@article {arango_4d-var_2023,
	title = {4D-Var data assimilation in a nested model of the Mid-Atlantic Bight},
	journal = {Ocean Modelling},
	volume = {184},
	year = {2023},
	pages = {102201},
	abstract = {The Regional Ocean Modeling System (ROMS) 4-dimensional variational (4D-Var) data assimilation platform has been extended to include nested grid configurations using both one-way and two-way nesting strategies. The efficacy of this new ROMS utility is demonstrated in a model comprising three nested grids with horizontal refinement and configured for the Mid-Atlantic Bight. The three nested grids have a horizontal resolution ranging from \~{}7 km to \~{}0.8 km thereby capturing circulation regimes that span the Gulf Stream western boundary current, through the mesoscale eddy field, and down to the rapidly evolving and energetic submesoscale. These circulation regimes represent a challenge for any data assimilation system, and the nested 4D-Var system was found to perform well across the range of resolved space and time scales. The observational data used to constrain the ocean state estimates come from a wide range of remote sensing, in situ, and mobile platforms, along with the U.S. National Science Foundation{\textquoteright}s Ocean Observatories Initiative Pioneer Array. Several aspects of the system performance are explored and described here, including the fit of the model to the observations, the influence of data assimilation on the wave number spectra at the submesoscale, and the downscaling and upscaling of information captured by the observations.},
	keywords = {4D-Var, Data assimilation, Mid-Atlantic Bight, Nested grids, Pioneer Array},
	issn = {1463-5003},
	doi = {10.1016/j.ocemod.2023.102201},
	url = {https://www.sciencedirect.com/science/article/pii/S1463500323000422},
	author = {Arango, Hernan G. and Levin, Julia and Wilkin, John and Moore, Andrew M.}
}
