In June 2012 Geoscience Australia was commissioned by Commonwealth Scientific and Industrial Research Organisation (CSIRO) to undertake detailed wind hazard assessments for 14 Pacific Island countries and East Timor as part of the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program. PACCSAP program follows on from work Geoscience Australia did for the Pacific Climate Change Science Program (PCCSP) looking at CMIP3 generation of climate models. The objective of this study is to improve scientific knowledge by examining past climate trends and variability to provide regional and national climate projections. This document presents results from current and future climate projections of severe wind hazard from tropical cyclones for the 15 PACCSAP partner countries describing the data and methods used for the analysis. The severe wind hazard was estimated for current (1981 to 2000) and future (2081 to 2100) climate scenarios. Tropical-cyclone like vortices from climate simulations conducted by CSIRO using six Coupled Model Intercomparison Project phase 5 (CMIP5) models (BCC-CSM1.1, NorESM1-M, CSIRO-Mk3.6, IPSL-CM5A, MRI-CGM3 and GFDL-ESM2M) as well as the International Best Track Archive for Climate Stewardship were used as input to the Geoscience Australia's Tropical Cyclone Risk Model to generate return period wind speeds for the 15 PACCSAP partner countries. The Tropical Cyclone Risk Model is a statistical-parametric model of tropical cyclone behaviour, enabling users to generate synthetic records of tropical cyclones representing many thousands of years of activity. The 500-year return period wind speed is analysed and discussed into more details in this report, since it is used as a benchmark for the design loads on residential buildings. Results indicate that there is not a consistent spatial trend for the changes in 500-year cyclonic wind speed return period when CMIP5 models are compared individually. BCC-CSM1M and IPSL-CM5A presented an increase in the annual TC frequency for East Timor, northern hemisphere and southern hemisphere. On the other hand, NorESM1M showed a decrease in the annual TC frequency for the same areas. The other three models showed a mixed of increase and decrease in their annual TC frequency. When CMIP5 models were analysed by partner county capitals for the 500-year cyclonic wind speed return period, IPSL-CM5A and GFDL-ESM2M models presented an increase in the cyclonic wind speed intensity for almost all capitals analysed with exception of Funafuti (GFDL-ESM2M), which presented a decrease of 0.7% and Honiara (IPSL-CM5A) with a decrease of 1.6%. The tropical cyclone annual frequency ensemble mean indicates an increase in the tropical cyclone frequency within all three regions considered in this study. When looking at individual capitals, a slight increase in the 500-year return period cyclonic wind speed ensemble mean varying between 0.8% (Port Vila) to 9.1% (Majuro) is noticed. A decline around 2.4% on average in the 500-year return period cyclonic wind speed ensemble mean is observed in Dili, Suva, Nukualofa and Ngerulmud. The ensemble spatial relative change did not show any particular consistency for the 500-year cyclonic wind speed. Areas where Marshall Islands and Niue are located presented an increase in the 500-year cyclonic wind speed while a decrease is observed in areas around South of Vanuatu, East of Solomon Islands, South of Fiji and some areas in Tonga. The information from the evaluation of severe wind hazard from tropical cyclones, together with other PACCSAP program outputs, will be used to build partner country capacity to effectively adapt and plan for the future and overcome challenges from climate change.

The Government of Indonesia has committed to deploying a network of 500 strong-motion sensors throughout the nation. The data from these sensors have the potential to provide critical near-real-time information on the level of ground shaking and potential impact from Indonesian earthquakes near communities. We describe the implementation of real-time ‘ShakeMaps’ within Indonesia's Agency of Meteorology, Climatology and Geophysics (BMKG). These ShakeMaps are intended to underpin real-time earthquake situational awareness tools. The use of the new strong-motion network is demonstrated for two recent earthquakes in northern Sumatra: the 2 July 2013 Mw 6.1 Bener Meriah, Sumatra and the 10 October 2013 Mw 5.4 Aceh Besar earthquakes. The former earthquake resulted in 35 fatalities, with a further 2400 reported injuries. The recently integrated ShakeMap system automatically generated shaking estimates calibrated by BMKG's strong-motion network within 7 min of the Bener Meriah earthquake's origin, which assisted the emergency response efforts. Recorded ground motions are generally consistent with theoretical models. However, more analysis is required to fully characterize the attenuation of strong ground motion in Indonesia.

