Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability

Toms, Benjamin A.; Barnes, Elizabeth A.; Ebert‐Uphoff, Imme

doi:10.1029/2019ms002002

i

Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability

Supporting Files

2020
By Toms, Benjamin A. ; Barnes, Elizabeth A. ; Ebert‐Uphoff, Imme

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Journal Title:

Journal of Advances in Modeling Earth Systems
Personal Author:

Toms, Benjamin A. ; Barnes, Elizabeth A. ; Ebert‐Uphoff, Imme
NOAA Program & Office:

CIRA (Cooperative Institute for Research in the Atmosphere)
Keywords:

Environmental Chemistry General Earth And Planetary Sciences Global And Planetary Change General Earth And Planetary Sciences Global And Planetary Change General Earth And Planetary Sciences Global And Planetary Change
Source:

Journal of Advances in Modeling Earth Systems, 12(9)
DOI:

https://doi.org/10.1029/2019ms002002
ISSN:

1942-2466 ; 1942-2466
Format:

PDF
Publisher:

American Geophysical Union (AGU)
Document Type:

Journal Article
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
Main Document Checksum:

urn:sha256:c6ec1e25b3b07a789e450c819b1147f34db7cfee33e383618a2963b5030d33e6
Download URL:

https://repository.library.noaa.gov/view/noaa/54887/noaa_54887_DS1.pdf
File Type:

[PDF - 9.18 MB ]

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