Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616485
Title: Comparing variational and ensemble data assimilation methods for numerical weather prediction
Author: Fairbairn, David
ISNI:       0000 0004 5347 5691
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2014
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Abstract:
Data assimilation (DA) methods combine a prior forecast (background state) with the latest observations of the atmosphere, to estimate the initial conditions for a weather forecast. Accurate and early forecasts of extreme weather events allow time for actions to be taken to protect populations from injury and death, and for the preservation of infrastructure as far as possible. Climate change is expected to increase the severity frequency of some extreme weather events over the coming Century. Advances in DA should improve the forecasts of these events.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.616485  DOI: Not available
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