National Tsunami Warning Center

Research Article| January 25, 2023 Introduction to the SRL Focus Section on the Hunga Tonga‐Hunga Ha’apai Eruption Margaret Hellweg; Margaret Hellweg * 1Berkeley Seismology Laboratory, University of California Berkeley, Berkeley, California, U.S.A. *Corresponding author: peggy@seismo.berkeley.edu Search for other works by this author on: GSW Google Scholar Stephen Arrowsmith; Stephen Arrowsmith 2Southern Methodist University, Dallas, Texas, U.S.A. https://orcid.org/0000-0002-9150-0363 Search for other works by this author on: GSW Google Scholar Hugo Delgado; Hugo Delgado 3Departamento de Vulcanologia, Instituto de Geofisica, Coyoacan, Mexico https://orcid.org/0000-0001-5263-7968 Search for other works by this author on: GSW Google Scholar James Gridley; James Gridley 4National Tsunami Warning Center, Palmer, Alaska, U.S.A. Search for other works by this author on: GSW Google Scholar Ronan Joseph Le Bras; Ronan Joseph Le Bras 5Comprehensive Test Ban Treaty Organization, Wien, Austria https://orcid.org/0000-0003-2439-6938 Search for other works by this author on: GSW Google Scholar Daniel McNamara; Daniel McNamara 6Ann Arbor, Michigan, U.S.A. Search for other works by this author on: GSW Google Scholar Steven Sherburn Steven Sherburn 7Data Science and Geohazards Monitoring Department, GNS Science, Taupo, New Zealand Search for other works by this author on: GSW Google Scholar Author and Article Information Margaret Hellweg * 1Berkeley Seismology Laboratory, University of California Berkeley, Berkeley, California, U.S.A. Stephen Arrowsmith https://orcid.org/0000-0002-9150-0363 2Southern Methodist University, Dallas, Texas, U.S.A. Hugo Delgado https://orcid.org/0000-0001-5263-7968 3Departamento de Vulcanologia, Instituto de Geofisica, Coyoacan, Mexico James Gridley 4National Tsunami Warning Center, Palmer, Alaska, U.S.A. Ronan Joseph Le Bras https://orcid.org/0000-0003-2439-6938 5Comprehensive Test Ban Treaty Organization, Wien, Austria Daniel McNamara 6Ann Arbor, Michigan, U.S.A. Steven Sherburn 7Data Science and Geohazards Monitoring Department, GNS Science, Taupo, New Zealand *Corresponding author: peggy@seismo.berkeley.edu Publisher: Seismological Society of America First Online: 25 Jan 2023 Online ISSN: 1938-2057 Print ISSN: 0895-0695 © Seismological Society of America Seismological Research Letters (2023) 94 (2A): 564–566. https://doi.org/10.1785/0220230001 Article history First Online: 25 Jan 2023 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Margaret Hellweg, Stephen Arrowsmith, Hugo Delgado, James Gridley, Ronan Joseph Le Bras, Daniel McNamara, Steven Sherburn; Introduction to the SRL Focus Section on the Hunga Tonga‐Hunga Ha’apai Eruption. Seismological Research Letters 2023;; 94 (2A): 564–566. doi: https://doi.org/10.1785/0220230001 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search Similar to the Roman god Janus, natural events often have two faces. For the people in their environment, they can be disasters, sometimes with truly terrible effects. For scientists, often geophysicists who observe the interactions on the planet, they may bring exciting new measurements and insights. The Hunga Tonga‐Hunga Ha’apai (HTHH) eruption was just such an event. It was the largest underwater eruption since 1883, when the Indonesian volcano Krakatoa produced a tsunami that killed more than 20,000 people, and the pressure wave that was heard (or measured) around the world. Similar to Krakatoa, the HTHH eruption was tremendous, with... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

