Exploring structural sensitivity in a 1-D marine biogeochemical model

[thumbnail of 23864703_Anugerahanti_thesis.pdf]
Preview
Text - Thesis
· Please see our End User Agreement before downloading.
| Preview
[thumbnail of 23864703_Anugerahanti_form.PDF]
Text - Thesis Deposit Form
· Restricted to Repository staff only
Restricted to Repository staff only

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Anugerahanti, P. (2020) Exploring structural sensitivity in a 1-D marine biogeochemical model. PhD thesis, University of Reading. doi: 10.48683/1926.00089371

Abstract/Summary

Equations used to describe the main biological processes determine the dynamics of biogeochemical models. From previous studies, altering the form of these process ‘structure functions’ has been shown to produce larger differences than changing the values of the parameters used in the models. This study explores the effect of this structural sensitivity in a marine biogeochemical model by generating an ensemble of runs. We use a 1-D Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration, and Acidification (MEDUSA) ensemble, where each member has a different combination of key biogeochemical process equations, each of which tuned to be as similar as possible to the default functions. The model is run at five oceanographic stations spanning three different biogeochemical regimes or provinces: oligotrophic, coastal, and abyssal plain. Marine biogeochemical models are also sensitive to the physical environment, so we also explore the relative impact of altering the physical input and biogeochemical process equations, separately and together. The impacts of perturbing the biogeochemistry and physics are quantified using statistical metrics, chlorophyll depth distributions, and phytoplankton bloom phenology. We explored the signature characteristics of the different ensembles by examining the anomaly correlations between different ensemble members and also the nitrogen fraction in phytoplankton across different ensemble members. We found that even small perturbations in model structure can produce a large ensemble spread in many metrics that then mostly easily encompasses the in situ observations. This perturbed biogeochemistry ensemble (PBE) also has an improved RMSE between observations and the ensemble mean, compared to a single deterministic model default run. Perturbing the physics does not generate as large an ensemble range in many of the metrics studied, and cannot always encompass the in situ chlorophyll observations. From exploring the signature characteristics of the different ensembles, very different characteristics are produced from the two ensembles. Perturbing biogeochemistry alters exchange fluxes between biogeochemical compartments, whereas perturbing the physics only alters the nutrient supply to the biological compartments. Therefore, the perturbed biogeochemistry ensemble provides better representations of uncertainty. We discuss how this might be useful for interpreting discrepancies against observational data.

Altmetric Badge

Item Type Thesis (PhD)
URI https://reading-clone.eprints-hosting.org/id/eprint/89371
Identification Number/DOI 10.48683/1926.00089371
Divisions Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Date on Title Page 2019
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar