The Measurement Error Proxy System Model: MEPSM v0.2

Fischer, Matt J.

doi:https://doi.org/10.5194/gmd-17-6745-2024

Articles | Volume 17, issue 17

https://doi.org/10.5194/gmd-17-6745-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-17-6745-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 17

Model description paper

|

12 Sep 2024

Model description paper |

| 12 Sep 2024

The Measurement Error Proxy System Model: MEPSM v0.2

Matt J. Fischer

Supplement

https://doi.org/10.5194/gmd-17-6745-2024-supplement

Data sets

NOAA Extended Reconstructed Sea Surface Temperature (ERSST), Version 5 Boyin Huang et al. https://doi.org/10.7289/V5T72FNM

HadEN4 salinity and salinity error standard deviation data V. Gouretski and F. Reseghetti https://apdrc.soest.hawaii.edu/las/v6/dataset?catitem=16652

Model code and software

Mattriks/MeasurementErrorModels.jl: MEPSM v0.2.0 Matt Fischer https://doi.org/10.5281/zenodo.7793741

Data assimilation notebook and code module Matt Fischer https://doi.org/10.5281/zenodo.12660485

Short summary

In paleoclimate research, proxy system models (PSMs) model chemical or biological systems which receive environmental input and output (e.g., geochemical signals). The environmental inputs are rarely noiseless, which causes problems when calibrating multi-input PSMs. Here a PSM is developed which includes generalized noise in both model inputs and outputs and prior information. A quasi-Bayesian method enhances the stability of the solution of the Measurement Error Proxy System Model.