Improving the representation of internal waves in the Navy and NOAA data assimilative forecasting sy

Abstract

The Global Ocean Forecast System (GOFS) is the U.S. Navy?s operational global ocean prediction system that runs daily at US Navy pro,duction centers. The system depicts the location of mesoscale features such as oceanic eddies and fronts, i.e., the ?ocean weather?,, and provides accurate 3-dimensional ocean temperature, salinity, and current structure to the Fleet. In the last decades, GOFS has,improved its predictive capabilities for ocean circulation over a wide range of frequencies and wave numbers. The assimilation of ob,servational data using NCODA-3DVAR, a three-dimensional variational data assimilation (DA) technique, has significantly lowered the,forecast errors of subtidal fields (Chassignet et al., 2009; Cummings and Smedstad, 2014; Luecke et al, 2017). A major step forward,in the HYCOM system was achieved with the introduction of tidal forcing (Arbic et al., 2010, 2012, 2018). The current implementation, of NCODA-3DVAR data assimilation data of observational data is however, not without drawbacks. It causes shocks in the positioning,of mesoscale fields and these shocks can result in high-frequency internal gravity waves, which appear as ?noise? in the tidal bands, and inertial bands in regions with strong mesoscale activity. These spurious internal waves cause an excess of energy when compared, to observations (drifters) and/or to simulations without data assimilation. The main objective of this proposal is to have more acc,urate internal tide predictions in GOFS by reducing the generation of high-frequency noise introduced by the data assimilation and b,y taking advantage of the new observational datasets. To minimize the noise introduced by the DA, we propose to evaluate several dat,a assimilation techniques and to quantify their impact on the representation of high-frequency motions. The data assimilation method,s are NCODA-3DVAR (default configuration; Cummings, 2005), TSIS (Srinivasan et al., 2021), 4DVAR (Ngodock and Carrier, 2014), and LE,TKF (Penny, 2014). The evaluations will be performed in idealized, regional, and global HYCOM configurations.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 08, 2022
Source ID
N000142212574

Entities

People

  • Eric Chassignet

Organizations

  • Florida State University
  • Office of Naval Research
  • United States Navy

Tags

Fields of Study

  • Environmental science

Readers

  • Coastal Oceanography
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers