This dataset details all tropical cyclones that are known to have occurred in the region south of the equator between 90E and 160E. The data has been sourced from the Tropical Cyclone Database, maintained by the Bureau of Meteorology (BOM). This record represents a snapshot of the data taken on 23/03/2023 for the purposes of generating a mapping visualisation of recent cyclone activity. The most current database can be downloaded from the BOM website: http://www.bom.gov.au/cyclone/tropical-cyclone-knowledge-centre/databases/ Point data from the BOM has been converted into cyclone tracks for visualisation. The data and mapping layer will be refreshed annually following cyclone season (May-June each year). Last updated 21st November 2023.

This resource contains access links to all data collected and and created under the ACE-CRC program. See 'online resources' section of this record for index of all online ACE-CRC data.

Cyclone data was used to develop a spatial model using the intensity and to determine whether Sea Surface Temperature or Tropical Cyclone Heat Potential contributes to the North Indian Ocean cyclone intensity and, if so, how?

The prolonged rainfall reduction in South West Western Australia (SWWA) in recent decades has previously been reported to be unprecedented in the past 750 years. This rainfall reduction has reduced the water supply for both residents and agriculture in SWWA. However, the cause of this rainfall reduction is unclear. The relatively short length of the SWWA instrumental rainfall record limits long term studies of SWWA rainfall. In this study, SWWA rainfall is reconstructed based on a statistically significant negative correlation between SWWA rainfall and snowfall at Dome Summit South (DSS), East Antarctica. The 2000-year DSS snow accumulation record is used to reconstruct SWWA rainfall from 22 BCE to 2015 CE. With Cumulative Summation (CUSUM) analysis applied to the rainfall reconstruction, it is found that SWWA rainfall started to reduce around 1971 CE. This prolonged rainfall reduction is unprecedented during the past 750 years, but there have been two prior droughts of similar duration and intensity during the past 2000 years. Applying statistical techniques to compare the rainfall reconstruction with climate model simulations, it is found that greenhouse gases are likely to be the dominant driver of the SWWA rainfall drying trend after 1971 CE. This record describes the Honours Thesis [available for download in 'Online Resources' section of thsi record]. For the data generated by this project, see https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/d7d5ea56-f972-435d-b44b-44fea598150c

'Weather@home ANZ' is a global citizen science distributed computing project being run as part of the Oxford-based 'weather@home' project, which is part of 'climateprediction.net'. In this experiment, a detailed limited area (regional) climate model is embedded within the less detailed 'driving' global model. This higher-resolution regional model is able to tell us in unprecedented detail about potential changes to patterns of weather as climate changes. In the initial 'weather@home' experiment launched in 2010, the project team released this regional modelling capability for three regions: Europe, Southern Africa and the Western USA. This capability has been extended to other regions around the world and the first such new region to be developed was the Australasian region encompassing Australia, New Zealand and surrounding areas, which was launched to the public in 2014. This particular part of the project - 'weatherathome ANZ' - has received support from the University of Oxford (U.K.), the U.K. Met. Office, the Universities of Melbourne and Tasmania (Australia), the Tasmanian Partnership for Advanced Computing and the New Zealand National Institute for Water and Atmospheric Research (NIWA). 'weather@home' has also been supported by Microsoft Research.

This atlas uses all of the available full water column profiles of oxygen, salinity and temperature available as part of the World Ocean Atlas released in 2018. Instead of optimal interpolation we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° x 1/2° degree atlas covers the period 1955 to 2018 in 1 year intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints thus offering improvements in the representations of oxygen, salinity and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84% ± 0.42%. For this period temperature driven solubility changes explain about 21% of the oxygen decline over the full water column, in the upper 100 m solubility changes can explain all of the oxygen decrease, for the 100-600 m depth range it can explain only 29%, 19% between 600 m and 1000 m, and just 11% in the deep ocean.