Through Australian Department of Foreign Affairs and Trade, Geoscience Australia has been working closely with the Government of Papua New Guinea technical agencies (Rabaul Volcano Observatory, Port Moresby Geophysical Observatory, and Engineering Geology Branch) since September 2010 to enhance their capabilities to monitor and assess natural hazards. The objective of this program is to support the Government of Papua New Guinea in developing fundamental information and practices for the effective response and management of natural hazard events in PNG. Earthquakes as natural hazards are one of the key focus points of this project, as they continue to cause loss of life and widespread damage to buildings and infrastructure in Papua New Guinea. The country’s vulnerability to earthquakes is evident from the significant socio-economic consequences of recent major events in Papua New Guinea, e.g., a magnitude 7.5 earthquake that occurred in the Hela Province of Papua New Guinea in 2018. Earthquake risk is likely to increase significantly in the years to come due to the growth in population and urbanization in Papua New Guinea. However, earthquake risk, unlike hazard, can be managed and minimized. One obvious example would be minimizing earthquake risk by constructing earthquake-resistant structures following building standards. The high level of earthquake hazard of Papua New Guinea has been long recognised and the suite of building standards released in 1982 contained provisions to impart adequate resilience to buildings based on the best understanding of seismic hazard available at that time. However, the building standards and incorporated seismic hazard assessment for Papua New Guinea has not been updated since the 1980s. The integration of modern national seismic hazard models into national building codes and practices provides the most effective way that we can reduce human casualties and economic losses from future earthquakes. This report aims at partially fulfilling this task by performing a probabilistic seismic hazard assessment to underpin a revision of the earthquake loading component of the building standards of Papua New Guinea. The updated assessment offers many important advances over its predecessor. It is based on a modern probabilistic hazard framework and considers an earthquake catalogue augmented with an additional four decades-worth of data. The revised assessment considers advances in ground-motion modelling through the use of multiple ground-motion models. Also, for the first time, the individual fault sources representing active major and microplate boundaries are implemented in the input hazard model. Furthermore, the intraslab sources are represented realistically by using the continuous slab volume to constrain the finite ruptures of such events. This would better constrain the expected levels of ground motion at any given site in Papua New Guinea. The results suggest a high level of hazard in the coastal areas of the Huon Peninsula and the New Britain–Bougainville region, and a relatively low level of hazard in the southern part of the New Guinea Highlands Block. In comparison with the seismic zonation map in the current design standard, it can be noted that the spatial distribution used for building design does not match the bedrock hazard distribution of this study. In particular, the high seismic hazard of the Huon Peninsula in the revised assessment is not captured in the current seismic zoning map, leading to a significant under-estimation of hazard in PNG’s second-largest city, Lae. It can also be shown that in many other regions and community localities in PNG the hazard is higher than that regulated for the design of buildings having a range of natural periods. Thus, the need for an updated hazard map for building design has been confirmed from the results of this study, and a revised map is developed for consideration in a revised building standard of Papua New Guinea.

<div>The city of Lae is Papua New Guinea (PNG)’s second largest, and is the home of PNG’s largest port. Here, a convergence rate of ~50 mm/yr between the South Bismarck Plate and the Australian Plate is accommodated across the Ramu-Markham Fault Zone (RMFZ). The active structures of the RMFZ are relatively closely spaced to the west of Lae. However, the fault zone bifurcates immediately west of the Lae urban area, with one strand continuing to the east, and a second strand trending southeast through Lae City and connecting to the Markham Trench within the Huon Gulf. </div><div>The geomorphology of the Lae region relates to the interaction between riverine (and limited marine) deposition and erosion, and range-building over low-angle thrust faults of the RMFZ. Flights of river terraces imply repeated tectonic uplift events; dating of these terraces will constrain the timing of past earthquakes and associated recurrence intervals. Terrace riser heights are typically on the order of 3 m, indicating causative earthquake events of greater than magnitude 7. </div><div>Future work will expose the most recently active fault traces in trenches to assess single event displacements, and extend the study to the RMFZ north of Nadzab Airport. These results will inform a seismic hazard and risk assessment for Lae city and surrounding region.</div> Presented at the 2023 Australian Earthquake Engineering Society (AEES) Conference

<div>Australia has been supporting 13 Pacific Island countries (PICs) to measure, record and analyse long-term sea level and land motion for over 25 years. This is known as the Pacific Sea Level and Geodetic Monitoring (PSLGM) project which is funded by Australian Aid under the Climate and Oceans Support Program in the Pacific (COSPPac). </div><div>The sea level data is collected continuously at one or two tide gauges in each of the 13 PICs. The land motion data is collected continuously at one or two Global Navigation Satellite System (GNSS) stations in each of the 13 PICs. The height difference between the tide gauges and GNSS stations is observed once every 18 months (approximately). The data is then analysed to produce sea level information-based products (e.g. tide calendars) and to inform about motion of the land (e.g. for coastal infrastructure planning). </div><div>The PSLGM project involves Australian science agencies (Bureau of Meteorology (Bureau) and Geoscience Australia (GA)) working in partnership with regional organisations (Pacific Community (SPC)), and Pacific government ministries (meteorology and land and survey departments).</div><div><br></div><div>This GA Record reports findings regarding the absolute vertical rate of movement (i.e. the rate at which the land is moving up or down with respect to the centre of the Earth) of 13 Pacific Island Countries tide gauges over the period 2003 – 2022 based on the analysis of Global Navigation Satellite System (GNSS) data and levelling data.&nbsp;&nbsp;</div><div><br></div>

<div>On January 15, 2022, an ongoing eruption at the Hunga 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 111 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 Hunga volcano pressure wave and tsunami in Australia. It will be useful for research in atmospheric and ocean waves associated with large volcanic eruptions. <b>Citation:</b> Davies, G., Wilson, K., Hague, B. et al. Australian atmospheric pressure and sea level data during the 2022 Hunga-Tonga Hunga-Ha’apai volcano tsunami. <i>Sci Data</i> <b>11</b>, 114 (2024). https://doi.org/10.1038/s41597-024-02949-2

