Tools
Tools
Skákala, J, Ford, D, Fowler, A, Lea, D, Martin, M and Ciavatta, S 2024 How uncertain and observable are marine ecosystem indicators in shelf seas?. Progress in Oceanography, 224. 103249. https://doi.org/10.1016/j.pocean.2024.103249
|
Text
1-s2.0-S0079661124000557-main.pdf - Published Version Available under License Creative Commons Attribution. Download (5MB) | Preview |
Abstract/Summary
Operational analysis and forecast products of shelf sea biogeochemistry often lack reliable information on uncertainty. This is problematic, as good quality uncertainty information is both requested by the product end�users and essential for data assimilation. To address this problem we developed a quality-assessed ensemble representation of many leading sources of uncertainty in a coupled marine physical-biogeochemical model of the North-West European Shelf. Based on these ensembles we have estimated the uncertainty of several marine ecosystem health indicators (MEHIs), acting as proxies for biological productivity, phytoplankton community structure, trophic fluxes, deoxygenation, acidification and carbon export. We have also evaluated how observable these MEHIs are from the most widely available observations of total chlorophyll (mostly from the surface), highlighting those MEHIs and locations that need to be better monitored. Our results show that the most uncertain and the least observable MEHI is the phytoplankton community composition, highlighting the value of its observations (and their assimilation) particularly in the UK regional waters. We demonstrate that daily operational estimates of the other MEHIs, produced by the Met Office, are fairly well constrained. We also quantify how much MEHI uncertainties are reduced when one substantially coarsens the MEHI spatial and temporal resolution, as in the global and/or climate applications.
| Item Type: | Publication - Article |
|---|---|
| Additional Keywords: | Marine ecosystem health indicators Shelf seas Uncertainty quantification Model observability Ensemble-variational data assimilation |
| Divisions: | Plymouth Marine Laboratory > National Capability categories > National Capability Modelling |
| Depositing User: | S Hawkins |
| Date made live: | 23 Apr 2024 09:11 |
| Last Modified: | 23 Apr 2024 09:45 |
| URI: | https://plymsea.ac.uk/id/eprint/10185 |
Actions (login required)
 |
View Item |