The aim of SIMPLE is to investigate and parameterise the influence of small-scale spatial variability in plankton concentrations on the behaviour of large-scale mean fields. This is necessary for accurate plankton ecosystem models as biogeochemical subunits of predictive climate models, which must account for the influence of plankton ecosystems on the biosphere, and as tools to predict the large-scale effects of climate change on sensitive marine ecosystems, which support economically-critical resources. SIMPLE will achieve this aim in two stages. First, we use spatially-resolved numerical simulation to investigate the influence of small-scale spatial variability on mean field behaviour (the ‘biological Reynolds fluxes’), and how these fluxes may be parameterised in coarse-resolution models using second moment closure (SMC) methods. Second, we groundtruth the SMC method by fitting coarse-resolution models to in situ and satellite data from the BATS (Bermuda Atlantic Time Series) region and attempting to predict independent data. The objectives are to quantify the ecosystem fluxes due to unresolved biological variability, develop SMC parameterisations of these fluxes, and assess the predictive benefits in a context applicable to large areas of the oceans. SIMPLE will fulfil FP7 directives for collaborative research into the Environment (‘Cooperation’ block) as well as frontier science (‘Ideas’) and training/career development for the applicant (‘People’).
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