We present results from a series of exploratory numerical experiments based on ocean bottom pressure and seismic data from a simulated linear array of SMART cable stations off the trench in the Sumatra-Java region. We use six rupture scenarios to calculate tsunami propagation using hydrodynamic simulations. Through these experiments we show that such an addition would result in up to several hours of improvement in the detection of earthquakes and tsunamis compared to the existing (minimal) DART systems in the northern and southern Indian Ocean. By simulating tsunamis from 58 submarine landslide scenarios in the region, we show that the SMART system can provide invaluable information in early warning against landslide tsunamis. We also calculate seismic phase arrival times from six source scenarios at existing seismic stations and our proposed SMART cables. Statistical analysis of our results shows that inclusion of such a SMART array can improve the important network parameters for the detection, evaluation and locating of seismic events.

The 2004 magnitude (M) 9.1 Sumatra-Andaman Islands earthquake in the Indian Ocean triggered the deadliest tsunami ever, killing more than 230,000 people. In response, the United Nations Educational, Scientific, and Cultural Organization (UNESCO) established three additional Intergovernmental Coordination Groups (ICGs) for the Tsunami and Other Coastal Hazards Early Warning System: for the Caribbean and Adjacent Regions (ICG/CARIBE-EWS), for the Indian Ocean, and for the Northeastern Atlantic, Mediterranean, and Connected Seas. Along with the ICG for the Pacific Ocean, which was established in 1965, one of the goals of the new ICGs was to improve earthquake and tsunami monitoring and early warning. This need was further demonstrated by the 2011 Great East Japan (Tōhoku-oki) earthquake and tsunami, which killed more than 20,000 people, and other destructive tsunamis that occurred in the Solomon Islands, Samoa, Tonga, Chile, Indonesia, and Peru. 
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\nIn response to the call to action by the UN Decade of Ocean Science for Sustainable Development (2021–2030), as well as the desired safe ocean outcome (von Hillebrandt-Andrade et al., 2021), the Intergovernmental Oceanographic Commission (IOC) of UNESCO approved the Ocean Decade Tsunami Programme in June 2021. One of its goals is to develop the capability to issue actionable alerts for tsunamis from all sources with minimum uncertainty within 10 minutes (Angove et al., 2019). While laudable, this goal presents complexities. Currently, warning depends on quick detection as well as the location and initial magnitude estimates of an earthquake that may generate a tsunami. Other factors that affect tsunamis, such as the faulting mechanism (how the faults slide past each other) and areal extent of the earthquake, currently take at least 20–30 minutes to forecast and are still subject to large uncertainties. Hence, agencies charged with tsunami early warning need to broadcast public alerts within minutes after an earthquake occurs but may struggle to meet this 10-minute goal without further technological advances, some of which are outlined in this article. 
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\nTo reduce loss of life through adequate tsunami warning requires global ocean-based seismic, sea level, and geodetic initiatives to detect high-impact earthquakes and tsunamis, combined with sufficient communication and education so that people know how to respond when they receive alerts and warnings. The United Nations International Strategy for Disaster Reduction defines an early warning system as “a set of capacities needed to generate and disseminate timely and meaningful warning information to enable individuals, communities, and organizations threatened by a hazard to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss” (UNISDR, 2012). In short, a successful early warning system requires technology coupled with human factors (Kelman and Glantz, 2014). 
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\nIn this article, we explore case studies from Japan and Canada, where scientists are leading the way in incorporating ocean observing capabilities in their early warning systems. We also explore advancements and challenges in the Caribbean, an area with a complex tectonic environment that would benefit greatly from increased global ocean observing capabilities. We also explore physical and social science interventions necessary to reduce loss of life.

