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Predicting Interannual Variability in Sea Surface Height Along the West Coast of Australia Using a Simple Ocean Model.

Authors :
Nagura, Motoki
McPhaden, Michael J.
Source :
Geophysical Research Letters. 9/28/2021, Vol. 48 Issue 18, p1-9. 9p.
Publication Year :
2021

Abstract

Sea surface height (SSH) along the west coast of Australia is key to local climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. This study provides a method to predict interannual variability in SSH along the west coast of Australia using a simple 1.5‐layer dynamical ocean model forced by a statistical atmospheric model for ENSO‐related winds. The model has realistic coastlines and is driven by reanalysis surface winds regressed onto an ENSO index. The model when run in hindcast mode to predict past variability can simulate tide gauge observations at Fremantle along the west coast of Australia up to 13 months in advance, which outperforms persistence. We conclude that this methodology can be useful as a baseline for gauging the performance of more sophisticated forecast models for predicting SSH variations along the west coast of Australia. Plain Language Summary: Sea surface height (SSH) along the west coast of Australia is key to regional climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. Previous studies predicted interannual variability in SSH in this region using sophisticated ocean‐atmosphere coupled general circulation models, but their ocean models had coarse horizontal resolution, required to reduce computational burden. This study provides a much simpler method to predict SSH variability along the west coast of Australia using a simple ocean dynamical model with realistic coastlines forced by ENSO‐related atmospheric winds. Our model, run in hindcast mode to predict past SSH variability, is able to simulate SSH anomalies along the west coast of Australia up to 13 months in advance. A true forecast system to predict future variations would also require prediction of ENSO. However, this methodology can be useful as a baseline for gauging the performance of more sophisticated model forecast systems. Key Points: Interannual variability in sea level along the west Australian coast can be predicted up to 13 months in advance using a simple ocean modelTo illustrate, the model is run in hindcast mode forced remotely by Pacific surface winds related to El Niño Southern OscillationModel hindcasts generally outperform persistence forecasts in terms of anomaly correlation and root‐mean‐squared differences [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00948276
Volume :
48
Issue :
18
Database :
Academic Search Index
Journal :
Geophysical Research Letters
Publication Type :
Academic Journal
Accession number :
152652585
Full Text :
https://doi.org/10.1029/2021GL094592