| Literature DB >> 35457374 |
Yui-Yip Lau1, Tsz-Leung Yip2, Maxim A Dulebenets3, Yuk-Ming Tang4, Tomoya Kawasaki5.
Abstract
Tropical cyclones are highly destructive weather systems, especially in coastal areas. Tropical cyclones with maximum sustained winds exceeding 74 mph (≈119 kph) are classified as typhoons in the Northwest Pacific, whilst the term 'hurricanes' applies to other regions. This study aims to investigate the general characteristics of the most devastating and catastrophic tropical cyclones in the USA Europe, and Asia. To achieve the study objectives, the three most devastating typical tropical cyclones in each region were selected. The tropical cyclones were examined based on various features, such as the number of deaths, minimum pressure, highest wind speed, total financial losses, and frequency per year. In contrast to Europe and Asia, the USA has recorded the highest number of catastrophic tropical cyclones. The damage induced by hurricanes Katrina, Harvey, and Maria in the USA totalled approximately USD USD 380 billion. In addition, the present research highlights the demand to improve the public attitude and behaviour toward the impact of climate change along with the enhancement of climate change alleviation strategies. The number of intense tropical cyclones is expected to rise, and the tropical cyclone-related precipitation rate is expected to increase in warmer-climate areas. Stakeholders and industrial practitioners may use the research findings to design resilience and adaptation plans in the face of tropical cyclones, allowing them to assess the effects of climate change on tropical cyclone incidents from an academic humanitarian logistics viewpoint in the forthcoming years.Entities:
Keywords: adaptation; climate change; humanitarian logistics; resilience; tropical cyclones
Mesh:
Year: 2022 PMID: 35457374 PMCID: PMC9029545 DOI: 10.3390/ijerph19084499
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Typhoon data as logistics attributes.
| Item | Logistics Attributes | Typhoon Data |
|---|---|---|
| 1 | Location | Formation location |
| 2 | Transport | Date of year |
| 3 | Inventory | Wind speed or Wind scale |
| 4 | Value | Economic loss |
Figure 1Product life cycle (PLC) of a typhoon event.
The interface between a typhoon event and humanitarian logistics.
| Stage | PLC | Humanitarian Logistics |
|---|---|---|
| 1 | Introduction (or formation) | Early warning through advanced communication technology |
| 2 | Growth (or development) | Hazard monitoring for risk assessment |
| 3 | Maturity | Prevention; business continuity plan (e.g., mobilising relief items, such as water, food, and housing); quick transportation; allocation of scarce resources |
| 4 | Decline | Disruptions and recovery via post-disaster humanitarian operations |
Figure 2The interface of a typhoon event and humanitarian logistics.
Figure 3Number of recorded storms in the USA since the 1850s.
Figure 4Natural disaster declarations in the USA states. Source: FEMA [52].
Costliest hurricanes in the USA since 2000.
| a/a | Hurricane | Year | Maximum Wind Speed (mph) | Lowest | Total Deaths | Total Losses | Total Rainfall (inches) |
|---|---|---|---|---|---|---|---|
| 1 | Katrina | 2005 | 175 | 902 | 1836 | 160.0 billion | 37 |
| 2 | Harvey | 2017 | 130 | 937 | 107 | 125.0 billion | 99 |
| 3 | Maria | 2017 | 175 | 908 | 3059 | 91.6 billion | 100 |
| 4 | Irma | 2017 | 180 | 914 | 134 | 77.2 billion | 15 |
| 5 | Sandy | 2012 | 115 | 940 | 233 | 70.2 billion | 10 |
| 6 | Ike | 2008 | 145 | 935 | 214 | 38.0 billion | 10 |
| 7 | Ivan | 2004 | 165 | 910 | 124 | 27.1 billion | 7 |
| 8 | Michael | 2018 | 160 | 919 | 74 | 25.1 billion | 7 |
| 9 | Wilma | 2005 | 185 | 882 | 52 | 24.3 billion | 6 |
| 10 | Florence | 2018 | 150 | 937 | 54 | 24.2 billion | 10 |
The list of costliest storms in Europe since 2000.
| a/a | Storm | Year | Maximum Wind Speed (mph) | Lowest | Total Deaths | Total Losses | Total Rainfall (inches) |
|---|---|---|---|---|---|---|---|
| 1 | Kyrill | 2007 | 160 | 960 | 53 | 4.70 billion | 54 |
| 2 | Xynthia | 2010 | 142 | 967 | 63 | 3.00 billion | 16 |
| 3 | David | 2018 | 126 | 974 | 15 | 2.60 billion | 21 |
| 4 | Ciara | 2020 | 136 | 943 | 13 | 1.90 billion | 14 |
| 5 | Gudrun | 2005 | 103 | 960 | 12 | 1.38 billion | 9 |
| 6 | St. Jude | 2013 | 121 | 967 | 17 | 1.10 billion | 10 |
| 7 | Xaver | 2013 | 142 | 962 | 15 | 1.00 billion | 10 |
| 8 | Eleanor | 2018 | 140 | 966 | 6 | 0.64 billion | 5 |
| 9 | Lorenzo | 2019 | 160 | 925 | 19 | 0.36 billion | 6 |
| 10 | Andrea | 2012 | 109 | 964 | 1 | 0.35 billion | 8 |
Recorded storms that occurred in Macau and Hong Kong (1960–2019).
| 1960–1969 | 1970–1979 | 1980–1989 | 1990–1999 | 2000–2009 | 2010–2019 | |
|---|---|---|---|---|---|---|
|
| 8 | 6 | 8 | 8 | 7 | 7 |
|
| 1 | 2 | 0 | 2 | 0 | 7 |
|
| 6 | 3 | 1 | 1 | 0 | 3 |
|
| 15 | 11 | 9 | 11 | 9 | 10 |
Summary of the most severe storms in Macau and Hong Kong since 2000.
| a/a | Storm | Year | Maximum Wind Speed (mph) | Lowest | Total Deaths | Total Losses | Total Rainfall (inches) |
|---|---|---|---|---|---|---|---|
| 1 | Hato | 2017 | 132 | 945.4 | 12 (Macau) | USD 6.41 billion | 50 |
| 2 | Mangkhut | 2018 | 180 | 956.4 | 0 | USD 3.77 billion | 29 |
| 3 | Vicente | 2012 | 140 | 964.2 | 0 | USD 0.35 billion | 35 |
| 4 | Dujuan | 2003 | 145 | 950 | 0 | USD 0.31 billion | 67 |
| 5 | Nuri | 2008 | 115 | 955 | 2 (Hong Kong) | USD 0.085 billion | 52 |
Figure 5Summary of tropical cyclones in the USA, Europe, and Asia.
Summary of tropical cyclones in the USA, Europe, and Asia since 2000.
| Region | Total Number of Storms | Season | Levels of Tropical Cyclones | Total Deaths | Total Losses | Total Rainfall (inches) |
|---|---|---|---|---|---|---|
| USA | 10 | 3 Summers | 10 super typhoons | 5887 | USD 662.7 billion | 301 |
| Europe | 10 | 2 Autumns | 5 typhoons | 214 | USD 17.03 billion | 153 |
| Asia | 5 | 4 Summers | 1 typhoon | 14 | USD 10.93 billion | 230 |