Leveraging Uncertainty Quantification to Design Ocean Climate Observing Systems.

View/ Open
Average rating
votes
Date
2021Author
Loose, Nora
Heimbach, Patrick
Metadata
Show full item recordAbstract
Ocean observations are expensive and difficult to collect. Designing effective ocean
observing systems therefore warrants deliberate, quantitative strategies. We leverage adjoint modeling
and Hessian uncertainty quantification (UQ) within the ECCO (Estimating the Circulation and Climate
of the Ocean) framework to explore a new design strategy for ocean climate observing systems. Within
this context, an observing system is optimal if it minimizes uncertainty in a set of investigator-defined
quantities of interest (QoIs), such as oceanic transports or other key climate indices. We show that
Hessian UQ unifies three design concepts. (1) An observing system reduces uncertainty in a target QoI
most effectively when it is sensitive to the same dynamical controls as the QoI. The dynamical controls
are exposed by the Hessian eigenvector patterns of the model-data misfit function. (2) Orthogonality of
the Hessian eigenvectors rigorously accounts for redundancy between distinct.....
Journal
Journal of Advances in Modeling Earth SystemsVolume
13Issue
Article e2020MS002386Page Range
25pp.Document Language
enSustainable Development Goals (SDG)
14.aEssential Ocean Variables (EOV)
N/ADOI Original
https://doi.org/10.1029/2020MS002386Citation
Loose, N. and Heimbach, P. (2021) Leveraging uncertainty quantification to design ocean climate observing systems. Journal of Advances in Modeling Earth Systems, 13: e2020MS00238, 25pp. DOI: https://doi. org/10.1029/2020MS002386Collections
The following license files are associated with this item: