Typhoon Maemi was generated as a tropical cyclone in the sea near Guam on September 4, 2003 and landed on the southern coast of the Korean peninsula on September 11 after passing through Okinawa Prefecture, Japan. Table 3 displays the typhoon information and basic building information to loss ratios for Typhoon Maemi as assessed through regression analysis. “Adress vulnerability, don’t try to stop a Typhoon”, "Adress vulnerability, don't try to stop a Typhoon". In order to reach this goal, this study used Typhoon Maemi loss record from a primary insurance company in South Korea. II: damage and loss estimation,”. Busan was also significantly devastated by the typhoon to the dollar amount of damages (43.8%) and the number of losses (45.0%). Furthermore, they can appraise the event limits and probable maximum loss, delineate premiums, estimate risk accumulation from typhoons, and institute business strategies found on the outcome of the metric. It reinforces the previous study indicating that the LOB grouping can categorize buildings as physical and financial functions [7]. Underwriters must consider PML in order to determine whether to take the risk and also to determine the premium [13]. Nevertheless, the other indicators are not related with the dependent variable of residential building. The models were also developed in specification of various types of buildings including commercial, residential, and industrial, so that the particular and practical application of these models are possible. During Typhoon Bopha (known as typhoon Pablo in the Philippines) in the island of Mindanao in 2012, which killed up to 2,000 people, the NPA discouraged communities to … This study also intends to develop and model a local vulnerability function, which assesses the damage of buildings from the results of typhoons by conducting the statistical analysis of the risk factors, in order for many sectors including federal and local governments, insurance companies, and construction companies to utilize in their own damage assessment. The various properties information of the typhoon directly affects the damage [31]. This also supports early research that reported that maximum wind speed is an essential indicator for predicting loss due to typhoons [12, 33, 40]. The records of previous extreme disasters are used as essential bases to establish the zone and limit. In order to achieve such accurate and reliable assessment, insurance companies use natural catastrophe models and historical loss records to predict and manage potential economic losses in individual buildings, regions, or countries. For this, this study adopted the various indicators that can be straightforwardly computed and easily accessed, found on Crichton’s risk triangle [11]. This means that the loss increases as the wind speed intensifies. Table 1 shows the distribution of loss per province from Typhoon Maemi. The models are statistically significant because the P values (0.000) are less than 0.05. Even as the country sits right in the active typhoon corridor, Narisma admitted that of all the phenomena associated with climate change, typhoons are actually the most uncertain. Ultimately, this study was designed to provide more methodologically grounded understanding and evidence-based knowledge in minimizing the risks of typhoons to buildings. Citing studies, Narisma said the intensities of the typhoons are getting stronger, with the most destructive tropical cyclones happening in the 1980s to 2000s. flood simulations and vulnerability assessment against pluvial flooding and coastal flooding due to storm surge during the passage of Typhoon Pablo. For this reason, insurers and reinsurers analyze extreme natural disasters in order to prepare reserves for losses from such extreme natural disasters. For instance, the correlation between building height and typhoon loss is negative, which means that as building height increases, typhoon loss decreases [37, 38]. In this study, the vulnerability function of the typhoon risk assessment models has also been developed and validated based on the statistical analysis of the actual loss claim payout data kept by an insurance company. The reason for this is that the building height is statistically correlated with the degree of financial loss, so it can be used as a vulnerability index to quantify a building’s vulnerability to hurricanes. After Typhoon Bopha (locally known as Pablo) in December 2012 caused catastrophic damage and high human losses the country is now position 2 of the ranking, only preceded by Haiti. Several previous studies have focused on hurricane/tornado damage, damage assessment, and vulnerability analysis. If there is a lot of poverty and housing conditions are not good,” Narisma noted. 1 Map of sites used as evacuation shelters within Cagayan De Oro in the Philippines during 3 recent flood events caused by tropical storms Sendong (2011), Pablo (2012) and Vinta (2017). The adjusted R2 value of the commercial building model was 0.332, indicating that 33.2% of the variance of the dependent variable can be explained by two indicators (total value of property and construction type). And therefore, the current situation is that the risk assessment is relied on the basic and minimum amount of data and information available. On Dec. 4, Typhoon Pablo slammed into Southern Mindanao, hitting some of the same cities and towns still recovering from the havoc suffered during Sendong. The maximum wind speed and loss due to the typhoon are positively interrelated. They also set up catastrophe zones and limit amounts in order to minimize the damage caused by these extreme disasters. Therefore, there is an urgent need for metrics and models that can easily and directly estimate and assess the vulnerabilities of the buildings to typhoons in these countries and situations. Variables for