scholarly journals Design of parametric risk transfer solutions for volcanic eruptions: an application to Japanese volcanoes

2021 ◽  
Vol 21 (1) ◽  
pp. 99-113
Author(s):  
Delioma Oramas-Dorta ◽  
Giulio Tirabassi ◽  
Guillermo Franco ◽  
Christina Magill
Keyword(s):  
Financial Risk ◽  
Volcanic Eruptions ◽  
Transfer Mechanism ◽  
Column Height ◽  
Regional Government ◽  
Building Structures ◽  
Risk Transfer ◽  
Natural Catastrophes ◽  
Ash Fall ◽  
Eruptive Column

Abstract. Volcanic eruptions are rare but potentially catastrophic phenomena, affecting societies and economies through different pathways. The 2010 Eyjafjallajökull eruption in Iceland, a medium-sized ash-fall-producing eruption, caused losses in the range of billions of dollars, mainly to the aviation and tourism industries. Financial risk transfer mechanisms such as insurance are used by individuals, companies, governments, etc., to protect themselves from losses associated with natural catastrophes. In this work, we conceptualize and design a parametric risk transfer mechanism to offset losses to building structures arising from large, ash-fall-producing volcanic eruptions. Such a transfer mechanism relies on the objective measurement of physical characteristics of volcanic eruptions that are correlated with the size of resulting losses (in this case, height of the eruptive column and predominant direction of ash dispersal) in order to pre-determine payments to the risk cedent concerned. We apply this risk transfer mechanism to the case of Mount Fuji in Japan by considering a potential risk cedent such as a regional government interested in offsetting losses to dwellings in the heavily populated prefectures of Tokyo and Kanagawa. The simplicity in determining eruptive column height and ash fall dispersal direction makes this design suitable for extrapolation to other volcanic settings worldwide where significant ash-fall-producing eruptions may occur, provided these parameters are reported by an official, reputable agency and a suitable loss model is available for the volcanoes of interest.

scholarly journals Design of parametric risk transfer solutions for volcanic eruptions: an application to Japanese volcanoes

2019 ◽  
Author(s):  
Delioma Oramas-Dorta ◽  
Giulio Tirabassi ◽  
Guillermo E. Franco ◽  
Christina Magill
Keyword(s):  
Financial Risk ◽  
Volcanic Eruptions ◽  
Transfer Mechanism ◽  
Column Height ◽  
Regional Government ◽  
Building Structures ◽  
Risk Transfer ◽  
Natural Catastrophes ◽  
Ash Fall ◽  
Eruptive Column

Abstract. Volcanic eruptions are rare but potentially catastrophic phenomena, affecting societies and economies through different pathways. The 2010 Eyjafjallajökull eruption in Iceland, a medium-sized ash fall producing eruption, caused losses in the range of billions of dollars, mainly to the aviation and tourist industries. Financial risk transfer mechanisms such as insurance are used by individuals, companies, Governments, etc. to protect themselves from losses associated to natural catastrophes. In this work, we conceptualize and design a parametric risk transfer mechanism to offset losses to building structures arising from large, ash fall-producing volcanic eruptions. Such transfer mechanism relies on the objective measurement of physical characteristics of volcanic eruptions that are correlated with the size of resulting losses (in this case, height of the eruptive column and predominant direction of ash dispersal), in order to pre-determine payments to the risk cedant concerned. We apply this risk transfer mechanism to the case of Mount Fuji in Japan, by considering a potential risk cedant such as a regional Government interested in offsetting losses to dwellings in the heavily populated Prefectures of Tokyo and Kanagawa. The simplicity in determining eruptive column height and ash fall dispersal direction makes this design suitable for extrapolation to other volcanic settings world-wide where significant ash fall producing eruptions may occur, provided these parameters are reported by an official, reputable agency, and a suitable loss model is available for the volcanoes of interest.

scholarly journals Climate change modulates the stratospheric volcanic sulfate aerosol lifecycle and radiative forcing from tropical eruptions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Thomas J. Aubry ◽  
John Staunton-Sykes ◽  
Lauren R. Marshall ◽  
Jim Haywood ◽  
Nathan Luke Abraham ◽  
...  
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Stratospheric Aerosol ◽  
Sulfate Aerosol ◽  
Column Height ◽  
Surface Cooling ◽  
Eruptive Column ◽  
Column Dynamics

AbstractExplosive volcanic eruptions affect climate, but how climate change affects the stratospheric volcanic sulfate aerosol lifecycle and radiative forcing remains unexplored. We combine an eruptive column model with an aerosol-climate model to show that the stratospheric aerosol optical depth perturbation from frequent moderate-magnitude tropical eruptions (e.g. Nabro 2011) will be reduced by 75% in a high-end warming scenario compared to today, a consequence of future tropopause height rise and unchanged eruptive column height. In contrast, global-mean radiative forcing, stratospheric warming and surface cooling from infrequent large-magnitude tropical eruptions (e.g. Mt. Pinatubo 1991) will be exacerbated by 30%, 52 and 15% in the future, respectively. These changes are driven by an aerosol size decrease, mainly caused by the acceleration of the Brewer-Dobson circulation, and an increase in eruptive column height. Quantifying changes in both eruptive column dynamics and aerosol lifecycle is therefore key to assessing the climate response to future eruptions.

Ensemble-based data assimilation of volcanic aerosols using FALL3D+PDAF

2021 ◽  
Author(s):  
Leonardo Mingari ◽  
Andrew Prata ◽  
Federica Pardini
Keyword(s):  
Data Assimilation ◽  
Information Transfer ◽  
High Performance ◽  
Volcanic Ash ◽  
Numerical Models ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Eruption Column ◽  
Operational Environment ◽  
Assimilation System

<p>Modelling atmospheric dispersion and deposition of volcanic ash is becoming increasingly valuable for understanding the potential impacts of explosive volcanic eruptions on infrastructures, air quality and aviation. The generation of high-resolution forecasts depends on the accuracy and reliability of the input data for models. Uncertainties in key parameters such as eruption column height injection, physical properties of particles or meteorological fields, represent a major source of error in forecasting airborne volcanic ash. The availability of nearly real time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context. Data assimilation (DA) is one of the most effective ways to reduce the error associated with the forecasts through the incorporation of available observations into numerical models. Here we present a new implementation of an ensemble-based data assimilation system based on the coupling between the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The implementation is based on the last version release of FALL3D (versions 8.x) tailored to the extreme-scale computing requirements, which has been redesigned and rewritten from scratch in the framework of the EU Center of Excellence for Exascale in Solid Earth (ChEESE). The proposed methodology can be efficiently implemented in an operational environment by exploiting high-performance computing (HPC) resources. The FALL3D+PDAF system can be run in parallel and supports online-coupled DA, which allows an efficient information transfer through parallel communication. Satellite-retrieved data from recent volcanic eruptions were considered as input observations for the assimilation system.</p>

Changing hazard awareness over two decades: the case of Furnas, São Miguel (Azores)

2021 ◽  
pp. SP519-2020-120
Author(s):  
Alessandra Lotteri ◽  
Janet Speake ◽  
Victoria Kennedy ◽  
Nicolau Wallenstein ◽  
Rui Coutinho ◽  
...  
Keyword(s):  
Volcanic Eruption ◽  
Volcanic Eruptions ◽  
Fumarolic Activity ◽  
Regional Government ◽  
Civil Protection ◽  
Volcanic Gas ◽  
Multiple Hazards ◽  
The People ◽  
Furnas Volcano ◽  
Hazard Awareness

AbstractFurnas (ca. 1,500 inhabitants) lies within the caldera of Furnas volcano on the island of São Miguel (Azores) and has the potential to expose its inhabitants to multiple hazards (e.g. landslides, earthquakes, volcanic eruptions and degassing). The present population has never experienced a volcanic eruption or a major earthquake, although the catalogue records six eruptions, sub-Plinian in style over the last 2 ka years. Today, the area experiences strong fumarolic activity. In the case of an eruption, early evacuation would be necessary to prevent inhabitants being trapped within the caldera. Awareness of potential threats and knowledge of what to do in the case of an emergency would assist in evacuation. In this paper inhabitants' awareness of volcanic and seismic threats in 2017 is compared with those revealed in a similar study completed more than two decades ago. It is concluded that, whereas awareness of earthquakes and the dangers posed by volcanic gas discharge has increased, knowledge of the threat of volcanic eruptions and the need to prepare for possible evacuation has not. Research suggests that changing awareness is related to effective collaboration that has developed between the regional government, through its civil protection authorities and scientists, and the people of Furnas.

