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Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

J Salinger1, A J Hobday2, R J Matear2

  • 1School of Environment, The University of Auckland, Auckland, New Zealand; CSIRO Oceans and Atmosphere, Hobart, TAS, Australia.

Advances in Marine Biology
|August 31, 2016
PubMed
Summary

Predicting marine ecosystem changes requires understanding decadal climate variability. Key Australian climate drivers like ENSO influence marine industries, necessitating improved forecasting for risk reduction.

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AustraliaClimate driversDecadalEl Niño/Southern OscillationExtremesForecastingIndian Ocean DipoleInterdecadal Pacific OscillationMarine resourcesSouthern Annular Mode

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Area of Science:

  • Marine ecology and climate science.
  • Oceanography and climate dynamics.
  • Environmental forecasting.

Background:

  • Marine ecosystems are influenced by climate variability across multiple timescales.
  • Interannual to decadal climate variability impacts on marine industries are understudied.
  • Large-scale ocean climate modes offer predictability up to 10 years.

Purpose of the Study:

  • To investigate decadal climate variability and its impacts on Australian marine ecosystems and industries.
  • To illustrate the roles of major climate drivers in extreme marine events.
  • To outline methods for generating and translating climate forecasts for marine end-users.

Main Methods:

  • Analysis of major Australian climate drivers: Southern Annular Mode, Indian Ocean Dipole, El Niño/Southern Oscillation, and Interdecadal Pacific Oscillation.
  • Case studies of extreme events: Western Australia marine heatwave, Great Barrier Reef coral bleaching, and Queensland flooding.
  • Description of statistical and dynamical forecasting approaches for climate drivers.

Main Results:

  • Identified key climate drivers influencing Australian marine environments.
  • Demonstrated the link between climate drivers and specific extreme marine events.
  • Outlined pathways for translating climate forecasts into actionable information for marine sectors.

Conclusions:

  • Improved decadal forecasting is crucial for managing marine resources and reducing environmental risk.
  • Significant investment is needed in models, observing systems, data collection, and decision support tools.
  • Collaboration between forecast developers and marine industries is essential for effective forecast-based decision-making.