Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations
Name
journal.pone.0223131.pdf
Description
Published version
Size
1.06 MB
Format
Unknown
Checksum (MD5)
c9d3f53fd94eafd1057c32e5d4a59c98
Author(s)
Mattern, Jann Paul
Edwards, Christopher A.
Hill, Christopher N.
Date Issued
October 2019
Journal
PLoS ONE
Publisher
Public Library of Science (PLoS)
Version
Final published version
Abstract
© 2019 Mattern et al. Dual numbers allow for automatic, exact evaluation of the numerical derivative of highdimensional functions at an arbitrary point with minimal coding effort. We use dual numbers to construct tangent linear and adjoint model code for a biogeochemical ocean model and apply it to a variational (4D-Var) data assimilation system when coupled to a realistic physical ocean circulation model with existing data assimilation capabilities. The resulting data assimilation system takes modestly longer to run than its hand-coded equivalent but is considerably easier to implement and updates automatically when modifications are made to the biogeochemical model, thus making its maintenance with code changes trivial.
MIT Department
Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1371/JOURNAL.PONE.0223131