Estimating the Volcanic Ash Fall Rate from the Mount Sinabung Eruption on February 19, 2018 Using Weather Radar

2019 ◽  
Vol 14 (1) ◽  
pp. 135-150 ◽  
Author(s):  
Magfira Syarifuddin ◽  
Satoru Oishi ◽  
Ratih Indri Hapsari ◽  
Jiro Shiokawa ◽  
Hanggar Ganara Mawandha ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Elevation Angle ◽  
Training Data ◽  
Classification Model ◽  
Column Height ◽  
Depth Information ◽  
Fall Rate ◽  
Angular Range ◽  
Ash Fall ◽  
Reflectivity Factor

This paper presents a theoretical method for estimating volcanic ash fall rate from the eruption of Sinabung Volcano on February 19, 2018 using an X-band multi-parameter radar (X-MP radar). The X-MP radar was run in a sectoral range height indicator (SRHI) scan mode for 6° angular range (azimuth of 221°–226°) and at an elevation angle of 7° to 40° angular range. The distance of the radar is approximately 8 km in the Southeastern direction of the vent of Mount Sinabung. Based on a three-dimensional (3-D) image of the radar reflectivity factor, the ash column height was established to be more than 7.7 km, and in-depth information on detectable tephra could be obtained. This paper aims to present the microphysical parameters of volcanic ash measured by X-MP radar, which are the tephra concentration and the fall-out rate. These parameters were calculated in a two-step stepwise approach microphysical model using the scaled gamma distribution. The first step was ash classification based on a set of training data on synthetic ash and its estimated reflectivity factor. Using a naïve Bayesian classification, the measured reflectivity factors from the eruption were classified into the classification model. The second step was estimating the volcanic ash concentration and the fall-out rate by power-law function. The model estimated a maximum of approximately 12.9 g·m-3of ash concentration from the coarse ash class (mean diameterDn= 0.1 mm) and a minimum of approximately 0.8 megatons of volcanic ash mass accumulation from the eruption.

scholarly journals Data Assimilation of Volcanic Aerosols using FALL3D+PDAF

2021 ◽  
Author(s):  
Leonardo Mingari ◽  
Arnau Folch ◽  
Andrew T. Prata ◽  
Federica Pardini ◽  
Giovanni Macedonio ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Volcanic Ash ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Model Parameters ◽  
Eruption Column ◽  
Mass Loading ◽  
Multiple Model ◽  
Volcanic Aerosols ◽  
Forecast Quality

Abstract. Modelling atmospheric dispersal of volcanic ash and aerosols is becoming increasingly valuable for assessing the potential impacts of explosive volcanic eruptions on infrastructures, air quality, and aviation. Management of volcanic risk and reduction of aviation impacts can strongly benefit from quantitative forecasting of volcanic ash. However, an accurate prediction of volcanic aerosol concentrations using numerical modelling relies on proper estimations of multiple model parameters which are prone to errors. Uncertainties in key parameters such as eruption column height, physical properties of particles or meteorological fields, represent a major source of error affecting the forecast quality. The availability of near-real-time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context by incorporating observations into numerical models. Specifically, ensemble-based filters aim at converting a prior ensemble of system states into an analysis ensemble by assimilating a set of noisy observations. Previous studies dealing with volcanic ash transport have demonstrated that a significant improvement of forecast skill can be achieved by this approach. In this work, we present a new implementation of an ensemble-based Data Assimilation (DA) method coupling the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The FALL3D+PDAF system runs in parallel, supports online-coupled DA and can be efficiently integrated into operational workflows by exploiting high-performance computing (HPC) resources. Two numerical experiments are considered: (i) a twin experiment using an incomplete dataset of synthetic observations of volcanic ash and, (ii) an experiment based on the 2019 Raikoke eruption using real observations of SO2 mass loading. An ensemble-based Kalman filtering technique based on the Local Ensemble Transform Kalman Filter (LETKF) is used to assimilate satellite-retrieved data of column mass loading. We show that this procedure may lead to nonphysical solutions and, consequently, conclude that LETKF is not the best approach for the assimilation of volcanic aerosols. However, we find that a truncated state constructed from the LETKF solution approaches the real solution after a few assimilation cycles, yielding a dramatic improvement of forecast quality when compared to simulations without assimilation.

