integrated sakurajima volcanic ash fall distribution under ... · integrated sakurajima volcanic...
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Integrated Sakurajima Volcanic Ash Fall DistributionUnder Climate Change
An Analysis based on JRA-55 Data using Neural Network
1. Background• A volcanic eruption is one of the events which emit several
dangerous pollutants that led to catastrophes.• Volcanic ashes, apparently hampering not only the resident who
lived near the volcano but also the other citizens in the fartherarea that can get indirect impact from that.
• The volcanic ash released by large-scale eruptions may causeserious damage to critical infrastructures, buildings, andcause health problem.
PUFF Model
DPRI, Kyoto University
3. Methodology
• Integrated volcanic ashfall risk assessment in large-scaleeruption.a. Systematically estimate the risk of volcanic ashfall from probable large-
scale volcanic eruption in Sakurajima.b. Historical weather data is used for risk estimation to validate and
understand ashfall risk.c. Get critical characteristic from historical eruption data and past climate
data for verifying implemented policies obtained from the prior result.
• Confirmation of risk assessment between historicalweather data and predictive weather data that will enhancethe decision support system for volcanic disaster riskmanagement for the development of early warningsystem.a. Compare daily ash fallout map between results obtained from both
predictive data and historical data on general occasion.b. Compare daily ash fallout map between results obtained from both
predictive data and historical data on specific occasion.c. Thorough analysis by comparing similarities and anomalies detection
between both results.
• The confirmed ash fallout distribution data, added withpopulation data, will be extended to the development ofintegrated evacuation planning that consideredevacuation willingness of the potential endangeredresident.
2. Objectives
4. Results on Annual and Monthly Observation
5. Result under Typhoons No. 24 (Sep 28th-30th)
6. Conclusions• Ash fallout distribution maps produced from PUFF model with JRA-55 data give
risk assessment coverage confirming the risk threshold on different riskcomponents.
• In typhoon approaching situation, the alterations in ashfall dispersion course isdetected by using JRA-55 data.
• Lastly, by conducting ashfall risk-assessment on large-scale eruption scenariofor long period and confirming the development of ashfall early warning system,we can build more comprehensive evacuation planning based on peoplebehavior towards the ashfall hazard.
7. Future Works
𝑟𝑟𝑖𝑖 𝑡𝑡 ：Position vector of the 𝑖𝑖−th particle at time 𝑡𝑡𝑆𝑆𝑖𝑖：Initial locations of the particles as a source term𝑉𝑉：Local wind velocity to transport the particle
𝑍𝑍：Diffusion velocity𝐺𝐺：Gravitational fallout velocity∆𝑡𝑡：Time step (300𝑠𝑠)
Probability Distribution
Eruption Scenario
Risk Map for 0.1 mm thick ash fall in 2018
The risk threshold for ash fall hazard
Risk Map for 5 cm thickash fall in 2017
Risk Map for 5 cm thickash fall in January 2017
Risk Map for 5 cm thickash fall in August 2017
Risk Map for 50 cm thickash fall in August 2017
Risk Map for 50 cm thickash fall in October 2017
TyphoonTrajectory
Risk Map on Sep 28th, 2018 Risk Map on Sep 29th, 2018 Risk Map on Sep 30th, 2018
Haris Rahadianto
Master StudentGraduate School of Informatics - Kyoto University
[email protected] - JAPAN
Haris Rahadianto・Subhajyoti Samaddar・Hirokazu Tatano