Abstract. The dynamics of biogeochemical models are determined by the mathematical structure used for the main biological processes. Earlier studies have shown that small changes in the model formulation may lead to major changes in system dynamics, a property known as structural sensitivity. We assessed the impact of structural sensitivity in an intermediately complex biogeochemical model (MEDUSA) by modelling the chlorophyll and nitrogen concentrations at five different oceanographic stations spanning three different regimes: oligotrophic, coastal, and the abyssal plain over a 10-year timescale. A 1-D MEDUSA ensemble was used with each ensemble member having a combination of tuned function parameterizations that describe the key biogeochemical processes, namely nutrient uptake, zooplankton grazing, and plankton mortalities. The impact is quantified using phytoplankton phenology (initiation, bloom time, peak height, duration, and termination of phytoplankton blooms) and other statistical measures. The spread of the ensemble as a measure of uncertainty is assessed against observations using the Normalised RMSE Ratio (NRR). We found that even small perturbations in model structure can produce large ensemble spreads. The range of 10-year mean surface chlorophyll concentrations are between 0.14–3.69 mg m−3 at coastal stations, 0.43–1.11 mg m−3 on the abyssal plain, and 0.004–0.16 mg m−3 at the oligotrophic stations. Changing mortality and grazing functions have the largest impact on chlorophyll concentrations. The in situ measurements of bloom timings, duration, and terminations lie mostly within the ensemble range and using the ensemble properties such as the mean and median, the errors are mostly reduced compared to the default model output. The NRRs for monthly variability suggest the ensemble spread is generally narrow (NRR 1.21–1.39 for nitrogen and 1.19–1.39 for chlorophyll profiles, 1.07–1.40 for surface chlorophyll, and 1.01–1.40 for depth-integrated chlorophyll). Among the five stations, the most reliable ensemble are obtained for the oligotrophic station at ALOHA (for the surface and integrated chlorophyll 10-year time series and bloom peak height), coastal station L4 (for inter-annual mean), and abyssal plain station PAP (for bloom peak height). Overall our studies provided a novel way to generate ensemble spread by perturbing the model structure/parameterizations, and reliable ensemble means and spreads may be generated.
Application of aerodynamic model structure determination to UAV data