|33rd International Liège Colloquium on Ocean Dynamics: The use of data assimilation in coupled hydrodynamic, ecological and bio-geo-chemical models of the ocean|
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Period: 2001-05-07 - 2001-05-11
Location: Liège, Belgium
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- Université de Liège; GeoHydrodynamics and Environmental Research group (GHER), more, organiser
The capacity of dynamical models to simulate interdisciplinary ocean processes over specific space-time windows and thus forecast their evolution over predictable time scales is conditioned upon the availability of relevant observations to: initialise and continually update the physical and bio-geo-chemical sectors of the ocean state; provide relevant atmospheric and boundary forcing; calibrate the parameterisations of sub-grid scale processes, growth rates and reaction rates; construct interdisciplinary and multiscale correlation and feature models; identify and estimate the main sources of errors in the models; control or correct for mis-represented or neglected processes.
The access to multivariate data sets requires the implementation, exploitation and management of dedicated ocean observing and prediction systems. However, the available data are often limited and, for instance, seldom in a form to be directly compatible or directly inserted into the numerical models. To relate the data to the ocean state on all scales and regions that matter, evolving three-dimensional and multivariate ( measurement ) models are becoming important. Equally significant is the reduction of observational requirements by design of sampling strategies via Observation System Simulation Experiments and adaptive sampling.
The theoretical framework of data assimilation for marine sciences is now relatively well established, routed in control theory, estimation theory or inverse techniques, from variational to sequential approaches. Ongoing research efforts of special importance for interdisciplinary applications include the: stochastic representation of processes and determination of model and data errors; treatment of (open) boundary conditions and strong nonlinearities; space-time, multivariate extrapolation of limited and noisy data and determination of measurement models; demonstration that bio-geo-chemical models are valid enough and of adequate structures for their deficiencies to be controlled by data assimilation; and finally, ability to provide accurate estimates of fields, parameters, variabilities and errors, with large and complex dynamical models and data sets.
Operationally, major engineering and computational challenges for the coming years include the: development of theoretically sound methods into useful, practical and reliable techniques at affordable costs; implementation of scalable, seamless and automated systems linking observing systems, numerical models and assimilation schemes; adequate mix of integrated and distributed (Web-based) networks; construction of user-friendly architectures and establishment of standards for the description of data and software (metadata) for efficient communication, dissemination and management.
In addition to addressing the above items, the 33rd Liege Colloquium will offer the opportunity to :
- review the status and current progress of data assimilation methodologies utilised in the physical, acoustical, optical and bio-geo-chemical scientific communities;
- demonstrate the potentials of data assimilation systems developed for coupled physical/ecosystem models, from scientific to management inquiries;
- examine the impact of data assimilation and inverse modelling in improving model parameterisations;
- discuss the observability and controllability properties of, and identify the missing gaps in current observing and prediction systems;
- and, exchange the results of and the learnings from pre-operational marine exercises.