Details of Grant 

EPSRC Reference:	EP/I00405X/1
Title:	Advanced new methods for multi-scale free surface regional ocean modelling with adjoint data assimilation
Principal Investigator:	Pain, Professor CC
Other Investigators:	Gorman, Dr G Piggott, Professor MD Allison, Professor PA
Researcher Co-Investigators:
Project Partners:	Fujitsu H R Wallingford Ltd Istituto per l'ambiente marino costiero Proudman Oceanographic Laboratory Sea Zone Solution Ltd. University of Strathclyde University of Tokyo
Department:	Earth Science and Engineering
Organisation:	Imperial College London
Scheme:	Standard Research
Starts:	01 October 2010	Ends:	30 September 2013	Value (£):	789,662
EPSRC Research Topic Classifications:	Coastal & Waterway Engineering
EPSRC Industrial Sector Classifications:	Water
Related Grants:
Panel History:	Panel Date Panel Name Outcome 22 Apr 2010 Process Environment & Sustainability Panel Announced
Summary on Grant Application Form
The combined effect of population growth and industrialisation in the UK is such that coastal land areas are increasingly occupied by multiple user groups with diverse and competing needs (e.g. environmental, tourism, industrial). An important aspect of climate change is the increased likelihood of storms, and hence storm-surges and flooding, and this will have obvious impact upon low lying areas. There is thus an increased need to improve our capacity to predicti (especially over a wide range of spatial scales - a few meters to many kilometres) flooding. Improved modelling ability will inform policy makers, rescue services and scientists involved with ocean, climate change and risk reduction strategies. Data assimilation techniques are extremely valuable in compensating for lack of information about our oceans. Observed data is assimilated into models to produce an accurate estimate (in some optimal sense) of the state of the ocean. However, applications of efficient data assimilation approaches (e.g., variational data assimilation) are hampered by two major difficulties: the often complex code (implementation and maintainability) required; and the high computational costs. To address these issues, the proposed work will improve the existing models by using: 1) a newly developed data assimilation formulation to dramatically reduce the code complexity and increase maintainability; 2) a new highly stable and accurate wetting and drying method capable of resolving multi-scale physics and uniquely designed for use with a next generation ocean model; 3) model reduction in which large-scale models are reduced down to a few hundred unknowns so that the resulting models are orders of magnitude faster than the original model. Our overall aim is the accurate prediction of free surface dominated flows in coastal regions. Prediction will be achieved by developing a variational data assimilation (in the content of the time dependent problems solved here) framework within our advanced adaptive mesh ocean model. This framework will be capable of quantifying the effect of model uncertainties, performing sensitivity analysis, and capturing abruptly changing fields such as wetting and drying fronts in free surface dominated regional flows. This will pave the way towards an open source, community, next generation regional ocean model with multi-scale adaptive finite element meshing features and predictive capability. The overall deliverable will be a model capable of resolving free surface dominated flows from ocean to estuary (and smaller scale) scale. The proposed combination of recently developed techniques is the only feasible way of resolving these demanding multi-scale flows. The proposed research is also expected to have a substantial impact on the future development of operational implementation of variational data assimilation in both meteorology and oceanography. The reduction in computational effort and memory requirements will render data assimilation a more affordable research and operational tool. Society as a whole will benefit from this research through improved prediction of multi-scale coastal flows, especially the prediction of storm flooding. In particular, government, regulatory bodies and stakeholder, companies/industries, meteorology, oceanography communities and institutes would benefit from the new technologies that could be used for prediction and impact assessment of natural disasters, pollution and rapid emergency response.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Project URL:	http://www3.imperial.ac.uk/earthscienceandengineering/research/amcg
Further Information:
Organisation Website:	http://www.imperial.ac.uk