Impact of coherent ocean stratification on AMOC reconstruction by coupled data assimilation with a biased model

However, models always have systematic errors called bias owing to imperfect numerical representation of the real world. Model bias and the sparse nature of ocean observations, particularly in deep oceans, make it difficult to generate a complete historical picture of AMOC structure and variability.

Here, two coupled models that are biased with respect to each other are used to design "twin'' experiments to systematically study the influence of model bias on AMOC reconstruction. One model is used to produce the "observations'' that sample the "true'' solution of the AMOC to be reconstructed, while the other model is used to incorporate the "observations'' to reconstruct the "truth'' through coupled data assimilation (CDA).