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.

On 6th July 2006, an intense swarm of earthquake activity began in the Sulu Range, Central New Britain, Papua New Guinea. The earthquakes were felt almost every one to two minutes, 24 hours a day, with modified Mercalli intensities of MM1 to MM4. They were accompanied by unusual vigorous activity in the hot springs southwest of the Sulu Range. Fearing a possible eruption and tsunami, about 1000 locals were evacuated.

The Philippine Institute of Volcanology and Seismology (PHIVOLCS) and Geoscience Australia (GA) have developed a long-term partnership in order to better understand and reduce the risks associated with earthquake hazards in the Philippines. The Project discussed herein was supported by the Australian Agency for International Development (AusAID). Specifically, this partnership was designed to enhance the exposure and damage estimation capabilities of the Rapid Earthquake Damage Assessment System (REDAS), which has been designed and built by PHIVOLCS. Prior to the commencement of this Project, REDAS had the capability to model a range of potential earthquake hazards including ground shaking, tsunami inundation, liquefaction and landslides, as well as providing information about elements at risk (e.g., schools, bridges, etc.) from the aforementioned hazards. The current Project enhances the exposure and vulnerability modules in REDAS and enable it to estimate building damage and fatalities resulting from scenario earthquakes, and to provide critical information to first-responders on the likely impacts of an earthquake in near real-time. To investigate this emergent capability within PHIVOLCS, we have chosen the pilot community of Iloilo City, Western Visayas. A large component of this project has been the compilation of datasets to develop building exposure models, and subsequently, developing methodologies to make these datasets useful for natural hazard impact assessments. Collection of the exposure data was undertaken at two levels: national and local. The national exposure dataset was gathered from the Philippines National Statistics Office (NSO) and comprises basic information on wall type, roof type, and floor area for residential buildings. The NSO census dataset also comprises crucial information on the population distribution throughout the Philippines. The local exposure dataset gathered from the Iloilo City Assessors Office includes slightly more detailed information on the building type for all buildings (residential, commercial, government, etc.) and appears to provide more accurate information on the floor area. However, the local Iloilo City dataset does not provide any information on the number of people that occupy these buildings. Consequently, in order for the local data to be useful for our purposes, we must merge the population data from the NSO with the local Assessors Office data. Subsequent validation if the Iloilo City exposure database has been conducted through targeted foot-based building inventory surveys and has allowed us to generate statistical models to approximate the distribution of engineering structural systems aggregated at a barangay level using simple wall and roof-type information from the NSO census data. We present a comparison of the national and local exposure data and discuss how information assembled from the Iloilo City pilot study - and future study areas where detailed exposure assessments are conducted - could be extended to describe the distribution of building stock in other regions of the Philippines using only the first-order national-scale NSO data. We present exposure information gathered for Iloilo City at barangay level in a format that can be readily imported to REDAS for estimating earthquake impact.

With a population of over 250 million people, Indonesia is the fourth most populous country in the world (United Nations, 2013). Indonesia also experiences more earthquakes than any other country in the world (USGS, 2015). Its borders encompass one of the most active tectonic regions on Earth including over 18 000 km of major tectonic plate boundary, more than twice that of Japan or Papua New Guinea (Bird, 2003). The potential for this tectonic activity to impact large populations has been tragically demonstrated by the 20004 Sumatra earthquake and tsunami. In order to inform earthquake risk reduction in Indonesia, a new national earthquake hazard map was developed in 2010 (Irsyam et al., 2010). In this report historical records of damaging earthquakes from the 17th to 19th centuries are used to test our current understanding of earthquake hazard in Indonesia and identify areas where further research is needed. In this report we address the following questions: - How well does our current understanding of earthquake hazard in Indonesia reflect historical activity? - Can we associate major historical earthquakes with known active faults, and are these accounted for in current assessments of earthquake hazard? - Does the current earthquake hazard map predict a frequency and intensity of shaking commensurate with the historical record? - What would the impact of these historical earthquakes be if they were to reoccur today? To help answer questions like these, this report collates historical observations of eight large earthquakes from Java, Bali and Nusa Tenggara between 1699 and 1867. These observations are then used to: - Identify plausible sources for each event; - Develop ground shaking models using the OpenQuake Engine (GEM Foundation, 2015); - Assess the validity of the current national seismic hazard map; and - Estimate fatalities were the historical events to occur today using the InaSAFE (InaSAFE.org, 2015) software.

<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>

<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>

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. 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. 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. This report provides the results of the GNSS 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 Nukualofa, Tonga from 7th to 19th July 2019. It also provides an updated height of the tide gauge derived from GNSS time series analysis and precise levelling observations.

Probabilistic seismic hazard map of Papua New Guinea, in terms of Peak Ground Acceleration, is developed for return period of 475 years. The calculations were performed for bedrock site conditions (Vs30=760 m/s). Logic-tree framework is applied to include epistemic uncertainty in seismic source as well as ground-motion modelling processes. In this regard two source models, using area source zones and smoothed seismicity, are developed. Based on available geological and seismological data, defined seismic sources are classified into 4 different tectonic environments. For each of the tectonic regimes three Ground Motion Prediction Equations are selected and used to estimate the ground motions at a grid of sites with spacing of 0.1 degree in latitude and longitude. Results show high level of hazard in the coastal areas of Huon Peninsula and New Britain/ Bougainville regions and relatively low level of hazard in the southern part of the New Guinea highlands block. In Huon Peninsula, as shown by seismic hazard disaggregation results, high level of hazard is caused by modelled frequent moderate to large earthquakes occurring at Ramu-Markham Fault zone. On the other hand in New Britain/Bougainville region, the geometry and distance to the subduction zone along New Britain Trench mainly controls the calculated level of hazard. It is also shown that estimated level of PGAs is very sensitive to the selection of GMPEs and overall the results are closer to the results from studies using more recent ground-motion models.