Papua New Guinea (PNG) lies in a belt of intense tectonic activity that experiences high levels of seismicity. Although this seismicity poses significant risks to society, the Building Code of PNG and its underpinning seismic loading requirements have not been revised since 1982. This study aims to partially address this gap by updating the seismic zoning map on which the earthquake loading component of the building code is based. We performed a new probabilistic seismic hazard assessment for PNG using the OpenQuake software developed by the Global Earthquake Model Foundation (Pagani et al. 2014). Among other enhancements, for the first time together with background sources, individual fault sources are implemented to represent active major and microplate boundaries in the region to better constrain the earthquake-rate and seismic-source models. The seismic-source model also models intraslab, Wadati–Benioff zone seismicity in a more realistic way using a continuous slab volume to constrain the finite ruptures of such events. 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 southwestern part of mainland PNG. In comparison with the seismic zonation map in the current design standard, it can be noted that the spatial distribution of seismic hazard 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 building code of PNG. <b>Citation:</b> Ghasemi, H., Cummins, P., Weatherill, G. <i>et al.</i> Seismotectonic model and probabilistic seismic hazard assessment for Papua New Guinea. <i>Bull Earthquake Eng, </i><b>18</b>, 6571–6605 (2020). https://doi.org/10.1007/s10518-020-00966-1

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 Lautoka, Fiji from 9th to 16th January 2019. It also provides an updated ellipsoidal height of the tide gauge derived from GNSS time series analysis and precise levelling observations.

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 Manus Island, Papua New Guinea from 25th to 31st March 2019. It also provides an updated ellipsoidal height of the tide gauge derived from GNSS time series analysis and precise levelling observations.

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 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 Majuro, Marshall Islands from 4th – 11th February 2020. It also provides an updated height of the tide gauge derived from GNSS time series analysis and precise levelling observations.

Heterogeneous distribution of slip during megathrust earthquakes has been shown to significantly affect the spatial distribution of tsunami height in both numerical studies and field observations. This means that tsunami hazard maps generated using uniform slip distributions in their tsunami source models may underestimate tsunami inundation in some locations compared with real events of the same magnitude in the same location. In order to more completely define areas that may be inundated during a tsunami it is important to consider how different possible distributions of slip will impact different parts of the coastline. We generate tsunami inundation maps for the Mentawai Islands, West Sumatra, Indonesia, from a composite suite of possible source models that are consistent with current knowledge of the source region. First, a suite of earthquake source models with randomly distributed slip along the Mentawai Segment of the Sunda Subduction Zone is generated using a k-2 rupture model. From this suite we select source models that generate vertical deformation consistent with that observed in coral palaeogeodetic records of previous ruptures of the Mentawai Segment in 1797 and 1833, minus deformation observed in the 2007 Bengkulu earthquake sequence. Tsunami inundation is then modelled using high resolution elevation data for selected source models and the results compiled to generate a maximum tsunami inundation zone. This method allows us to constrain the slip distribution beneath the Mentawai Islands, where coral palaeogeodetic data is available, while allowing for greater variation in the slip distribution away from the islands, in particular near the trench where large slip events can generate very large tsunami. This method also allows us to consider high slip events on deeper portions of the megathrust between the Mentawai Islands and the Sumatran Mainland, which give greater tsunami inundation on the eastern part of the Mentawai Islands and the west coast of Sumatra compared with near-trench event. By accounting for uncertainty in slip distribution, the resulting hazard maps give a more complete picture of the areas that may be inundated compared with hazard maps derived from a single 'worst case' source model. These maps allow for more robust tsunami evacuation plans to be developed to support immediate community evacuation in response to strong or long-lasting earthquake ground shaking. From the American Geophysical Union Fall Meeting Abstracts

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 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 Apia, Samoa from 30th July to 10th August 2019. It also provides an updated height of the tide gauge derived from GNSS time series analysis and precise levelling observations.

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.

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 Pohnpei, FSM from 16th to 27th October 2018. It also provides an updated ellipsoidal height of the tide gauge derived from GNSS time series analysis and precise levelling observations.

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.

Tsunami hazard maps are generated for the Mentawai Islands, West Sumatra, Indonesia, to support evacuation and disaster response planning. A random heterogeneous slip generator is used to forward model a suite of earthquake rupture scenarios on the Mentawai Segment of the Sunda Subduction Zone. A total of 1000 rupture models that fit constraints provided by coral and geodetic records of coseismic vertical deformation from great earthquakes in 1797, 1833 and 2007 are used to model inundation and define a maximum inundation zone that envelopes all of these scenarios. Results are compared with single scenario hazard assessments developed by experts and agreed through scientific consensus building processes to assess the additional value of modelling a suite of scenarios to obtain a more robust estimate of potential inundated areas by incorporating uncertainty in the earthquake source. The model presented here, like all tsunami hazard assessments, is based on assumptions about the characteristics of future events based on past events, however by sampling a range of plausible outcomes we gain a more robust estimate of which areas may be inundated during a tsunami within the bounds of our assumptions.