The Joint Task Force, Science Monitoring And Reliable Telecommunications (JTF SMART) Subsea Cables are working to integrate environmental sensors (temperature, pressure, seismic acceleration) into submarine telecommunications cables. This will support climate and ocean observation, sea level monitoring, observations of Earth structure, tsunami and earthquake early warning and disaster risk reduction. Recent advances include regional SMART pilot systems that are the initial steps to trans-ocean and global implementation. Building on the OceanObs’19 conference and community white paper (doi:10.3389/fmars.2019.00424), this paper presents an overview of the initiative and a description of ongoing projects including: InSea wet demonstration project off Sicily; Vanuatu and New Caledonia; Indonesia; CAM-2 triangle system connecting Lisbon, Azores and Madeira; New Zealand; and Antarctica. In addition to the diverse scientific and societal benefits, the telecommunications industry mission of societal connectivity will also benefit because environmental awareness improves both individual cable system integrity and the resilience of the overall global communications network.

Meteotsunamis are created by transitory weather disturbances moving over water, have a long history of impacting the United States (U.S.) and have resulted in loss of life and property. Many of these events have been historically mischaracterized as seiches, anomalous weather-related waves, or ignored altogether. In this paper, we review meteotsunami generation mechanisms common in the U.S. and highlight several classic historical cases of U.S. meteotsunami formation and impact. We then describe recent advances in sensing and understanding that led to the establishment of initial, rudimentary alerting capabilities for the U.S. Great Lakes and U.S. East Coast. Finally, we describe the major challenges and gaps that must be overcome to move the U.S. toward a comprehensive meteotsunami forecast and warning capability. We also discuss how we envision the various relevant offices of the national oceanic and atmospheric administration (NOAA) working together to achieve this vision. These offices include the NOAA research laboratories, national weather service (NWS) Weather Forecast Offices and National Centers, National Ocean Service Center for Operational Oceanographic Products and Services and NWS Tsunami Warning Centers.

Abstract The Mw 7.1 47 km deep earthquake that occurred on 30 November 2018 had deep societal impacts across southcentral Alaska and exhibited phenomena of broad scientific interest. We document observations that point to future directions of research and hazard mitigation. The rupture mechanism, aftershocks, and deformation of the mainshock are consistent with extension inside the Pacific plate near the down‐dip limit of flat‐slab subduction. Peak ground motions >25%g were observed across more than 8000 km2, though the most violent near‐fault shaking was avoided because the hypocenter was nearly 50 km below the surface. The ground motions show substantial variation, highlighting the influence of regional geology and near‐surface soil conditions. Aftershock activity was vigorous with roughly 300 felt events in the first six months, including two dozen aftershocks exceeding M 4.5. Broad subsidence of up to 5 cm across the region is consistent with the rupture mechanism. The passage of seismic waves and possibly the coseismic subsidence mobilized ground waters, resulting in temporary increases in stream flow. Although there were many failures of natural slopes and soils, the shaking was insufficient to reactivate many of the failures observed during the 1964 M 9.2 earthquake. This is explained by the much shorter duration of shaking as well as the lower amplitude long‐period motions in 2018. The majority of observed soil failures were in anthropogenically placed fill soils. Structural damage is attributed to both the failure of these emplaced soils as well as to the ground motion, which shows some spatial correlation to damage. However, the paucity of instrumental ground‐motion recordings outside of downtown Anchorage makes these comparisons challenging. The earthquake demonstrated the challenge of issuing tsunami warnings in complex coastal geographies and highlights the need for a targeted tsunami hazard evaluation of the region. The event also demonstrates the challenge of estimating the probabilistic hazard posed by intraslab earthquakes.

Abstract. In September 2017, hurricanes Irma and Maria wreaked havoc across the Caribbean region. While obliterating the infrastructure in the Caribbean nations found along their path, both hurricanes gradually destroyed the existing seismic networks. We quantified the impact of the hurricanes on the PTWC tsunami warning capability for the Caribbean region relying on the computation of theoretical earthquake detection and response times after accounting for hurricane-related station outages. The results show that the hurricanes rendered inoperative 38 % of the 146 stations available in the Caribbean. Within the eastern Caribbean region monitored by PTWC the hurricanes exacerbated outages to an astonishing 82 % of the available 76 seismic stations. Puerto Rico, the Virgin Islands, and the Lesser Antilles suffered the brunt of both hurricanes, and their seismic networks nearly disappeared. The double punch delivered by two successive category 5 hurricanes added up to 02:43 and 04:33 minutes to the earthquake detection and response times, effectively knocking out PTWC's local tsunami warning capabilities in the region. Emergency adjustments, including the temporary reduction of the number of stations required for earthquake detection and ML magnitude release, enabled a faster response to earthquakes in the region than otherwise possible in the aftermath of hurricanes Irma and Maria.

