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Title: Real-time tephra detection and dispersal forecasting by a ground-based weather radar
Authors: Magfira Syarifuddin
Jenkins, Susanna F.
Ratih Indri Hapsari
Yang, Qingyuan
Taisne, Benoit
Andika Bayu Aji
Nurnaning Aisyah
Hanggar Ganara Mawandha
Djoko Legono
Keywords: Science::Geology
Issue Date: 2021
Source: Magfira Syarifuddin, Jenkins, S. F., Ratih Indri Hapsari, Yang, Q., Taisne, B., Andika Bayu Aji, Nurnaning Aisyah, Hanggar Ganara Mawandha & Djoko Legono (2021). Real-time tephra detection and dispersal forecasting by a ground-based weather radar. Remote Sensing, 13(24), 5174-.
Journal: Remote Sensing 
Abstract: Tephra plumes can cause a significant hazard for surrounding towns, infrastructure, and air traffic. The current work presents the use of a small and compact X-band multi-parameter (X-MP) radar for the remote tephra detection and tracking of two eruptive events at Merapi Volcano, Indone-sia, in May and June 2018. Tephra detection was performed by analysing the multiple parameters of radar: copolar correlation and reflectivity intensity factor. These parameters were used to cancel unwanted clutter and retrieve tephra properties, which are grain size and concentration. Real-time spatial and temporal forecasting of tephra dispersal was performed by applying an advection scheme (nowcasting) in the manner of an ensemble prediction system (EPS). Cross-validation was performed using field-survey data, radar observations, and Himawari-8 imageries. The nowcasting model computed both the displacement and growth and decaying rate of the plume based on the temporal changes in two-dimensional movement and tephra concentration, respectively. Our results are in agreement with ground-based data, where the radar-based estimated grain size distribution falls within the range of in situ grain size. The uncertainty of real-time forecasted tephra plume depends on the initial condition, which affects the growth and decaying rate estimation. The EPS improves the predictability rate by reducing the number of missed and false forecasted events. Our findings and the method presented here are suitable for early warning of tephra fall hazard at the local scale.
ISSN: 2072-4292
DOI: 10.3390/rs13245174
Schools: Asian School of the Environment 
Research Centres: Earth Observatory of Singapore 
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// 4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ASE Journal Articles
EOS Journal Articles

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