Machine learning emulation of gravity wave drag in numerical weather forecasting
Machine learning emulation of gravity wave drag in numerical weather forecasting
About this item
Full title
Author / Creator
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
Formats
Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
Subjects
More information
Scope and Contents
Contents
We assess the value of machine learning as an accelerator for the parameterisation schemes of operational weather forecasting systems, specifically the parameterisation of non-orographic gravity wave drag. Emulators of this scheme can be trained to produce stable and accurate results up to seasonal forecasting timescales. Generally, more complex ne...
Alternative Titles
Full title
Machine learning emulation of gravity wave drag in numerical weather forecasting
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2479575183
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2479575183
Other Identifiers
E-ISSN
2331-8422
DOI
10.48550/arxiv.2101.08195
