Dynamical forecasting of marine heatwaves

Seasonal forecasting of MHWs is a new and cutting edge field of research, with significant industry and public interest.

Seasonal forecasts of ocean temperature, and marine heatwaves in particular, provide insight into conditions several months into the future. These forecasts can support operational decision making, and help inform questions such as:

  • Where do we survey this summer in the marine park?
  • Will our fish stocks be further south this year?
  • Do we need extra staff to manage fish farm operations this summer?
  • Should we harvest from our aquaculture business to avoid a heatwave?

Forecast usefulness depends on the management decision timeline and the critical environmental period affecting the decision, together with forecast accuracy at that time. Our team has spent almost 10 years working with marine stakeholders to improve forecast delivery and use. We have developed seasonal forecast tools in Australia that are used by coral reef managers, fishers and fishery management authorities, and aquaculture businesses.

Forecasts based on dynamic ocean-atmosphere models are expected to perform better than statistical forecasting techniques, particularly in a rapidly changing climate.

Experimental MHW forecasts from ACCESS-S

Project aim

This collaborative project between CSIRO and the Bureau of Meteorology seeks to develop an experimental seasonal MHW forecast product(s) for Australian waters, based on ACCESS-S, and conduct the underpinning research and verification required.

These prototype MHW products would be based on ACCESS-S, supported by scientific publications and developed in collaboration with stakeholders. The expectation would be future inclusion into the existing operational seasonal ocean outlook service for Australia, expanding the current user base and adding value to the existing service.

Project Press Release – Sussan Ley, Minister for the Environment (Aug 2020)

MHW_project_overview_flyer_Mar2021 – short overview and project approach (Mar 2021)


This project commenced August 2020 and will run for three years. Initial algorithms would be developed and tested using ACCESS-S1 hindcasts before transition to ACCESS-S2 when this version becomes available.Specific outputs include:

  • Experimental seasonal MHW outlook product suite for Australia
  • Comprehensive skill assessment of ACCESS-S SST hindcast data
  • Case studies for MHW events around Australia
  • Scientific peer-reviewed publications

Project Team

  • Alistair Hobday (CSIRO Oceans and Atmosphere)
  • Claire Spillman (Australian Bureau of Meteorology)
  • Grant Smith (Australian Bureau of Meteorology)
  • Jason Hartog (CSIRO Oceans and Atmosphere)

Publications by this team – forecasting


  1. Bureau blog on Ningaloo Nino and marine heatwaves in Western Australia: February 2021
  2. WMO article on forecasting extreme events: March 2021
  3. DeMott, C., Á. G. Muñoz, C. D. Roberts, C. M. Spillman and F. Vitart (2021). The benefits of better ocean weather forecasting. Eos 102: https://doi.org/10.1029/2021EO210601.  November 2021

Overview papers

  1. Hobday, A. J., C. M. Spillman, J. P. Eveson and J. R. Hartog (2016). Seasonal forecasting for decision support in marine fisheries and aquaculture. Fisheries Oceanography 25(S1): 45-56.
  2. Hobday, A. J., C. M. Spillman, P. Eveson, J. R. Hartog, X. Zhang and S. Brodie (2018). A Framework for Combining Seasonal Forecasts and Climate Projections to Aid Risk Management for Fisheries and Aquaculture. Frontiers in Marine Science: https://doi.org/10.3389/fmars.2018.00137.
  3. Tommasi, D., C. Stock, A. J. Hobday, R. Methot, I. Kaplan, P. Eveson, K. Holsman, T. Miller, S. Gaichas, M. Gehlen, A. Pershing, G. Vecchi, R. Msadek, T. Delworth, M. Eakin, M. Haltuch, R. Sefarian, C. Spillman, J. Hartog, S. Siedlecki, J. Samhouri, B. Muhling, R. Asch, M. Pinsky, V. Saba, S. Kapnick, C. Gaitan, R. Rykaczewski, M. Alexander, Y. Xue, K. Pegion, P. Lynch, M. Payne, T. Kristiansen, P. Lehodey and C. Werner (2017). Managing living marine resources in a dynamic environment: the role of seasonal to decadal climate forecasts. Progress in Oceanography 152: 15-49.
  4. Vanhatalo, J., A. J. Hobday, L. R. Little and C. M. Spillman (2016). Downscaling and extrapolating dynamic seasonal marine forecasts for coastal ocean users. Ocean Modelling 100: 20-30 10.1016/j.ocemod.2016.1001.1004.

Fisheries applications

  1. Brodie, S., A. J. Hobday, J. A. Smith, C. M. Spillman, J. R. Hartog, J. D. Everett, M. D. Taylor, C. A. Gray and I. M. Suthers (2017). Seasonal forecasting of dolphinfish distribution in eastern Australia to aid recreational fishers and managers. Deep Sea Research Part II: Topical Studies in Oceanography 140: 229-239.
  2. Eveson, J. P., A. J. Hobday, J. R. Hartog, C. M. Spillman and K. M. Rough (2015). Forecasting spatial distribution of SBT habitat in the GAB. FRDC Final Report 2012/239. Hobart, Tasmania. Available at http://frdc.com.au/research/final-reports/Pages/default.aspx.
  3. Eveson, J. P., A. J. Hobday, J. R. Hartog, C. M. Spillman and K. M. Rough (2015). Seasonal forecasting of tuna habitat in the Great Australian Bight. Fisheries Research 170: 39–49.
  4. Hobday, A. J., J. Hartog, C. Spillman and O. Alves (2011). Seasonal forecasting of tuna habitat for dynamic spatial management. Canadian Journal of Fisheries and Aquatic Sciences 68: 898–911.

Aquaculture applications

  1. Hobday, A. J., V. Lyne, R. Thresher, C. Spillman and A. Norman-Lopez (2011). Atlantic Salmon Aquaculture Subprogram: Forecasting ocean temperatures for salmon at the farm site. FRDC report 2010/217.
  2. Spillman, C. M., J. R. Hartog, A. J. Hobday and D. Hudson (2015). Predicting environmental drivers for prawn aquaculture production to aid improved farm management. Aquaculture 447: 56–65.
  3. Spillman, C. M. and A. J. Hobday (2014). Dynamical seasonal forecasts aid salmon farm management in an ocean warming hotspot. Climate Risk Management 1: 25-38.

Coral reef applications

  1. Smith, G. and C. Spillman (2019). New high-resolution sea surface temperature forecasts for coral reef management on the Great Barrier Reef. Coral Reefs: https://doi.org/10.1007/s00338-00019-01829-00331.
  2. Spillman, C. M., O. Alves and D. A. Hudson (2011). Seasonal Prediction of Thermal Stress Accumulation for Coral Bleaching in the Tropical Oceans. Monthly Weather Review 139: 317-331.
  3. Spillman, C. M., O. Alves and D. A. Hudson (2012) Predicting thermal stress for coral bleaching in the Great Barrier Reef using a coupled ocean-atmosphere seasonal forecast model. International Journal of Climatology 33:1001-1014.
  4. Prediction for the Great Barrier Reef: http://media.bom.gov.au/social/blog/2373/how-predicting-ocean-temperature-helps-care-for-the-great-barrier-reef/