The University of Southampton
University of Southampton Institutional Repository

Assimilating satellite ocean-colour observations into oceanic ecosystem models

Assimilating satellite ocean-colour observations into oceanic ecosystem models
Assimilating satellite ocean-colour observations into oceanic ecosystem models
The effectiveness of ocean-colour data assimilation in providing robust biological-parameter estimates for basin-scale ecosystem models is investigated for a phytoplankton-zooplankton-nutrient model using North Atlantic satellite chlorophyll data. The model is forced by annual cycles of mixed-layer depth, day length, photosynthetically available radiation and a temperature-dependent phytoplankton maximum growth rate.
Although ocean-colour data are potentially limited in their ability to constrain model parameters because they provide information about the phytoplankton component only, this limitation is offset by the volume of data available covering the range of possible biogeochemical responses to similar and widely varying physical conditions. The results are improved by applying wintertime nutrient estimates based on in situ observations as an additional constraint.
Repeatability of parameter estimates obtained from independent samples is examined. Results obtained using regional and basin-wide sampling strategies for obtaining the optimization dataset are compared and the geographic applicability of the calibrated models is assessed.
PARAMETER ESTIMATION, BIOGEOCHEMISTRY, MARINE PLANKTON
1364-503X
33-39
Hemmings, J.C.P.
ebf33f54-d2b2-4ab3-9ac8-fd9dc9ae6a7f
Srokosz, M.A.
1e0442ce-679f-43f2-8fe4-9a0f0174d483
Challenor, P.
a7e71e56-8391-442c-b140-6e4b90c33547
Fasham, M.J.R.
7fb86485-8cfc-4199-bde4-2276abefdf2e
Hemmings, J.C.P.
ebf33f54-d2b2-4ab3-9ac8-fd9dc9ae6a7f
Srokosz, M.A.
1e0442ce-679f-43f2-8fe4-9a0f0174d483
Challenor, P.
a7e71e56-8391-442c-b140-6e4b90c33547
Fasham, M.J.R.
7fb86485-8cfc-4199-bde4-2276abefdf2e

Hemmings, J.C.P., Srokosz, M.A., Challenor, P. and Fasham, M.J.R. (2003) Assimilating satellite ocean-colour observations into oceanic ecosystem models. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 361 (1802), 33-39. (doi:10.1098/rsta.2002.1104).

Record type: Article

Abstract

The effectiveness of ocean-colour data assimilation in providing robust biological-parameter estimates for basin-scale ecosystem models is investigated for a phytoplankton-zooplankton-nutrient model using North Atlantic satellite chlorophyll data. The model is forced by annual cycles of mixed-layer depth, day length, photosynthetically available radiation and a temperature-dependent phytoplankton maximum growth rate.
Although ocean-colour data are potentially limited in their ability to constrain model parameters because they provide information about the phytoplankton component only, this limitation is offset by the volume of data available covering the range of possible biogeochemical responses to similar and widely varying physical conditions. The results are improved by applying wintertime nutrient estimates based on in situ observations as an additional constraint.
Repeatability of parameter estimates obtained from independent samples is examined. Results obtained using regional and basin-wide sampling strategies for obtaining the optimization dataset are compared and the geographic applicability of the calibrated models is assessed.

This record has no associated files available for download.

More information

Published date: 2003
Keywords: PARAMETER ESTIMATION, BIOGEOCHEMISTRY, MARINE PLANKTON
Organisations: National Oceanography Centre,Southampton

Identifiers

Local EPrints ID: 1968
URI: http://eprints.soton.ac.uk/id/eprint/1968
ISSN: 1364-503X
PURE UUID: 3ed6d1ee-dd22-4745-8077-65597b5b2694

Catalogue record

Date deposited: 06 May 2004
Last modified: 15 Mar 2024 04:43

Export record

Altmetrics

Contributors

Author: J.C.P. Hemmings
Author: M.A. Srokosz
Author: P. Challenor
Author: M.J.R. Fasham

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×