Nesting and data assimilation considerations in regional operational ocean forecasting

ABSTRACT

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.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was sponsored by the Office of Naval Research Program Element 62435N as part of the ‘‘Local Analysis Through Tactical Ensonification’’ project. This paper is NRL paper contribution number NRL/JA/7320-20-5021.

Notes on contributors

Hans Ngodock

Dr. Hans Ngodock is an oceanographer with the Naval Research Laboratory. He received his PhD in Applied Mathematics and inverse modeling from the Université Joseph Fourier (France) in 1996. His expertise is in the implementation of advanced data assimilation algorithms into numerical models, with applications to single and coupled models of the ocean, atmosphere, waves and acoustics.

Matthew Carrier

Dr. Matthew Carrier is an oceanographer with the Naval Research Laboratory. He received his PhD in Meteorology and data assimilation The Florida State University in 2008. His expertise is in the implementation of advanced data assimilation algorithms into numerical models, with applications to single and coupled models of the ocean, atmosphere, waves and acoustics.

John Osborne

Dr. John Osborne is an oceanographer with the Naval Research Laboratory. He received his PhD in Physical Oceanography and data assimilation from Oregon State University in 2014. His expertise is in ocean modeling and the implementation of advanced data assimilation algorithms into numerical models, with applications to single and coupled models of the ocean, atmosphere, waves and acoustics.

Scott Smith

Dr. Scott Smith is an oceanographer with the Naval Research Laboratory. He received his PhD in Aerospace Engineering from The University of Colorado in 2002. His expertise is in ocean modeling and the implementation of advanced data assimilation algorithms into numerical models, with applications to single and coupled models of the ocean, atmosphere, waves and acoustics.