Oral Presentation AMOS Annual Meeting and International Conference on Tropical Meteorology and Oceanography

Forecasting extreme Sea Surface Temperatures for New Zealand aquaculture (#49)

Catherine de Burgh-Day 1 , Claire Spillman 1 , Craig Stevens 2 3 , Oscar Alves 1 , Graham Rickard 2
  1. The Australian Bureau of Meteorology, Docklands, VIC, Australia
  2. National Institute of Water and Atmospheric Research, Wellington, New Zealand
  3. The University of Auckland, Auckland, New Zealand

Coupled ocean-atmosphere models can be used to predict anomalous sea surface temperature (SST) from weeks to months in advance. A joint initiative is underway between the Australian Bureau of Meteorology and the National Institute of Water and Atmospheric Research (NIWA) in New Zealand to develop multi-week and seasonal (to approximately 6 months ahead) ocean forecast products for aquaculture in New Zealand, focusing on several geographic regions of interest to the industry. These products utilize the Bureau’s new coupled seasonal prediction system ACCESS-S1, which was made operational in mid-2018. Compared to its predecessor POAMA, ACCESS-S1 has improved horizontal (25km vs 100-200km) and vertical (1m vs 15m for upper layers) resolution in the ocean model, leading to improved detail in coastal areas and upper-level sea temperature forecasts.

We have assessed the ocean temperature and 300m heat content forecast skill of ACCESS-S1 around New Zealand. This skill assessment is based on a set of retrospective ensemble forecasts for 1990-2012, verified against satellite observations and the Bluelink Reanalysis V3.5. An initial set of trial forecast products has also been created, including both ensemble mean products to show the predicted mean state, and probabilistic products to provide advance warning of extreme events such as marine heat waves.

We show that the improved resolution of ACCESS-S1 over POAMA creates a new opportunity to give advance warning of extreme SST events for localized and inshore regions around New Zealand, providing a potentially valuable management tool for aquaculture and fisheries industries.