Metric: Diesel rebate available to offset costs of production ($AUD/L of fuel). Measures the financial support available to reduce fuel costs for fishing operations.

This resource is a map of Sea Surface Temperature and comes from from a simulation that uses the multi-model mean forcings from RCP8.5 projection to drive an ocean eddy-resolving model (OFAM3). Insights for Warming and Acidification Increased frequency and duration of marine heatwaves increase the likelihood of more frequent and severe coral bleaching events. Tasman Sea approaches a permanent marine heatwave state by GWL3. Great Barrier Reef and Ningaloo Reef will experience annual conditions for extreme bleaching by GWL3. Acidity at GWL3: Southern Ocean surface waters south of 60S will drop below an annual mean aragonite saturation state of 1. Values above 1.0 are required to produce calcareous shells or skeletons optimally. Values below 1 are considered corrosive, and skeletons and shells may be subject to dissolution. The ocean environment will become more stressful for marine organisms and ecosystems. The references for the simulations are: Feng, M., Zhang, X., Oke, P., Monselesan, D., Chamberlain, M. A., Matear, R. J., & Schiller, A. (2016). Invigorating ocean boundary current systems around Australia during 19792014: As simulated in a near-global eddy-resolving ocean model. Journal Of Geophysical Research-Oceans. Hayashida, H., Matear, R. J., & Strutton, P. G. (2020). Background nutrient concentration determines phytoplankton bloom response to marine heatwaves. Global Change Biology, 26(9), 48004811. https://doi.org/10.1111/gcb.15255 Hayashida, H., Matear, R. J., Strutton, P. G., & Zhang, X. (2020). Insights into projected changes in marine heatwaves from a high-resolution ocean circulation model. Nature Communications, 11(1), 19. https://doi.org/10.1038/s41467-020-18241-x Matear, R. J., Chamberlain, M. A., Sun, C., & Feng, M. (2015). Climate change projection for the western tropical Pacific Ocean using a high-resolution ocean model: Implications for tuna fisheries. Deep Sea Research Part II: Topical Studies in Oceanography, 113(0), 2246. Matear, R. J., Chamberlain, M. A., Sun, C., & Feng, M. (2013). Climate change projection of the Tasman Sea from an Eddy-resolving Ocean Model. Journal Of Geophysical Research-Oceans, 118(6), 29612976. Zhang, X., Oke, P. R., Feng, M., Chamberlain, M. A., Church, J. A., Monselesan, D., et al. (2016). A near-global eddy-resolving OGCM for climate studies. Geoscientific Model Development Discussions. Diagnostics The key ocean diagnostics are displayed according to Global Warming Levels (GWLs) using the 20 year period that define a given GWL. The key ocean diagnostics are: 1. Sea Surface Temperature monthly climatology 2. Surface Aragonite Saturation State monthly climatology 3. Surface pH monthly climatology 4. Intensity of Marine Heat Wave 5. Duration of Marine Heat Wave 6. NPP monthly climatology (N mol/m^2/s) 7. Degree Heating Weeks (average of the annual maximum value dhw_amax, maximum (dhw_max) and minimum (dhw_max) annual value over GWL period 8. Bottom Temperature 9. Full ocean depth temperature (note simulation used restoring to T and S below 2000m)10. Magnitude of Bottom Stress (bmf) 10. Bottom aragonite saturation state Data/confidence Confidence: high confidence in the direction of change, medium confidence in the magnitude of change and low confidence in the ecological consequence of the changes. (consistent with IPCC AR6) Limitation: ocean simulations that are not well suited for representing the high-resolution dynamics and features of the Australian coastal areas. https://github.com/AusClimateService/hazard_ocean/blob/main/README.md

This resource is a Map of Vessel traffic in the Australian EEZ for the periods 2018/19 - 2022/23 and current 2022/23. The data presented here are summaries of the tracks of vessels between the points identified by either AUSREP or AIS, summarised to the number of KM per 0.1 deg grid square. The Craft Tracking System (CTS) and Mariweb are AMSAs vessel traffic databases. They collect vessel traffic data from a variety of sources, including terrestrial and satellite shipborne Automatic Identification System (AIS) data sources. This dataset has been built from AIS data extracted from CTS, and it contains vessel traffic data for the month of November 2024. The dataset covers the extents of Australias Search and Rescue Region. Each point within the dataset represents a vessel position report and is spatially and temporally defined by geographic coordinates and a Universal Time Coordinate (UTC) timestamp respectively. https://www.operations.amsa.gov.au/spatial/DataServices/DigitalData

This resource is a map of artifical reef permit locations provided by The Department of Climate Change, Energy, the Environment and Water

A definition of MHWs (Hobday et al. 2016) has been widely adopted by researchers and other users. A MHW is defined as a period when seawater temperatures exceed a seasonally-varying threshold (usually the 90th percentile) for at least 5 consecutive days. Successive events with gaps of 2 days or less are considered part of the same MHW. In a subsequent study (Hobday et al. 2018) we extended the definition to introduce categories of severity, based on multiples of the threshold being exceeded. Once MHWs are defined, we can define each event by a set of properties including duration (time from the start to end date, in days), intensity (the temperature anomaly above the climatology, in C, meaning how much warmer than expected for that time of year), and cumulative intensity (the integral of intensity over the duration of the event, similar to degree heating days or degree heating weeks). Over a whole year we can define the annual frequency (count of events in a particular year) and the annual marine heatwave days (the count of days in a year that were classified as being a MHW). Heatwaves can happen at any time of year, although the most extreme absolute sea temperatures are generally observed during summertime MHWs, which can become stressful to marine life. MHWs that occur in other seasons can also have important impacts, such as in the southeast of Australia where the spiny sea urchin can only colonise further south when winter temperatures are above 12 C. MHWs are caused by a wide range of processes, which vary in their importance between regions and events. The most common drivers of MHWs include ocean currents which can build up areas of warm water and air-sea heat flux, or warming through the ocean surface from the atmosphere. Winds can enhance or suppress the warming in a MHW, and climate modes like El Nio can change the likelihood of events occurring in certain regions. https://www.marineheatwaves.org/mhw-overview.html