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Thesis

Stochastic parametrisation and model uncertainty

Abstract:

Representing model uncertainty in atmospheric simulators is essential for the production of reliable probabilistic forecasts, and stochastic parametrisation schemes have been proposed for this purpose. Such schemes have been shown to improve the skill of ensemble forecasts, resulting in a growing use of stochastic parametrisation schemes in numerical weather prediction. However, little research has explicitly tested the ability of stochastic parametrisations to represent model uncertainty,...

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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atmos Ocean & Planet Physics
Oxford college:
Jesus College
Role:
Author

Contributors

Division:
MPLS
Department:
Physics
Sub department:
Atmos Ocean & Planet Physics
Role:
Supervisor
Division:
MPLS
Department:
Physics
Sub department:
Atmos Ocean & Planet Physics
Role:
Supervisor
Publication date:
2013
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
Language:
English
Keywords:
Subjects:
UUID:
uuid:6af40a12-d0fa-44b2-9c18-99e0526062c5
Local pid:
ora:9518
Deposit date:
2014-12-04

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