Parameter optimisation of a marine ecosystem model at two contrasting stations in the Sub-Antarctic Zone
Kidston, M and Matear, R and Baird, ME, Parameter optimisation of a marine ecosystem model at two contrasting stations in the Sub-Antarctic Zone, Deep-Sea Research. Part 2: Topical Studies in Oceanography, 58, (21-22) pp. 2301-2315. ISSN 0967-0645 (2011) [Refereed Article]
Crown Copyright 2011 Published by Elsevier Ltd. All rights reserved.
SeaWiFS surface chlorophyll estimates in the Sub-Antarctic Zone show low concentrations south west of Tasmania and high concentrations south east of Tasmania. Data assimilation experiments were performed using simulated annealing to obtain parameter estimates of a simple nitrogen based mixed-layer marine ecosystem model at two locations in this region (station P1 at 140°E, 46.5°S and station P3 at 152°E, 45.5°S). The assimilation methods and parameter sensitivities are assessed in a twin experiment. This assessment determined that inversion method was successful at estimating the correct parameters but that only a sub-set of the model parameters can be uniquely determined using chlorophyll a observations. An analysis of parameter uncertainties shows at both stations accurate parameterisations of phytoplankton growth and zooplankton mortality, and the biological recycling processes are required to realistically model chlorophyll.Applying the inversion method to the climatological SeaWiFS chlorophyll a observations from the two sites we estimate model parameters at these two sites. The most significant differences in parameters between the two stations are the parameters relating to phytoplankton growth and zooplankton mortality. The difference in growth parameters results in spring time productivity estimates of 659mgCm-2d-1 at P1 and 203mgCm-2d-1 at P3. In situ estimates from the SAZ-Sense cruise do not support such dramatic differences in primary production between the two stations. We conclude that the same ecosystem model structure is not applicable at both stations and we need additional processes at P3 to reproduce the observed seasonality of phytoplankton and the observed primary productivity. We hypothesise that the missing processes in the ecosystem model at P3 are iron limitation of phytoplankton and the seasonal variations in atmospheric deposition of iron.
data assimilation, ecosystem modelling, iron, phytoplankton, phytoplankton dynamics