Antarctic Landfast sea ice (fast ice) is important climatologically, biologically and for logistics for short time-scale anomalies. Until recently, there hasn’t been an accurate, high-resolution fast ice extent dataset which can support an analysis on drivers of fast ice and most studies only investigate fast ice on limited regions of Antarctica in a limited time scale. There is a need to extend the spatial and temporal studying coverage to provide detailed information on the Antarctic coast over a longer period. This is the first detailed analysis to identify and quantify correlation between the environmental anomaly and fast ice anomaly mainly in the east Antarctic coast. By examining regional/local fast ice extent in in east Antarctic coast in the context of the broader and/or remote-teleconnected atmospheric circulation/properties using spatial correlation techniques, a strong correlation between NINO3 region and Lützow-Holm Bay fast ice and similar and significant correlation of regional scale factors from Lützow-Holm Bay to Mawson Coast mainly are found. The results of this thesis suggest that the pack ice, atmospheric factors and oceanic factors are important for interpreting fast ice anomalies. To identify and quantify correlation between the pack ice, temperature at 2m, wind at 10m, snow fall anomaly, sea surface temperature anomaly, ocean heat content anomaly and fast ice anomaly, backward multiple linear regression is conducted to demonstrate some predictive fast ice driver information by quantifying the correlation between different drivers and fast ice anomaly. The multiple linear regression also suggests that oceanic influences including pack ice are generally more important than atmospheric influences. Future experiments could be conducted to interpret fast ice anomalies in the context of the ocean mainly.

Baited remote underwater stereo-video (stereo-BRUV) were used to sample the fish assemblages of the Hunter Marine Park and adjacent Port Stephens - Great Lakes Marine Park at equivalent depths. Stereo-BRUV were deployed in both autumn and spring from spring 2016 to autumn 2018 and at depth of 32-105m. The videos were analyse to all fish species to the lowest taxonmic level and estimate relative abundance (MaxN) and lengths of all species. This information was used to form a baseline of the benthic fish assemblages of the Hunter Marine Park. This study was done as part of the NESP Marine Biodiversity Hub D3 project (https://www.nespmarine.edu.au/project/project-d3-implementing-monitoring-amps-and-status-marine-biodiversity-assets-continental).

This project will determine the downburst thunderstorms over Tasmania from the Severe Storms Archive, investigate the atmospheric condition during those downburst thunderstorms and determine the probability of meteorological conditions suitable for downburst thunderstorms over Tasmania during 1990-2019. This project will use the recently completed Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) dataset, which offers more than 100 atmospheric model variables at higher resolution in space and time than existing global reanalyses (Jakob et al. 2017). The hourly temporal resolution, 70 levels vertical resolution and 1.5 km horizontal resolution, which has been developed specifically for Tasmania and other three regions, makes it particularly powerful in comparison to larger scale reanalyses for analysis of short-term phenomena like thunderstorms and their environments in Tasmania.

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

Voyage IN2019_V04 contributed an additional 29,000 kms2 of seafloor survey data to the Coral Sea knowledge base. From this new bathymetric data individual seamounts have been extracted and have been classified to the Geoscience Australia Geomorphology Classification Scheme. This dataset contains two layers representing the classification layers- 1) Surface (Plain, Slope, Escarpment) and 2) fine scale Geomorphology of the seamount for the Cassowary Seamount. Ongoing research with this survey data will provide new insights into the detailed geomorphic shape and spatial relationships between adjacent seabed features. This information will be released in future publications to show the potential of how the scale of such seafloor data can be used for predictive habitat modelling when analysed with the biological data overlays.

Ecosystem data was collected as part of an integrated study of the continental shelf over a 2 and a half year period between November 2015 and January 2018. Data were collected bi-monthly through the spring to autumn (November, January, March, May). Stations were situated perpendicular to shelf bathymetry, ranging in depth from ~50 m to 100 m near the edge of the shelf and were located between 5 km and 15 km from land; encompassing from south Storm Bay, past the southern tip of Bruny Island and into the Southern Ocean (south-east Tasmania, Australia). Data collected focused on each trophic level, characterizing the zooplankton community, fish schools and marine predators. The overarching aim of the study was to investigate the effects of long term warming, and a marine heatwave event on zooplankton dynamics in terms of community response variables and the flow-on effects of changing lower-trophic level dynamics for top predators.

The Indonesian Throughflow (ITF) is connects the Pacific Ocean and the Indian Ocean in the tropics. The ITF plays an essential role in ocean circulation and regional climate: it hosts strong mixing that can change water-mass properties, influences the sea surface temperature in both oceans and affects the global ocean volume and heat transports. The ITF transports water properties across Indonesian Seas characterized by complex topography with most of the water entering through two main inflow straits, Makassar and Lifamatola straits, and exiting into the Indian Ocean through three main outflow straits, Ombai, Lombok and Timor straits. The ITF shows variabilities on different time scales, including decadal, interannual, seasonal and intra-seasonal. The ITF variability on intra-seasonal time scales is driven by remotely generated Kelvin and Rossby waves that propagate into the Indonesian Seas from the Indian Ocean and Pacific Ocean. This project focuses on the variability driven by Kelvin waves that propagate into Indonesian seas through three main outflow straits (Ombai, Lombok and Timor). We use a global ocean model and a high-resolution regional ITF model to characterize these variabilities at different depths and in different straits. We also use the mooring observations from the INSTANT program to validate the ocean models.