Preliminary Observations and Impact in Japan of the Tsunami Caused by the Tonga Volcanic Eruption on January 15, 2022.

The tsunami caused by the Tonga submarine volcanic eruption that occurred at 13:15 Japan Time (JST) on January 15, 2022, exposed a blind spot in Japan's tsunami monitoring and warning system, which was established in 1952 for local tsunamis and expanded to distant tsunamis after the 1960 Chile tsunami. This paper summarizes how the warning system responded to the unprecedented tsunami, the actual evacuation process, and the damage it caused in Japan. Initially, the tsunami from the volcanic eruption was expected to arrive at approximately midnight with amplitudes of less than 20 cm. However, a series of short waves arrived at approximately 21:00, a few hours earlier than expected. The early arrival of these sea waves coincided with a rapid increase in atmospheric pressure; then, the short-period component was predominant, and the wave height was amplified while forming wave groups. After a 1.2 m tsunami was observed in Amami City in southern Japan at 23:55 JST, the Japan Meteorological Agency issued a tsunami warning/advisory. The tsunami continued, and all advisories were cleared at 14:00 JST on January 16. Information about this tsunami and the response to it are summarized here, including the characteristics and issues of the actual tsunami evacuation situation in each region. There were no casualties, but the issues that emerged included difficulty evacuating on a winter night and traffic congestion due to evacuation by car and under the conditions of the COVID-19 pandemic. In the coastal area, damage to fishing boats and aquaculture facilities was reported due to the flow of the tsunami. In addition, damage to aquaculture facilities, including those producing oysters, scallops, seaweed and other marine products, decreased the supply of marine products, and the economic impact is likely to increase in the future.

Dataset of Post-Event Survey of the 2024 Noto Peninsula Earthquake Tsunami in Japan.

An earthquake with a moment magnitude of 7.5 (Mw) struck the northern Noto Peninsula, Ishikawa Prefecture, Japan, at 16:10 local time on January 1, 2024. This earthquake triggered a tsunami that propagated along the coastline of Ishikawa, Toyama, and Niigata Prefectures facing the Sea of Japan and significantly damaged coastal communities and infrastructure. Approximately 70 researchers from 23 universities or other institutes throughout Japan formed a joint research group to conduct a post-tsunami survey along a 340 km stretch of the coast. Based on the watermarks and traces of the tsunami, the inundation and run-up heights were surveyed using total stations, automatic optical levels, laser range finders, and a real-time kinematic (RTK) Global Navigation Satellite System (GNSS). The tidal correction was adjusted using astronomical tidal tables. In total, 303 survey records have been compiled, generating the NP2024TS (Noto Peninsula 2024 Tsunami Survey) dataset. This dataset provides comprehensive information on the inundation and run-up heights of the tsunami, which is useful for understanding tsunami characteristics and validating numerical tsunami models.

Resonance characteristics of tsunami in bay of Japan by the Hunga Tonga-Hunga Ha'apai volcano eruption on 15th January 2022.

The massive eruption of the Hunga Tonga-Hunga Ha'apai (HTHH) volcano in Tonga on 15 January 2022 at 04:15 UTC had a global impact and triggered an atmospheric wave and a tsunami. We first analyzed observation data from meteorological stations and tide gauges at 12 locations. Low-frequency trends in the observation data were removed by using a high-pass filter. Fourier and wavelet spectral analyses were applied to determine the frequency characteristics of the filtered data. Modal analysis was developed and used to investigate natural oscillation periods based on bathymetry. The results showed that the Lamb wave generated by the atmospheric pressure wave arrived ~ 7 and ~ 44 h after the eruption. The tsunami arrived ~ 11 and ~ 45 h after the eruption, which corresponded to the arrival time of the Lamb wave. The dominant periods of the Lamb waves were ~ 7.7 and ~ 7.5 min, and for the tsunamis they were ~ 9.9 and ~ 28.7 min. The periods derived from the spectral analysis matched the natural oscillation of the eigenperiod derived from the modal analysis, in eight out of the twelve stations. This study provides valuable insight and information regarding the nonseismic and far-field effects of tsunamis generated by volcanic eruptions.

Universal health coverage mitigated COVID-19 health-related consequences in Asia Oceania.

The COVID-19 pandemic has been a continual challenge since 2020, and it continues to impact people and industries as a disaster caused by a biological hazard. This study examined universal health coverage (UHC) scores in relation to the performance in combating COVID-19 in the Southeast Asian region (SEAR) and the Western Pacific region (WPR), along with the State Party Self-Assessment Annual Reporting (SPAR) index under the international health regulations (IHC). The numbers of infections and deaths per million population from December 2019 to June 2022 were used as primary outcomes to measure countries' performance. Countries with UHC scores of 63 or higher had a significantly lower number of infected patients and deaths. In addition, several inter-capacity correlations within the SPAR capacities, including with C8 (the National Health Emergency Framework), as well as a very strong correlation to C4 (Food Safety), C5 (Laboratory), and C7 (Human Resources). Furthermore, C9 (Health Service Provisions) has a very strong correlation to C1 (Legislation and Financing), C2 (International Health Regulation Coordination and a National IHR Focal Point function), and C4 (Food Safety), suggesting that the capability to manage an emerging infectious disease form blocks of capacities. In conclusion, UHC clearly mitigated the health-related consequences of COVID-19 in South-East Asia Region (SEAR) and Western Pacific Region (WPR). Investigating the correlation between the SPAR capacities and UHC is a promising approach for future research, including the importance of the provision of health services, points of entry, and, most importantly, risk communications as critical factors for managing pandemic. This study constitutes a good opportunity to apply the SPAR index to define which capacities correlate with the outcome of the pandemic in terms of infections and deaths.

The near-field tsunami generated by the 15 January 2022 eruption of the Hunga Tonga-Hunga Ha'apai volcano and its impact on Tongatapu, Tonga.

On 15 January 2022 at 04:15 UTC, the Hunga Tonga-Hunga Ha'apai (HTHH) volcano in Tonga produced a massive eruption that triggered a transoceanic tsunami generated by the coupled ocean and atmospheric shock wave produced during the explosion. The tsunami first reached the coast of Tonga and eventually reached many coasts around the world. This volcano previously underwent a massive eruption in 1100 AD, and an eruption occurs approximately every 1000 years. The 2022 HTHH event provides an opportunity to study a major volcanically generated tsunami that caused substantial damage. In this study, we present a numerical simulation of a tsunami with a state-of-the-art numerical model based on a submarine explosion scenario. We constrain the geometry and magnitude of the explosion energy source based on analyses of pre- and post-event satellite images, which demonstrate that the explosion magnitude varied from 1 to 90 megatons of trinitrotoluene (Mt). Estimated submarine explosion geometries result in a suitable explosion magnitude of approximately 25 Mt, as determined with the waveform from the tide gauge in the time and frequency domains. The tsunami wave first reached the northwestern part of Tonga's Tongatapu within 10 min, with a maximum runup height of approximately 15 m, and covered the whole of Tongatapu within 30 min. Finally, the numerical simulation provides deep insights into the physical volcanic explosion processes and improves our understanding and forecasting capabilities of frequent and catastrophic tsunamis caused by submarine volcanic explosions.

People's Perception of Well-Being during the COVID-19 Pandemic: A Case Study in Japan.

This study aims to examine people's perception of well-being during the COVID-19 pandemic in Japan and quantitatively clarify key factors towards realizing evidence-based policymaking. In March 2022, 400 participants responded to a survey conducted through Rakuten Insight. The authors applied an ordinal logistic regression (OLR), followed by principal component analysis (PCA), to create a new compound indicator (CI) to represent people's perception of well-being during the pandemic in addition to ordinary least squares (OLS) regression with a forward-backward stepwise selection method, where the dependent variable is the principal component score of the first principal component (PC1), while the independent variables are the same as the abovementioned OLR. Consequently, while analyzing OLR, some independent variables showed statistical significance, while the CI provided an option to grasp people's perception of well-being. Furthermore, family structure was statistically significant in all cases of OLR and OLS. Moreover, in terms of the standardized coefficients (beta) of OLS, the family structure had the greatest impact on the CI. Based on the study results, the authors advocate that the Japanese government should pay more attention to single-person households affected by the COVID-19 pandemic.

Factors affecting worriedness: A study of the COVID-19 pandemic in Japan.

The global effect of COVID-19 is no longer simply a public health issue; it is causing an economic crisis that has a significant impact on the job market and people's lives. The disease has led to 43% of businesses temporarily closing, and almost all these closures are due to COVID-19. Organizations that have temporarily suspended their activities have pointed mainly to a decline in demand and employee health issues as the reasons for closure. In emergency and disaster management, perception often helps shape personality and how people act in certain situations. This study aims to examine personal risk perception of COVID-19 from many viewpoints and whether it affects motivation with regard to improving personal preparedness. We collected data from three major Japanese cities through a questionnaire survey and analyzed the results of the survey through factor analysis and multiple regression analysis by using the Partial Least Square Structural Equation Modeling (PLS-SEM). The three study areas include (1) the most damaged regions from the 2011 Great East Japan earthquake and tsunami, (2) the capital city and surrounding areas of Tokyo, and (3) Kumamoto, which has recently experienced an earthquake. The findings show a correlation between the nature of the information received during COVID-19 and worriedness and the necessity for adequate information. The expected benefit of this study is to provide guidelines for the government or organizations to make a suitable emergency management plan based on pertinent factors for future pandemics.

Perceptions of the COVID-19 pandemic in Japan with respect to cultural, information, disaster and social issues.

A questionnaire survey was distributed via the Internet to 600 respondents. Preliminary results revealed that most Japanese people regularly washed their hands and had low resistance to wearing masks even before the COVID-19 pandemic. Internet news was the most common source of information. Half of the respondents said they would "stay at home evacuation" if a disaster occurred during the COVID-19 pandemic, reflecting the strategy promoted to reduce crowding in evacuation shelters. If a state of emergency must be reinstated, one-third of respondents said they could bear it for a few months and another one-third for a few weeks.