Output details
14 - Civil and Construction Engineering
University of Strathclyde
Analysis error covariance versus posterior covariance in variational data assimilation
This paper presents new 'variational' estimates of the Bayesian posterior covariance, which is important for parameter estimation methodology in general and for large-scale weather and ocean forecasting in particular. The key paper underpinning Gejadze's NERC Advanced Fellowship research proposal (NE/J018201/1) where the research will be applied within the framework of the NEMO ocean model, with the UK Met Office, to improve global predictions of ocean state. This will "give insights into how to construct and make best use of ensembles of model forecasts and, therefore, considerably improve the quality of the forecasts." (Mike Bell, National Centre for Ocean Forecasting, mike.bell@metoffice.gov.uk)
