Show simple item record

dc.contributor.authorChao, Yi
dc.contributor.authorLi, Zhijin
dc.contributor.authorFarrara, John
dc.contributor.authorMcWilliams, James C.
dc.contributor.authorBellingham, James
dc.contributor.authorCapet, Xavier
dc.contributor.authorChavez, Francisco
dc.contributor.authorChoi, Jei-Kook
dc.contributor.authorDavis, Russ
dc.contributor.authorDoyle, Jim
dc.contributor.authorFratantoni, David M.
dc.contributor.authorLi, Peggy
dc.contributor.authorMarchesiello, Patrick
dc.contributor.authorMoline, Mark A.
dc.contributor.authorPaduan, Jeff
dc.contributor.authorRamp, Steve
dc.date.accessioned2018-11-20T18:36:01Z
dc.date.available2018-11-20T18:36:01Z
dc.date.issued2009
dc.identifier.citationChao, Yi, et al. "Development, implementation and evaluation of a data-assimilative ocean forecasting system off the central California coast." Deep Sea Research Part II: Topical Studies in Oceanography 56.3-5 (2009): 100-126.
dc.identifier.urihttps://hdl.handle.net/10945/60673
dc.description.abstractThe 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 conj. unction 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 degrees C and 0.2 psu (practical salinity unit), respectively, with root-mean-square (RMS) differences of less than 1.5 degrees 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.en_US
dc.publisherElsevier
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleDevelopment, implementation and evaluation of a data-assimilative ocean forecasting system off the central California coasten_US
dc.typeArticleen_US
dc.subject.authorData assimilationen_US
dc.subject.authorOcean modelingen_US
dc.subject.authorOcean forecasten_US
dc.subject.authorCoastal oceanen_US
dc.subject.authorAdaptive samplingen_US
dc.subject.authorReanalysisen_US
dc.description.funderJet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA)
dc.description.funderOffice of Naval Research (ONR) through a subcontract from MBARI to Raytheon
dc.description.funderONR’s program element 0601153N for J. Doyle
dc.description.funderComputational resources for COAMPS were supported in part by the FNMOC.


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record