DocumentCode
392945
Title
Real-time ocean data assimilation and prediction with global NCOM
Author
Rowley, C. ; Barron, C. ; Smedstad, L. ; Rhodes, R.
Author_Institution
Naval Res. Lab., Stennis Space Center, MS, USA
Volume
2
fYear
2002
fDate
29-31 Oct. 2002
Firstpage
775
Abstract
The Naval Research Laboratory (NRL) at Stennis Space Center has developed a global implementation of the Navy Coastal Ocean Model (NCOM). Global NCOM encompasses the open ocean to 5 m depth in a curvilinear global model grid with 1/8 degree grid spacing at 45°N, extending from 80°S to a complete Arctic cap with grid singularities mapped into Canada and Russia. The model employs 40 vertical sigma-z levels, with sigma in the upper ocean and coastal regions, and z in the deeper ocean. The real-time system uses Navy Operational Global Atmospheric Prediction System (NOGAPS) 3-hourly wind stresses and heat fluxes. Operationally available sea surface temperature (SST) and altimetry (SSH) data are incorporated into NAVOCEANO Modular Ocean Data Assimilation System (MODAS) and Navy Layered Ocean Model (NLOM) analyses and forecasts of SSH and SST. These in turn are combined with the MODAS synthetic database to yield three-dimensional fields of temperature and salinity for assimilation into global NCOM. We describe the analysis and forecast system, present selected evaluations of the model performance, and discuss planned upgrades to the model and data assimilation methods.
Keywords
oceanographic techniques; oceanography; 0 to 5 m; Canada; MODAS analyses; MODAS synthetic database; Modular Ocean Data Assimilation System; NAVOCEANO; NLOM analyses; NOGAPS; Naval Research Laboratory; Navy Coastal Ocean Model; Navy Layered Ocean Model; Navy Operational Global Atmospheric Prediction System; Russia; SSH data; SST data; Stennis Space Center; altimetry data; coastal region; curvilinear global model grid; deeper ocean; global NCOM; heat flux; real-time ocean data assimilation; real-time ocean data prediction; sea surface height; sea surface temperature; upper ocean; wind stress; Arctic; Atmospheric modeling; Data assimilation; Laboratories; Ocean temperature; Predictive models; Real time systems; Sea measurements; Stress; Wind forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
OCEANS '02 MTS/IEEE
Print_ISBN
0-7803-7534-3
Type
conf
DOI
10.1109/OCEANS.2002.1192068
Filename
1192068
Link To Document