Exploring Coupled 4D-Var Data Assimilation using an Idealised Atmosphere-Ocean Model
Smith, Polly; Fowler, Alison; Lawless, Amos
University of Reading, UNITED KINGDOM
Data assimilation techniques are now widely used in operational numerical weather prediction and ocean forecasting systems; their success has led to an increased interest in their use for the initialisation of coupled atmosphere-ocean models in seasonal to decadal timescale prediction. Coupled data assimilation presents a significant challenge but offers a long list of potential benefits including the improved use of near-surface observations, reduction of initialisation shocks in the forecasts, and generation of a consistent system state for the initialisation of coupled forecasts across all timescales.
A key driver behind our work is the development of the new Coupled ECMWF Re-analysis system (CERA), a prototype weakly coupled data assimilation system. Here, we will describe the development of an idealised single-column coupled atmosphere-ocean 4D-Var assimilation system designed to explore various approaches to performing coupled model data assimilation. The model is based on the ECMWF Integrated Forecast System (IFS) atmosphere model and a K-Profile Parameterisation (KKP) mixed layer ocean model developed by the NCAS climate group at the University of Reading and employs a strong constraint incremental 4D-var scheme. The work within this simple 1D framework will facilitate a greater theoretical understanding of the coupled atmosphere-ocean data assimilation problem and thus help inform the design and implementation of the different coupling strategies proposed for the CERA system.
We will present preliminary results from identical twin experiments devised to investigate and compare the behaviour and sensitivities of different assimilation methodologies for use in coupled atmosphere-ocean data assimilation.
This is research being carried out as part of the ESA Data Assimilation Projects - Coupled Model Data Assimilation initiative which aims to advance data assimilation techniques in fully coupled atmosphere-ocean models.