Data Assimilation Meetings at Reading

Date Meeting type Speakers
11 February 2015
Agric 1L16
Internal speaker Alison Fowler (University of Reading)
Model error in coupled atmosphere-ocean data assimilation (pdf)
The initialisation of coupled atmosphere-ocean models for long-term forecasting is currently an area of active research. In order to provide accurate initial conditions in which the atmosphere and ocean are consistent with one another it is necessary to take into account the coupling within the assimilation algorithm. Various approaches have been proposed based on incremental 4D-Var with varying degrees of coupling; ranging from 'strongly coupled' 4D-Var to 'uncoupled' 4D-Var which is only coupled in the sense that the background is generated from a coupled model. In other work we have shown that the benefits of a strongly coupled DA system include the reduced chance of an initialisation shock caused by an analysis in which the atmosphere and ocean are out of balance and the improved use of near surface observations. An outstanding issue is choosing a window length which is optimal for both the atmosphere and ocean. Ideally a long window length would be used to allow for sufficient information from observations in the ocean to constrain the initial conditions, however the presence of model error in the atmosphere prohibits this. Within this work we look at how model error in the atmosphere and ocean models affect the different coupling strategies. In particular we show that although uncoupled DA can help to reduce the impact of model error in long-window 4D-Var by preventing the model error in one system interacting with the other it is still unable to provide a balanced atmosphere-ocean initial state. The implications these results have for the development of long-window weak constraint coupled 4D-Var will then be discussed.

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