<div>The Australian Bureau of Meteorology (BoM), Geoscience Australia (GA) and the Pacific Community (SPC) work together on the Australian Aid funded Pacific Sea Level and Geodetic Monitoring Project (PSLGMP). The project is focused on determining the long-term variation in sea level through observation and analysis of changes in the height of the land (using Global Navigation Satellite System (GNSS) data) and changes in the sea level (using tide gauges managed and operated by the BoM. It is the role of GA and SPC to provide information about ‘absolute’ movement of the tide gauge (managed by BoM) using GNSS to continuously monitor land motion and using levelling (SPC) to measure the height difference between the tide gauge and GNSS pillar every 18 months. </div><br><div>Land movement caused by earthquakes, subsidence and surface uplift have an important effect on sea level observations at tide gauges. For example, a tide gauge connected to a pier which is subsiding at a rate of 5 mm per year would be observed as a rate of 5 mm per year of sea level rise at the tide gauge. Because of this, it is important to measure, and account for, the movement of land when measuring ‘absolute’ sea level variation - the change in the sea level relative to the centre of the Earth. Relative sea level variation on the other hand is measured relative to local buildings and landmass around the coastline.</div><div>Geoscience Australia’s work enables more accurate 'absolute' sea level estimates by providing observations of land motion which can be accounted for by BoM when analysing the tide gauge data.</div><div><br></div>

Tsunami hazard modelling for Tonga shows the potential impacts of tsunami generated by a very large earthquake on the nearby Tongan Trench.

<div>The Australian Bureau of Meteorology (BoM), Geoscience Australia (GA) and the Pacific Community (SPC) work together on the Australian Aid funded Pacific Sea Level and Geodetic Monitoring Project (PSLGMP). The project is focused on determining the long-term variation in sea level through observation and analysis of changes in the height of the land (using Global Navigation Satellite System (GNSS) data) and changes in the sea level (using tide gauges managed and operated by the BoM. It is the role of GA and SPC to provide information about ‘absolute’ movement of the tide gauge (managed by BoM) using GNSS to continuously monitor land motion and using levelling (SPC) to measure the height difference between the tide gauge and GNSS pillar every 18 months.</div><div><br></div><div>Land movement caused by earthquakes, subsidence and surface uplift have an important effect on sea level observations at tide gauges. For example, a tide gauge connected to a pier which is subsiding at a rate of 5 mm per year would be observed as a rate of 5 mm per year of sea level rise at the tide gauge. Because of this, it is important to measure, and account for, the movement of land when measuring ‘absolute’ sea level variation - the change in the sea level relative to the centre of the Earth. Relative sea level variation on the other hand is measured relative to local buildings and landmass around the coastline.</div><div>Geoscience Australia’s work enables more accurate 'absolute' sea level estimates by providing observations of land motion which can be accounted for by BoM when analysing the tide gauge data.</div><div><br></div><div>This report provides the results of the GNSS monument monitoring survey & high precision level survey completed between the Sea Level Fine Resolution Acoustic Measuring Equipment (SEAFRAME) tide gauge and the GNSS Continuously Operation Reference Station (CORS) in Funafuti, Tuvalu in October of 2019. It also provides an updated height of the tide gauge derived from GNSS time series analysis and precise levelling observations.</div><div><br></div>

In this study, we performed a probabilistic seismic hazard assessment (PSHA) for Papua New Guinea (Figure 1) to underpin a revision of the seismic zoning map for the national building code of PNG (Figure 2). To perform PSHA, we compiled a composite catalogue for the period of 1900-2017 (Figure 3). We then developed magnitude conversion equations to homogenize the catalogue in terms of moment magnitude scale (M_W , Figure 4). In contrast to previous studies in PNG (e.g. Ghasemi et. al, 2016), we developed a seismotectonic model that includes 18 fault models (Figure 5) combined with the distributed seismicity (Figure 6) to model earthquake sources. Following the classical PSHA methodology, we mapped the seismic hazard in terms of peak ground acceleration (PGA) with 10% probability of exceedance in 50 years (Figure 1). We also computed hazard curves (Figure 7) and uniform hazard spectra (Figure 8) at the location of major population centres in PNG (black circles in Figure 1). Results of this study indicate a high level of hazard in the coastal areas of Huon Peninsula and New Britain–Bougainville regions and a relatively low level of hazard in the southwestern part of Papua New Guinea. To identify earthquake sources that are contributing most to the overall hazard, we performed hazard disaggregation analysis for all of the major localities in PNG (e.g. Figure 9). Results of the hazard disaggregation analysis shows that in the Huon Peninsula region, the frequent moderate to large earthquakes occurring on the Ramu-Markham Fault Zone results in high seismic hazard (Figure 9). The New Britain–Bougainville region also has relatively high seismic hazard. The proximity to the subduction zone of the New Britain Trench is the main influence on the calculated level of hazard