differential propagation phase shift (ΦDP), and then the CAT is identified and removed using Bayesian method. The results show that the radar data can be effectively improved after the CAT has been eliminated, which include: (1) the removal rate of CAT is more than 98.2% in the analyzed cases. (2) In the area with high-frequency distribution of CAT, the CAT can be effectively suppressed; in the area with low-frequency distribution, some weather echo in the edge with SNR < 15 dB may be mistakenly identified as CAT, but the proportion of meteorological echoes to the total echoes is more than 85%, which indicate that the error rate is very low and does not affect the radar operation.

scholarly journals The Web-based Framework of X-Band Polarimetric Radar System

2019 ◽  
Vol 8 (2) ◽  
pp. 4165-4169 ◽  
Keyword(s):  
Disaster Preparedness ◽  
System Development ◽  
Radar Data ◽  
Radar System ◽  
Polarimetric Radar ◽  
Web Based ◽  
Internet Technologies ◽  
X Band ◽  
Estimation System ◽  
Web Based System

The application of X-Band Polarimetric radar (X-Band MP radar) is very effective in disaster risk management which can help professional, researchers, private and government agencies to take actions for rainfall-related disaster preparedness and prevention activities. This needs dissemination of rainfall radar data and information for developing the methods, models and applications. With the emerging Internet technologies, many web-based systems are used as a fundamental platform for gathering, processing and delivering the data or information in many fields. This paper is aimed to recognize the requirements of a web-based framework for rainfall estimation system by using X-Band MP radar. Through the systematic approach, three requirements for the proposed architecture are identified, which are the source of rainfall data, the technology involved in the system development and the features of web-based system. Those requirements are represent the whole concept of X-Band MP radar system for Malaysia. Based on the outcome of this study, a web-based system framework is proposed and the prototype of the proposed system will be developed.

Web‐based real‐time visualization of large‐scale weather radar data using 3D tiles

2020 ◽  
Author(s):  
Mingyue Lu ◽  
Xinhao Wang ◽  
Xintao Liu ◽  
Min Chen ◽  
Shuoben Bi ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Weather Radar ◽  
Radar Data ◽  
Web Based ◽  
Real Time Visualization
Sign in / Sign up

Export Citation Format

Share Document