Nesting and data assimilation considerations in regional operational ocean forecasting

A combination of nesting and data assimilation setups is explored for lowering analysis and forecast errors in a regional operational ocean model. Original downscaling from the global model and applying 3dVar to a regional model produce unacceptably high errors. The latter are reduced by the introduction of an intermediate assimilative nest with 3dVar and 4dVar assimilations, and by the use of 4dVar assimilation in the regional model. It is found that if only 3dVar assimilation is available, then the intermediate assimilative nest is necessary for lowering errors in the regional model. Alternatively, 4dVar assimilation can be used directly in the regional model or in the intermediate nest. Errors in the regional 3dVar nested in the intermediate 4dVar assimilative nest are comparable to regional 4dVar. Although the latter has lowest errors, there is value in the former, because the intermediate nest could encompass several regional models.