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EPSRC Reference: GR/R92363/01
Title: FARADAY FAST TRACK PROPOSAL: Direct and Inverse Modelling in End-to-End Environmental Estimation (DIME)
Principal Investigator: Smith, Professor LA
Other Investigators:
Roulston, Dr M Hunt of Chesterton, Lord J Penzer, Dr JR
Researcher Co-Investigators:
Project Partners:
A B Electronic Projects Group Risk Management Solutions
Department: Statistics
Organisation: London School of Economics & Pol Sci
Scheme: Faraday (PreFEC)
Starts: 01 March 2003 Ends: 31 August 2005 Value (£): 94,360
EPSRC Research Topic Classifications:
Non-linear Systems Mathematics Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Environment Financial Services
Energy Information Technologies
Related Grants:
Panel History:  
Summary on Grant Application Form
The end-to-end approach aims to track uncertainty, both from model inadequacy and from the unknown initial state of the atmosphere, all the way through the modelling process, to yield estimates of the uncertainty In quantities of industrial interest. We will contrast, and ideally meld, both direct (forward or physical simulation) models and inverse (statistical or empirical) models in a variety of contexts. London Electricity, one of our industrial collaborators, is most interested in the time-scales of days; here we will examine methods for forming hybrid ensembles from ensembles over initial condition, model, and initialisation time. Hybrid ensembles dress the individual trajectories of a Monte Carlo ensemble of trajectories with appropriate historical error statistics, providing a user specific approach to downscaling. More generally, the use of direct and inverse models will be contrasted in downscaling applications associated with wind energy. New inverse models for seasonal models will be constructed and compared with direct seasonal forecasts from the DEMETER project; the comparison will be based on industrial utility in quantifying weather risk. This is of direct industrial interest to Risk Management Solutions, our other industrial collaborator.
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Organisation Website: http://www.lse.ac.uk