basic building information indicators included total value of property, number of floors and underground floors, and construction types. Table 2 defines the loss and data. The report stated that the Pacific Island nation of Vanuatu topped the chart, followed by the Polynesian state of Tonga. Although provisional, the model this study presents found that it is the resistance of roof tile and the correlation of trajectories of flying debris that takes an important part in the vulnerability [23]. That is, Hurricane Sandy in 2012 led to losses of $71.4 billion, while Hurricane Ike in 2008 led to losses of $29.5 billion [2, 3]. The distance from the property centroid to the coastline is also estimated based on the address information using the Geographic Information System. Typhoon Maemi hit the Korean Peninsula on 11th September in 2003, as shown in Figure 1(a). For instance, when construction types can be divided into wood, stone, steel, and reinforced concrete, they are generally vulnerable to typhoons in the following ascending order: reinforced concrete, steel, stone, and wood [6, 35, 36]. In COVID-19-Positive Stroke Patients, More Severe Strokes and Worse Outcomes Than in…. Typhoon Pablo (Bopha) , 4 December 2012 World’sdeadliest storm in 2012 (strong winds- 260 km per hour and heavy rainfall- 500 mm in 24 hours); Reportedly the most powerful storm to hit southern Mindanao in more than 100 years. Do we accept that is already the case?” she asked.The scientist quoted a definition of disaster by the International Federation of Red Cross and Red Crescent societies, which says: “A disaster occurs when a hazard impacts in vulnerable people.”“When you have a strong hazard, you are vulnerable, then you have a recipe for disaster. Yet, due to the nature of the data, although any customer information is hardly included, the public access to the data is not permitted to avoid any possible problems. The typhoon landed on the south coast on the Korean peninsula, through the inland, to the east coast, causing extreme economic losses in many cities on the south coast, as shown in Figure 1(b). In the New Oxford American Dictionary, the term typhoon is defined as “a tropical storm in the region of the Indian or western Pacific oceans” [15]. “Will there be another Yolanda in the future? Chock looked into hurricane damage on Hawaii residential buildings gathered and georeferenced on the GIS. This indicates that the rate of loss increases as the value of property decreases. As a result, this study suggested risk relativity factors and developed loss functions, which contributed to estimating hurricane damage to various Hawaii buildings [20]. Typhoon Vulnerability Analysis in South Korea Utilizing Damage Record of Typhoon Maemi, Department of Architectural Engineering, Mokpo National University, 1666 Yeongsan-Ro, Cheonggye-myeon, Muan-gun, Jeonnam 58554, Republic of Korea, School of Architectural Engineering, University of Ulsan, 93 Daehak-Ro, Ulsan 44610, Republic of Korea, Department of Civil Engineering and Engineering Mechanics, Columbia University, 500 W. 120th Street #610, New York, NY 10027, USA, http://typ.kma.go.kr/TYPHOON/down/2011/%C0%CE%B8%ED%B9%D7%C0%E7%BB%EA%C7%C7%C7%D8.pdf, K. T. Bhatia, G. A. Vecchi, T. R. Knutson et al., “Recent increases in tropical cyclone intensification rates,”. This signifies that the degree of loss rises as a building is closer to the coast. Uncertainty of typhoons. Among the key indicators of the variables, the value of property is the significant indicator that is shared among the three models. In addition, the modeling firms encourage insurers and reinsurers to create an independent in-house model with which to apprehend and assess portfolios and risks. However, the other indicators are not associated with the loss ratio of residential building. Park, and K. Son, “Estimating the Texas windstorm insurance association claim payout of commercial buildings from hurricane Ike,”, G. Y. K. Chock, “Modeling of hurricane damage for Hawaii residential construction,”, J. Zhang, “A vulnerability assessment of storm surge in Guangdong province, China,”, P. Heneka and B. Ruck, “A damage model for the assessment of storm damage to buildings,”, S. Zhang, K. Nishijima, and T. Maruyama, “Reliability-based modeling of typhoon induced wind vulnerability for residential buildings in Japan,”, D. Gautam, R. Adhikari, P. Jha, R. Rupakhety, and M. Yadav, “Windstorm vulnerability of residential buildings and infrastructures in south-central Nepal,”, S.-Su Lee and E.-Mi Chang, “Application of GIS to typhoon risk assessment,”. The total amount of the property is also substantial in terms of the losses associated with windstorms. Among the two types of typhoons, straight and recurving, in areas such as Philippines, southern China, and Vietnam, are threatened by straight-moving typhoons, while recurving typhoons are threats to Korea, northern China, and Japan [16]. Gautam et al. The amount of loss is the claim payout based on ground-up loss, which is the pure loss not accounting for insurance. estimated the distance from the building to the coastline to identify the relationship between the distance and loss caused by Hurricane Ike on Galveston Island and the Bolivar Peninsula. The total economic damages were approximately 13 billion euros [4]. The adjusted R2 value of the industrial building model was 0.403, indicating that 40.3% of the difference of the dependent variable can be described by three indicators (distance from coast, total value of property, and construction type). The reason for this is that developing a database that includes such information is considered to be inefficient, timewise and moneywise, for not only small- and medium-sized companies but also large corporations [7]. The statistical analysis found that, in the case of commercial buildings, total value