To protect marine ecosystems threatened by climate change and anthropic stressors, it is essential to operationally monitor ocean health indicators. These are metrics synthetizing multiple marine processes relevant to the users of operational services. Here we assess if selected ocean indicators simulated by operational models can be controlled (here meaning constrained effectively) by biogeochemical observations, by using a newly proposed methodological framework. The method consists in firstly screening the sensitivities of the indicators with respect to the initial conditions of the observable variables. These initial conditions are perturbed stochastically in Monte Carlo simulations of one-dimensional configurations of a multi-model ensemble. Then, the models are applied in three-dimensional ensemble assimilation experiments, where the reduction of the ensemble variance corroborates the controllability of the indicators by the observations. The method is applied for ten relevant ecosystem indicators (ranging from inorganic chemicals to plankton production), seven observation types (representing data from satellite and underwater platforms), and an ensemble of five biogeochemical models of different complexity, employed operationally by the European Copernicus Marine Service. We demonstrate that all the indicators are controlled by one or more types of observations. In particular, the indicators of phytoplankton phenology are controlled and improved by the merged observations from the surface ocean colour and chlorophyll profiles. Similar observations also control and reduce the uncertainty of the plankton community structure and production. However, the uncertainty of the trophic efficiency and POC increases when assimilating chlorophyll-a data, though observations were not available to assess whether that was due to a worsen model skill. We recommend that the assessment of controllability proposed here becomes a standard practice in designing operational monitoring, reanalysis and forecast systems, to ultimately provide the users of operational services with more precise estimates of ocean ecosystem indicators.
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RBINS Staff Publications 2023
The Taiwan Strait (TS), situated between Taiwan and China, is shallow, relatively turbid, and characterized by strong tidal currents and winter and summer monsoon seasons. The aim of this study was to use images from the Moderate Resolution Imaging Spectroradiometer (MODIS)on board the Aqua satellite to investigate how local sediment sources in addition to the seasonality in wind, oceanographic currents, and waves influence the suspended particulate matter (SPM) dynamics in the TS. In winter, northeast (NE) winds drive the China Coastal Current southward. Cold water with a high SPM concentration is transported southward into the Strait. After the highest SPM concentration reaches its peak in December and January, the winds weaken and the SPM concentration decreases. During summer, winds are less strong and SPM concentration is lower. Although typhoons typically occur in summer, they generate only a weak signal in the surface SPM concentration data from MODIS because of the low number of cloud-free images during these periods. Typhoons result in a short-term increase in the SPM concentration but do not strongly influence the seasonal values in the satellite-derived SPM concentration maps.
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RBINS Staff Publications 2016
