Development, implementation and evaluation of a data-assimilative ocean forecasting system off the central California coast

Abstract

The development and implementation of a real-time ocean forecast system based on the Regional Ocean Modeling System (ROMS) off the coast of central California are described. The ROMS configuration consists of three nested modeling domains with increasing spatial resolutions: the US West coastal ocean at 15-km resolution, the central California coastal ocean at 5 km, and the Monterey Bay region at 1.5 km. All three nested models have 32 vertical sigma (or terrain-following) layers and were integrated in conjunction with a three-dimensional variational data assimilation algorithm (3DVAR) to produce snapshots of the ocean state every 6 h (the reanalysis) and 48-h forecasts once a day. This ROMS forecast system was operated in real time during the field experiment known as the Autonomous Ocean Sampling Network (AOSN-II) in August 2003. After the field experiment, a number of improvements were made to the ROMS forecast system: more data were added in the reanalysis with more careful quality control procedures, improvements were made in the data assimilation scheme, as well as model surface and side boundary conditions.The results from the ROMS reanalysis are presented here. The ROMS reanalysis is first compared with the assimilated data as a consistency check. An evaluation of the ROMS reanalysis against the independent measurements that are not assimilated into the model is then presented. This evaluation shows the mean differences in temperature and salinity between reanalysis and observations to be less than 1 °C and 0.2 psu (practical salinity unit), respectively, with root-mean-square (RMS) differences of less than 1.5 °C and 0.25 psu. Qualitative agreement is found between independent current measurements and the ROMS reanalysis. The agreement is particularly good for the vertically integrated current along the offshore glider tracks: the ROMS reanalysis can realistically reproduce the poleward California Undercurrent. Reasonably good agreement is found in the spatial patterns of the surface current as measured by high-frequency (HF) radars. Preliminary results concerning the ROMS forecast skill and predictability are also presented. Future plans to improve the ROMS forecast system with a particular focus on assimilation of HF radar current measurements are discussed.

The California Current System: A multiscale overview and the development of a feature-oriented regional modeling system (FORMS)

“…This idea supports the Mooers and Robinson (1984) larger-scale features including offshore eddies, the CUC and coastal trapped waves (e.g. Chao et al, 2008;Haley et al, 2009;Shulman et al, 2009;Ramp et al, 2010-this-issue).…”

Towards improving mission execution for autonomous gliders with an ocean model and kalman filter

“…The model output has three nested horizontal resolutions; the finest (2.2 km) resolution completely covers our area of interest. The vertical resolution is non-uniform, providing data at depths ranging from 0 to 2000 m. For specific details on ROMS, see [18], [19].…”

Oceanographic and atmospheric conditions on the continental shelf north of the Monterey Bay during August 2006

“…The models were run in near-real time to provide knowledge input to the adaptive sampling decision tree. The three models used were the Harvard Ocean Prediction System (HOPS) (Robinson, 1999;Haley et al, 2009;Haley and Lermusiaux, 2010), the Jet Propulsion Laboratory implementation of the Regional Ocean Modeling System (JPL/ROMS) (Schepetkin and Williams, 2004;Chao et al, 2009;Wang et al, 2009), and the Navy Coastal Ocean Model/Innovative Coastal-Ocean Observing Network (NCOM/ICON) model (Shulman et al, , 2010. Two versions of the HOPS model were examined: HOPS solo (hereafter HOPSs) which had 1.5 km horizontal resolution, and HOPS nested (hereafter HOPSn) which was nested within HOPSs and had 0.5 km horizontal resolution (Fig.…”