A performance measure for a DART® tsunami buoy network has been developed. DART® buoys are used to detect tsunamis, but the full potential of the data they collect is realized through accurate forecasts of inundations caused by the tsunamis. The performance measure assesses how well the network achieves its full potential through a statistical analysis of simulated forecasts of wave amplitudes outside an impact site and a consideration of how much the forecasts are degraded in accuracy when one or more buoys are inoperative. The analysis uses simulated tsunami amplitude time series collected at each buoy from selected source segments in the Short-term Inundation Forecast for Tsunamis database and involves a set for 1000 forecasts for each buoy/segment pair at sites just offshore of selected impact communities. Random error-producing scatter in the time series is induced by uncertainties in the source location, addition of real oceanic noise, and imperfect tidal removal. Comparison with an error-free standard leads to root-mean-square errors (RMSEs) for DART® buoys located near a subduction zone. The RMSEs indicate which buoy provides the best forecast (lowest RMSE) for sections of the zone, under a warning-time constraint for the forecasts of 3 h. The analysis also shows how the forecasts are degraded (larger minimum RMSE among the remaining buoys) when one or more buoys become inoperative. The RMSEs provide a way to assess array augmentation or redesign such as moving buoys to more optimal locations. Examples are shown for buoys off the Aleutian Islands and off the West Coast of South America for impact sites at Hilo HI and along the US West Coast (Crescent City CA and Port San Luis CA, USA). A simple measure (coded green, yellow or red) of the current status of the network’s ability to deliver accurate forecasts is proposed to flag the urgency of buoy repair.

Large earthquakes pose an almost incalculable risk, causing great destruction and, often, loss of life. While large regions of the world are susceptible to this potentially devastating natural hazard, the Asia-Pacific region is particularly vulnerable. Poignant examples in the recent past include the M∼9.2 Northern Sumatra earthquake and tsunami in December, 2004 which resulted in the deaths of nearly 300,000 people, the M∼7.6 Taiwan earthquake of September, 1999, with a death toll exceeding 2000 and $20 billion in damage, and the M∼7.2 Kobe, Japan earthquake of January, 1995, that killed 5500 people and induced losses of more than $150 billion.

Crescent City (CC) is particularly susceptible to tsunami attack. The combination of tsunami signal enhancement by both distant bathymetric features and local nearshore resonance seems to be responsible for this behavior. Application of global tsunami propagation models to the Kuril Islands Tsunami of November 2006 in the companion paper (Kowalik et al., 2008) delineated the importance of distant bathymetric features for both tsunami wave amplification and for increased duration of the tsunami arriving at CC. These distant features were responsible for delivering the late, high‐energy signal, which was delayed by 2 hours from the predicted arrival time. Additional local amplification and increased duration are caused by the shelf bathymetry adjacent to CC. As the initial tsunami arrives at CC, the shelf trapping mechanism tends to excite the gravest of the natural modes. This oscillation is slowly shifted toward the natural mode closest to the period of the incident tsunami wave packet. Short‐duration wave trains tend to influence the tsunami response at CC harbor in such a way that 1 hour after the first wave arrival a much stronger wave will be generated owing to the tendency of the shelf to initially ring at the frequency of the gravest mode. Practical implications of distant and local amplification relate to the potential hazard near CC, highlighting the need for awareness of the tsunami signal duration. In this respect, two timescales are important for this event: the 2‐hour time delay due to distant bathymetric features and the 1‐hour delay due to local offshore bathymetry.