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Grant Award View - GA141192-V2
Machine learning of subgrid ocean physics for global ocean models
GA ID:
GA141192-V2
Agency:
Australian Research Council
Approval Date:
1-Dec-2020
Variation Publish Date:
14-Oct-2021
Variation Date:
12-Oct-2021
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2021 to 31-Dec-2023
Value (AUD):
$434,030.00
(GST inclusive where applicable)
Varies:
GA141192
- Machine learning of subgrid ocean physics for global ocean models
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 20/21 Discovery
Grant Program:
Discovery Early Career Researcher Award
Grant Activity:
Machine learning of subgrid ocean physics for global ocean models
Purpose:
Climate projections require simulations with ocean-climate models for hundreds of years. Computational resources limit the resolution of our models for such long runs, meaning that some key physical processes remain unresolved and must be parameterised. This project uses machine learning to find new parameterisations for unresolved ocean processes. These new parameterisations will be implemented into computationally cheaper coarse-resolution ocean models, thereby enhancing these models' representation of the ocean circulation. This project expects to reveal the dynamics of unresolved processes, to improve the accuracy of climate projections and to provide a proof-of-concept for how machine learning can be used in ocean and climate science.
GO ID:
GO Title:
Discovery Early Career Researcher Award for funding commencing in 2021
Internal Reference ID:
DE21 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
The Australian National University
Recipient ABN:
52 234 063 906
Grant Recipient Location
Suburb:
ACTON
Town/City:
ACTON
Postcode:
2601
State/Territory:
ACT
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
ACT
Postcode:
2601
Country:
AUSTRALIA