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 article proposes a methodology for assessing the development of damage in building structures, subjected to differential settlement and uplift, using the analysis of Interferometry Synthetic Aperture Radar (InSAR) data. The proposed methodology is targeted towards general applicability, capable of providing assessment results for measurements over wide geographic areas and for varying structural typologies. The methodology is not limited to ground movement measurements linked to tunnelling, as is the common case. Instead it extends to the monitoring of arbitrary movement in buildings, for example, due to ground consolidation, water table changes or excavation. The methodology is designed for use alongside patrimonial building databases, from which data on individual building geometry and typology are extracted on a region or country scale. Ground movement monitoring data are used for the calculation of the building deformation, expressed in different types of deformation parameters. The combined use of this data with analytical models for settlement damage classification in building structures enables the assessment in patrimonial building structures, at a country scale. The methodology is elaborated and applied on the patrimonial inventory of Belgium for the evaluation of potential settlement and uplift damage on buildings over a period of nearly three decades. The analysis results are compared to on-site observations.
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RBINS Staff Publications 2020
