A Machine Learning Approach to Rapidly Downscale Sea Surface Temperature Extremes and Heat Stress on the Great Barrier Reef

A Machine Learning Approach to Rapidly Downscale Sea Surface Temperature Extremes and Heat Stress on the Great Barrier Reef

Abstract Reef‐scale climate projections, such as those generated by CMIP6, are critical for guiding the development of effective intervention strategies for mass coral bleaching events. We developed a machine learning (ML) model based on a super resolution deconvolutional neural network to rapidly d...

Full description

Saved in:
Bibliographic Details
Main Authors: Ajitha Cyriac, Chaojiao Sun, John Taylor, Richard Matear, Scott A. Condie, P. Jyoteeshkumar Reddy, Tongliang Liu
Format: Article
Language:English
Published: Wiley 2025-04-01
Series:Geophysical Research Letters
Subjects:
machine learning
downscaling
sea surface temperature
degree heating weeks
great barrier reef
Online Access:https://doi.org/10.1029/2024GL114521
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1029/2024GL114521

Similar Items