[ Research Interests → Data Assimilation ]
 
 

Data Assimilation:

I develop and apply practical methods for assimilating data into both shelf and deep ocean models. In a study of the seasonal cycle of the North Atlantic Yaremchuk, Nechaev and Thompson (2001) used an adjoint-based assimilation procedure to estimate the seasonal variation of the North Atlantic Current. This study demonstrated the importance of including the seasonal cycle in order to accurately reproduce the mean state of this nonlinear system. More recently I have developed a new scheme for suppressing the common problem of drift and bias in eddy resolving ocean models (Thompson, Wright, Demirov and Lu, 2005). The method has subsequently been used successfully to model eddy variability in both the North Atlantic (Wright, Thompson and Lu, 2005) and North Pacific (Stacey, Shore, Wright and Thompson, 2005). In a study of circulation on the continental shelf we (Lu, Thompson and Wright, 2001) showed the incremental approach, a technique developed originally in meteorology, could be used to infer open boundary conditions for a 3D nonlinear baroclinic model by taking advantage of a 2D linear barotropic model. Recently I have started work on assimilation of Lagrangian data (e.g. Argo data) using particle filters.

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