Seasonal coastal sea-level prediction
Seasonal coastal sea-level prediction using a dynamical model
Abstract
Sea level varies on a range of time scales from tidal through to decadal and centennial change. To date little attention has been focussed on the prediction of interannual sea-level anomalies. Here, we demonstrate that forecasts of coastal sea-level anomalies from the dynamical Predictive Ocean Atmosphere Model for Australia (POAMA) have significant skill throughout the equatorial Pacific and along the eastern boundaries of the Pacific and Indian oceans at lead times out to eight months.
POAMA forecasts for the western Pacific generally have greater skill than persistence, particularly at longer lead times. POAMA also has comparable or greater skill than previously published statistical forecasts from both a Markov model and canonical correlation analysis. Our results indicate the capability of physically-based models to address the challenge of providing skilful forecasts of seasonal sea-level fluctuations for coastal communities over a broad area and at a range of lead times.