Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations

Autoři: Jann Paul Mattern aff001;  Christopher A. Edwards aff001;  Christopher N. Hill aff002
Působiště autorů: Ocean Sciences Department, UC Santa Cruz, Santa Cruz, CA, United States of America aff001;  Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States of America aff002
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0223131


Dual numbers allow for automatic, exact evaluation of the numerical derivative of high-dimensional 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.

Klíčová slova:

Chlorophyll – Mathematical functions – Oceans – Programming languages – Tangents – Biogeochemistry – Fortran – Ocean modeling


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Článek vyšel v časopise


2019 Číslo 10
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