@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.}
}
@article {RN242,
	title = {The impact of remote sensing observations on cross-shelf transport estimates from 4D-Var analyses of the Mid-Atlantic Bight},
	journal = {Advances in Space Research},
	volume = {68},
	number = {2},
	year = {2021},
	pages = {553-570},
	type = {Journal Article},
	abstract = {This paper explores the impact of the individual components of a coastal ocean observing system on estimates of the circulation derived from a state-of-the-art analysis and forecast system for the Mid-Atlantic Bight and Gulf of Maine. The foundation of these activities is the Regional Ocean Modeling System 4-dimensional variational (4D-Var) data assimilation platform, which is run in support of the Mid-Atlantic Regional Association Coastal Ocean Observing System as part of the U.S. Integrated Ocean Observing System. The specific focus of this study is on the impact of remote sensing observations from both space- and land-based platforms on estimates of cross-shelf transport in the vicinity of the National Science Foundation Ocean Observatories Initiative Pioneer array. Sea surface temperature (SST) and sea surface height (SSH) were found to have, on average, a similar impact on the transport estimates. However, during a typical 3-day 4D-Var assimilation cycle, approximately two orders of magnitude more observations of SST than SSH are used in the model, and closer analysis shows that each altimeter measurement has approximately 50 times more impact on the transport estimates than an individual SST observation. This highlights the value of altimetry data for ocean state estimation, and the significance of expanding the altimeter constellation. The observations that are most impactful of all are in situ measurements of temperature and salinity, which have typically 3{\textendash}4 times more impact than an individual SSH datum. A robust geographical distribution of the observation impacts emerges across a range of transport metrics which results from the combined influence of space-time dynamical interpolation and error covariance information within the 4D-Var system. The observation impact calculations suggest that High Frequency (HF) radar estimates of surface currents have relatively little direct influence on cross-shelf transport estimates. However, quantification of the sensitivity of these same estimates to changes in the observing system indicate that HF radar observations indirectly provide important information. This is understood in the current system by appealing to the idea of borrowing strength from the field of statistics in which some observations (satellite remote sensing in the case considered here) can borrow strength from other, seemingly less important observations.},
	keywords = {4D-Var, Mid Atlantic Bight, Observation impact},
	issn = {0273-1177},
	doi = {10.1016/j.asr.2019.09.012},
	author = {Levin, J. and Arango, H. G. and Laughlin, B. and Wilkin, J. and Moore, A. M.}
}