of property and construction type are the two significant vulnerability indicators among the variables of both the natural hazard indicators and the basic building information indicators. As a result, the LOB category can classify buildings as physical and financial functions. They allocate portfolios to avoid emergencies and worst-case scenarios. The values of the variance inflation coefficient (VIF) ranged from 1.048 to 1.1. Meanwhile, claim payout records of insurance companies can provide specific, accurate, and reliable loss data. This terminology from insurance is also stated to relate policies in provision and book-keeping, such as the fact that injury and property policies can be classified as commercial, residential, and industrial. As of 2 p.m., typhoon Pablo was located 70 km south of Tagbiliran City with maximum sustained winds of 160 kph and gustiness of 195 kph moving west at 20 kph. Insurance and reinsurance companies can use the model from this research to improve their own business model using the methodologies to measure latent risks. Every year, typhoons such as Typhoon Maemi cause serious financial losses worldwide. To be more specific, the monetary data was adopted because of its definiteness and objectivity [30]. Sign up here as a reviewer to help fast-track new submissions. Following the scale of the coefficient, the indicators are (1) the total value of property (beta coefficient = –0.622), (2) floors (beta coefficient = 0.227), and (3) distance from coast (beta coefficient = –0.222). This means that there is a significant relationship between the dependent and independent variables. However, the remaining 66.8% caused by some unconfirmed indicators was not considered in this study. The lower the property value of a building, the more vulnerable it is to typhoons. In addition, the maximum amount of loss caused by a catastrophic disaster is a very vital number in the insurance industry. More specifically, it is a problem that models can only be developed and evaluated in a limited number of countries, such as the United States, China, and Japan, which often suffer large losses due to natural disasters and large insurance industries. After its rapid penetration of the southeastern part of the Korean Peninsula, it disappeared on September 14 in the East Sea. Typhoons cause significant financial damages worldwide every year. Typhoon Vamco, known in the Philippines as Typhoon Ulysses, was a powerful and deadly Category 4-equivalent typhoon that struck the Philippines and Vietnam and eventually became the second-costliest Philippine typhoon of all time, only surpassed by that of Typhoon Haiyan. This study also aims to assess the loss reflecting the regional vulnerability and to build a systematic method to measure other extreme cases and countries to predict the typhoon loss. 486,554 families / 5,408,900 persons in 1,926 barangays / 249 municipalities / 37 cities in 30 provinces of Regions IV-B, VI, VII, VIII, IX, X, XI, XII, and CARAGA were affected by typhoon Pablo. The reason for this was that the typhoon landed directly on the midcoast of Gyeongnam province, and the right side of the area had more influence than the left side of the area by the strong wind and rainfall of the typhoon [17, 18]. The property value of the building in this study was measured by the total sum insured. B. Robert et al., U. Ulbrich, A. H. Fink, M. Klawa, and J. G. Pinto, “Three extreme storms over Europe in December 1999,”, E. E. Koks, B. Jongman, T. G. Husby, and W. J. W. Botzen, “Combining hazard, exposure and social vulnerability to provide lessons for flood risk management,”, A. C. Khanduri and G. C. Morrow, “Vulnerability of buildings to windstorms and insurance loss estimation,”, J.-M. Kim, T. Kim, and K. Son, “Revealing building vulnerability to windstorms through an insurance claim payout prediction model: a case study in South Korea,”, H. Ryu, K. Son, and J.-M. Kim, “Loss prediction model for building construction projects using insurance claim payout,”. Hence, analyzing extreme disasters makes a significant contribution in assigning risk and determining pricing. Typhoon Pablo, as what Typhoon Bopha is called in the Philippines, was the most powerful storm to have hit the island of Mindanao, southern Philippines, in more than 100 years of recorded storms []. The damage was also enormous due to its severe wind speed, storm surge, and precipitation. Ultimately, 135 people died, there were 61,000 victims, and the overall property damage was about $ 4.3 billion (in 2003 year). The answer is no. The research scope is limited to South Korea. Keywords: Barangay Risk Reduction and Management Plan, disaster preparedness, response and relief, rehabilitation This again confirms that the number of floors is a vital indicator of quantifying typhoon, and it also strengthens the results of previous studies [37, 38]. For example, the vulnerability curve for typhoons describes the link between average damage rate and wind speed and determines the degree of damage, depending on the types of buildings. By contrast, the other indicators are not associated with the loss ratio of commercial building. To cope with such damages and losses, many industrialized countries have adopted and used insurance as a means to transfer the financial risks caused by typhoons. (2015) focused on the east coast municipalities, but Typhoon Previous typhoon and vulnerability research conducted in Asia has emphasised the socioeconomic and institutional factors contributing to people’s vulnerability (Gaillard et … It is dangerous to conclude the risk solely with the existing standard models alone. Shows a main indicator of the building’s typhoon vulnerability distribution of loss caused by typhoons and developed a provisional typhoon pablo vulnerability. 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