Australian atmospheric pressure and sea level data during the 2022 Hunga-Tonga Hunga-Ha'apai volcano tsunami.

On January 15, 2022, an ongoing eruption at the Hunga-Tonga Hunga-Ha'apai volcano generated a large explosion which resulted in a globally observed tsunami and atmospheric pressure wave. This paper presents time series observations of the event from Australia including 503 mean sea level pressure (MSLP) sensors and 103 tide gauges. Data is provided in its original format, which varies between data providers, and a post-processed format with consistent file structure and time zone. High-pass filtered variants of the data are also provided to facilitate study of the pressure wave and tsunami. For a minority of tide gauges the raw sea level data cannot be provided, due to licence restrictions, but high-pass filtered data is always provided. The data provides an important historical record of the volcanic pressure wave and tsunami in Australia. It will be useful for research on atmospheric and ocean waves associated with large volcanic eruptions.

From offshore to onshore probabilistic tsunami hazard assessment via efficient Monte Carlo sampling.

Offshore Probabilistic Tsunami Hazard Assessments (offshore PTHAs) provide large-scale analyses of earthquake-tsunami frequencies and uncertainties in the deep ocean, but do not provide high-resolution onshore tsunami hazard information as required for many risk-management applications. To understand the implications of an offshore PTHA for the onshore hazard at any site, in principle the tsunami inundation should be simulated locally for every earthquake scenario in the offshore PTHA. In practice this is rarely feasible due to the computational expense of inundation models, and the large number of scenarios in offshore PTHAs. Monte Carlo methods offer a practical and rigorous alternative for approximating the onshore hazard, using a random subset of scenarios. The resulting Monte Carlo errors can be quantified and controlled, enabling high-resolution onshore PTHAs to be implemented at a fraction of the computational cost. This study develops efficient Monte Carlo approaches for offshore-to-onshore PTHA. Modelled offshore PTHA wave heights are used to preferentially sample scenarios that have large offshore waves near an onshore site of interest. By appropriately weighting the scenarios, the Monte Carlo errors are reduced without introducing bias. The techniques are demonstrated in a high-resolution onshore PTHA for the island of Tongatapu in Tonga, using the 2018 Australian PTHA as the offshore PTHA, while considering only thrust earthquake sources on the Kermadec-Tonga trench. The efficiency improvements are equivalent to using 4-18 times more random scenarios, as compared with stratified-sampling by magnitude, which is commonly used for onshore PTHA. The greatest efficiency improvements are for rare, large tsunamis, and for calculations that represent epistemic uncertainties in the tsunami hazard. To facilitate the control of Monte Carlo errors in practical applications, this study also provides analytical techniques for estimating the errors both before and after inundation simulations are conducted. Before inundation simulation, this enables a proposed Monte Carlo sampling scheme to be checked, and potentially improved, at minimal computational cost. After inundation simulation, it enables the remaining Monte Carlo errors to be quantified at onshore sites, without additional inundation simulations. In combination these techniques enable offshore PTHAs to be rigorously transformed into onshore PTHAs, with quantification of epistemic uncertainties, while controlling Monte Carlo errors.

The Tsunami Threat to Sydney Harbour, Australia: Modelling potential and historic events.

Tsunami modelling of potential and historic events in Australia's Sydney Harbour quantifies the potentially damaging impacts of an earthquake generated tsunami. As a drowned river valley estuary exposed to distant source zones, these impacts are predominantly high current speeds (>2 m/s), wave amplification and rapid changes in water level. Significant land inundation only occurs for scenarios modelled with the largest waves (9.0 MW source). The degree of exposure to the open ocean and the geomorphology of locations within the Harbour determine the relative level of these impacts. Narrow, shallow channels, even those sheltered from the open ocean, create a bottleneck effect and experience the highest relative current speeds as well as elevated water levels. The largest maximum water levels (>8 m) occur in exposed, funnel-shaped bays and wave amplification is greatest at locations exposed to the open ocean: >7 times deep water wave heights for 9.0 MW source waves. Upstream attenuation rates of runup and maximum water level show a linear correlation with wave height parameters at the 100 m depth contour and may provide some predictive capabilities for potential tsunami impacts at analogous locations. In the event of a tsunami in Sydney Harbour, impacts may threaten marine traffic and infrastructure.

Seamless bathymetry and topography datasets for New South Wales, Australia.

This paper describes three datasets of seamless bathymetry and coastal topography for Sydney Harbour (Port Jackson), Botany and Bate Bays, and the Hawkesbury River. The datasets used to form these compilations were the most recent and highest quality available to the authors and were originally collated using the software ESRI ArcGIS. The original compilation of this data was undertaken to support tsunami modelling research by the authors of this paper. Before processing, all data were adjusted and/or reprojected to conform to the vertical datum Australian Height Datum (AHD) and horizontal projection WGS84 UTM zone 56. Data resolution and density was highly variable and grid resolutions of the final datasets were selected as the highest resolutions possible using the most sparse data in the compilation in question. For areas where no data were available, the ESRI ArcGIS interpolation tool, Topo to Raster, was used to provide a best estimate. These dastasets of three important Australian waterways provide a useful tool for coastal research and scientific interest.