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Field of Research : Physical Oceanography
Field of Research : Atmospheric Dynamics
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  • Active Funded Activity

    ARC Centres Of Excellence - Grant ID: CE170100023

    Funder
    Australian Research Council
    Funding Amount
    $30,050,000.00
    Summary
    ARC Centre of Excellence for Climate Extremes. This Centre aims to transform understanding of past and present climate extremes and revolutionise Australia’s capability to predict them into the future. Climate extremes cost Australia up to $4 billion a year and will intensify over coming decades. This Centre’s blue-sky research will discover processes that explain the behaviour of present and future climate extremes. It will use its researchers, data, modelling, collaboration, graduate programme .... ARC Centre of Excellence for Climate Extremes. This Centre aims to transform understanding of past and present climate extremes and revolutionise Australia’s capability to predict them into the future. Climate extremes cost Australia up to $4 billion a year and will intensify over coming decades. This Centre’s blue-sky research will discover processes that explain the behaviour of present and future climate extremes. It will use its researchers, data, modelling, collaboration, graduate programme and early career researcher mentoring to transform Australia’s capacity to predict climate extremes. This research is expected to make Australia more resilient to climate extremes and minimise risks from climate extremes to the Australian environment, society and economy.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200102329

    Funder
    Australian Research Council
    Funding Amount
    $410,000.00
    Summary
    Improving the credibility of regional sea level rise projections. Anthropogenic sea level rise is expected to inundate low-lying islands and coastlines around the world, with multiple model projections suggesting that changes in wind patterns will lead to larger than average sea level rise along Australia’s east coast and in neighbouring small island nations. Confidence in projections of this spatial sea level rise variability is low, however, due to a strong mismatch between patterns of observe .... Improving the credibility of regional sea level rise projections. Anthropogenic sea level rise is expected to inundate low-lying islands and coastlines around the world, with multiple model projections suggesting that changes in wind patterns will lead to larger than average sea level rise along Australia’s east coast and in neighbouring small island nations. Confidence in projections of this spatial sea level rise variability is low, however, due to a strong mismatch between patterns of observed and model-projected sea level rise in recent decades. This work will use a newly developed climate model hierarchy and innovative experimental design to determine the cause of this discrepancy and will produce more credible regional sea level rise projections by clarifying and reducing projection uncertainty.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT160100162

    Funder
    Australian Research Council
    Funding Amount
    $652,000.00
    Summary
    Predictability of the El Nino-Southern Oscillation. This project aims to improve understanding of the El Nino-Southern Oscillation (ENSO), the world’s largest source of climate variability. ENSO’s effects are so large that knowledge of its current phase and forecasts of its future phase underpin seasonal rainfall, temperature and tropical cyclone forecasts worldwide. In Australia, ENSO cycles cause drought and floods. Using a suite of empirical observations and numerical models to analyse ENSO e .... Predictability of the El Nino-Southern Oscillation. This project aims to improve understanding of the El Nino-Southern Oscillation (ENSO), the world’s largest source of climate variability. ENSO’s effects are so large that knowledge of its current phase and forecasts of its future phase underpin seasonal rainfall, temperature and tropical cyclone forecasts worldwide. In Australia, ENSO cycles cause drought and floods. Using a suite of empirical observations and numerical models to analyse ENSO event precursors, initiation and predictability, this project intends to enhance skill in inter-seasonal climate forecasting and help those sectors reliant on accurate prediction.
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