Natural Disaster Risk Financing and Transfer in ASEAN Countries

2020 ◽  
Author(s):  
Paul Raschky ◽  
Sommarat Chantarat
Keyword(s):  
Financial Risk ◽  
Ad Hoc ◽  
Large Fraction ◽  
Risk Modeling ◽  
Risk Transfer ◽  
Multilateral Cooperation ◽  
Asean Countries ◽  
Transfer Mechanisms ◽  
Financial Losses ◽  
Disaster Risk Financing

ASEAN countries are frequently hit by a variety of natural disasters, and a large fraction of economic activity in ASEAN countries is located in areas exposed to these natural perils. Increasing disaster damages require ASEA countries to manage the financial losses in a more efficient and proactive manner. Currently, most risk-transfer mechanisms in this region rely on ad-hoc government relief, which is not sustainable. Multilateral cooperation in the areas of risk-modeling and mapping as well as joint efforts to establish financial risk-transfer solutions could help to overcome existing challenges in this area.

Catastrophe risk, reinsurance and securitized risk-transfer solutions: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yang Zhao ◽  
Jin-Ping Lee ◽  
Min-Teh Yu
Keyword(s):  
Risk Management ◽  
Insurance Industry ◽  
Long Term Effects ◽  
Insurance Demand ◽  
Content Type ◽  
Risk Transfer ◽  
Natural Catastrophes ◽  
Structural Framework ◽  
Hybrid Solutions ◽  
The Impact

PurposeCatastrophe (CAT) events associated with natural catastrophes and man-made disasters cause profound impacts on the insurance industry. This research thus reviews the impact of CAT risk on the insurance industry and how traditional reinsurance and securitized risk-transfer instruments are used for managing CAT risk.Design/methodology/approachThis research reviews the impact of CAT risk on the insurance industry and how traditional reinsurance and securitized risk-transfer instruments are used for managing CAT risk. Apart from many negative influences, CAT events can increase the net revenue of the insurance industry around CAT events and improve insurance demand over the post-CAT periods. The underwriting cycle of reinsurance causes inefficiencies in transferring CAT risks. Securitized risk-transfer instruments resolve some inefficiencies of the reinsurance market, but are subject to moral hazard, basis risk, credit risk, regulatory uncertainty, etc. The authors introduce some popular securitized solutions and use Merton's structural framework to demonstrate how to value these CAT-linked securities. The hybrid solutions by combining reinsurance with securitized CAT instruments are expected to offer promising applications for CAT risk management.FindingsThe authors introduce some popular securitized solutions and use Merton's structural framework to demonstrate how to value these CAT-linked securities. The hybrid solutions by combining reinsurance with securitized CAT instruments are expected to offer promising applications for CAT risk management.Originality/valueThis research reviews a broad array of impacts of CAT risks on the (re)insurance industry. CAT events challenge (re)insurance capacity and influence insurers' supply decisions and reconstruction costs in the aftermath of catastrophes. While losses from natural catastrophes are the primary threat to property–casualty insurers, the mortality risk posed by influenza pandemics is a leading CAT risk for life insurers. At the same time, natural catastrophes and man-made disasters cause distinct impacts on (re)insures. Man-made disasters can increase the correlation between insurance stocks and the overall market, and natural catastrophes reduce the above correlation. It should be noted that huge CAT losses can also improve (re)insurance demand during the postevent period and thus bring long-term effects to the (re)insurance industry.

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