Real-time tephra detection and dispersal forecasting by a ground-based weather radar
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...
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sg-ntu-dr.10356-1606012022-07-30T20:11:28Z Real-time tephra detection and dispersal forecasting by a ground-based weather radar Magfira Syarifuddin Jenkins, Susanna F. Ratih Indri Hapsari Yang, Qingyuan Taisne, Benoit Andika Bayu Aji Nurnaning Aisyah Hanggar Ganara Mawandha Djoko Legono Asian School of the Environment Earth Observatory of Singapore Science::Geology Tephra Ground-Based Weather Radar 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. Ministry of Education (MOE) National Research Foundation (NRF) Published version This research was supported by the Earth Observatory of Singapore via its funding from the National Research Foundation Singapore and the Singapore Ministry of Education under the Research Centres of Excellence initiative. 2022-07-27T07:08:08Z 2022-07-27T07:08:08Z 2021 Journal Article 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-. https://dx.doi.org/10.3390/rs13245174 2072-4292 https://hdl.handle.net/10356/160601 10.3390/rs13245174 2-s2.0-85121664056 24 13 5174 en Remote Sensing © 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:// creativecommons.org/licenses/by/ 4.0/). application/pdf |
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Science::Geology Tephra Ground-Based Weather Radar Magfira Syarifuddin Jenkins, Susanna F. Ratih Indri Hapsari Yang, Qingyuan Taisne, Benoit Andika Bayu Aji Nurnaning Aisyah Hanggar Ganara Mawandha Djoko Legono Real-time tephra detection and dispersal forecasting by a ground-based weather radar |
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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. |
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Asian School of the Environment |
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Asian School of the Environment Magfira Syarifuddin Jenkins, Susanna F. Ratih Indri Hapsari Yang, Qingyuan Taisne, Benoit Andika Bayu Aji Nurnaning Aisyah Hanggar Ganara Mawandha Djoko Legono |
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Article |
author |
Magfira Syarifuddin Jenkins, Susanna F. Ratih Indri Hapsari Yang, Qingyuan Taisne, Benoit Andika Bayu Aji Nurnaning Aisyah Hanggar Ganara Mawandha Djoko Legono |
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Magfira Syarifuddin |
title |
Real-time tephra detection and dispersal forecasting by a ground-based weather radar |
title_short |
Real-time tephra detection and dispersal forecasting by a ground-based weather radar |
title_full |
Real-time tephra detection and dispersal forecasting by a ground-based weather radar |
title_fullStr |
Real-time tephra detection and dispersal forecasting by a ground-based weather radar |
title_full_unstemmed |
Real-time tephra detection and dispersal forecasting by a ground-based weather radar |
title_sort |
real-time tephra detection and dispersal forecasting by a ground-based weather radar |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/160601 |
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1739837451556356096 |