Browsing by Author "Vichi, M"

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    Drivers and uncertainties of future global marine primary production in marine ecosystem models
    (2015) Laufkötter, C; Vogt, M; Gruber, N; Aita-Noguchi, M; Aumont, O; Bopp, L; Buitenhuis, E; Doney, S C; Dunne, J; Hashioka, T; Hauck, J; Hirata, T; John, J; Le Quéré, C; Lima, D I; Nakano, H; Seferian, R; Totterdell, I; Vichi, M; Völker, C
    Past model studies have projected a global decrease in marine net primary production (NPP) over the 21st century, but these studies focused on the multi-model mean and mostly ignored the large inter-model differences. Here, we analyze model simulated changes of NPP for the 21st century under IPCC's high emission scenario RCP8.5 using a suite of nine coupled carbon–climate Earth System Models with embedded marine ecosystem models with a focus on the spread between the different models and the underlying reasons. Globally, five out of the nine models show a decrease in NPP over the course of the 21st century, while three show no significant trend and one even simulates an increase. The largest model spread occurs in the low latitudes (between 30° S and 30° N), with individual models simulating relative changes between −25 and +40%. In this region, the inter-quartile range of the differences between the 2012–2031 average and the 2081–2100 average is up to 3 mol C m-2 yr-1. These large differences in future change mirror large differences in present day NPP. Of the seven models diagnosing a net decrease in NPP in the low latitudes, only three simulate this to be a consequence of the classical interpretation, i.e., a stronger nutrient limitation due to increased stratification and reduced upwelling. In the other four, warming-induced increases in phytoplankton growth outbalance the stronger nutrient limitation. However, temperature-driven increases in grazing and other loss processes cause a net decrease in phytoplankton biomass and reduces NPP despite higher growth rates. One model projects a strong increase in NPP in the low latitudes, caused by an intensification of the microbial loop, while the remaining model simulates changes of less than 0.5%. While there is more consistency in the modeled increase in NPP in the Southern Ocean, the regional inter-model range is also very substantial. In most models, this increase in NPP is driven by temperature, but is also modulated by changes in light, macronutrients and iron as well as grazing. Overall, current projections of future changes in global marine NPP are subject to large uncertainties and necessitate a dedicated and sustained effort to improve the models and the concepts and data that guide their development.
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    Quantifying the SST biases in data assimilative ocean simulations of the Benguela Upwelling System
    (2018) Luyt, Hermann; Backeberg, B C; Veitch, J; Vichi, M
    The Benguela Upwelling System (BUS) on the west coast of southern Africa is one of the global ocean’s most productive upwelling systems supporting a large fishing industry, a fledgling aquaculture sector and offshore mining interests. Despite intensive monitoring and modelling studies, there is no regionally tailored ocean forecasting system that is explicitly developed to deal with the unique ocean dynamics of the Benguela. In this study, the Hybrid Coordinate Ocean Model (HYCOM) is used in conjunction with the Ensemble Optimal Interpolation (EnOI) assimilation scheme to study the impact of assimilating sea surface temperature (SST) and along-track sea level anomalies (SLA) observations on predicted upwelling dynamics in the Benguela. In order to evaluate the predictive skill and impact of data assimilation, three experiments with HYCOMEnOI are evaluated: (1) with no assimilation (HYCOMFREE), (2) only assimilating along-track SLA (HYCOMSLA) and (3) assimilating both SLA and SST (HYCOMSLA+SST). Using MODIS Terra SST as reference, the model SST outputs are evaluated. HYCOMFREE is found to exhibit a warm bias along the coast, HYCOMSLA shows an even greater warm bias while HYCOMSLA+SST conversely shows a much improved SST forecast skill. It is hypothesised that the warm biases could be due to errors in boundary conditions and/or the ERA-interim wind product used to force the model. Furthermore, a comparison of the assimilated SST product (the Operational Sea Surface Temperature and Sea Ice Analysis; OSTIA) with MODIS SST reveals biases in OSTIA up to ±1 ◦C, raising questions over its suitability for assimilation in upwelling regions. Studying the effect of assimilation on SSH, SST and surface currents before and after the assimilation suggests that an increase in SSH from assimilated SLA leads to increased warm SST biases in HYCOMSLA. This is due to an incorrect relationship between SSH and SST in the free-running HYCOM, from which the static ensemble is derived for the EnOI. HYCOMSLA+SST exhibits slightly enhanced SSH increments but the associated increase in SST is significantly reduced by the assimilated SST, resulting in a reduction of the bias with very little impact on the current dynamics. This is reflected in the surface velocitiy increments, which are similar to or worse than that of HYCOMSLA. Investigating the potential of HYCOM-EnOI as an operational forecasting system has revealed that the assimilation of SST and along-track SLA vastly improves modelled SST for the BUS upwelling. Errors in the free-running model, which constitutes the static ensemble, need addressing and comparisons between MODIS and OSTIA SSTs suggests that OSTIA may not be ideally suited for assimilation in the case of coastal upwelling, due to limitations in capturing the dynamics correctly.