Michael R. Carnes

The Modular Ocean Data Assimilation System (MODAS)

The Modular Ocean Data Assimilation System (MODAS) is used by the U.S. Navy for depiction of three- dimensional fields of temperature and salinity over the global ocean. MODAS includes both a static climatology and a dynamic climatology. While the static climatology represents the historical averages, the dynamic cli- matology assimilates near-real-time observations of sea surface height and sea surface temperature and provides improved temperature and salinity fields. The methodology for the construction of the MODAS climatology is described here. MODAS is compared with Levitus and Generalized Digital Environmental Model climatologies and with temperature and salinity profiles measured by SeaSoar in the Japan/East Sea to illustrate MODAS capabilities. MODAS with assimilated remotely sensed data is able to portray time-varying dynamical features that cannot be represented by static climatologies.

Data assimilation in a north pacific ocean monitoring and prediction system

Abstract The Naval Research Laboratory recently began experimenting with a Pacific Ocean nowcast/forecast system. It is being developed to eventually run operationally at the Fleet Numerical Meteorology and Oceanography Center (FNMOC) to provide real-time nowcasts and forecasts of the oceans temperature, salinity, sound speed and surface currents for Naval operations. This paper describes the models and assimilation schemes used and presents some early results from a pseudo-operational three-month series of test runs. Operationally available real-time data were used, and evaluations were performed using in situ observations which were not assimilated.

Inference of subsurface thermohaline structure from fields measurable by satellite

Abstract Satellites now provide global measurements of the oceans surface height and temperature. Ocean climatologies for the northwest Pacific and northwest Atlantic Oceans that relate sea surface height, sea surface temperature, day of the year, latitude, and longitude to temperature and salinity profiles were produced using least-squares regression. These analyses use over 33 000 profiles of historical temperature and salinity data and are considerably streamlined and compacted by expressing each profile in terms of empirical orthogonal functions. Evaluations and error analyses of the climatologies, including a comparison to the navys Generalized Digital Environmental Model, were performed and differences between the regions are discussed. Two sample vertical sections are shown to be closely reproduced with the climatologies. Climatologies based on surface height and temperature are found to offer considerable improvement over climatologies based only on position.

Temperature versus salinity gradients below the ocean mixed layer

Abstract : We characterize the global ocean seasonal variability of the temperature versus salinity gradients in the transition layer just below the mixed layer using observations of conductivity temperature and depth and profiling float data from the National Ocean Data Center s World Ocean Data set. The balance of these gradients determines the temperature versus salinity control at the mixed layer depth (MLD). We define the MLD as the shallowest of the isothermal, isohaline, and isopycnal layer depths (ITLD, IHLD, and IPLD), each with a shared dependence on a 0.2 deg C temperature offset. Data are gridded monthly using a variational technique that minimizes the squared analysis slope and data misfit. Surface layers of vertically uniform temperature, salinity, and density have substantially different characteristics. By examining differences between IPLD, ITLD, and IHLD, we determine the annual evolution of temperature or salinity or both temperature and salinity vertical gradients responsible for the observed MLD. We find ITLD determines MLD for 63% and IHLD for 14% of the global ocean. The remaining 23% of the ocean has both ITLD and IHLD nearly identical. It is found that temperature tends to control MLD where surface heat fluxes are large and precipitation is small. Conversely, salinity controls MLD where precipitation is large and surface heat fluxes are small. In the tropical ocean, salinity controls MLD where surface heat fluxes can be moderate but precipitation is very large and dominant.

Glider Optical Measurements and BUFR Format for Data QC and Storage

Unmanned underwater vehicles are becoming an increasingly important platform in oceanographic research and operational oceanography, where continuous in situ sampling throughout the water column is essential to understanding the ocean circulation and related biological, chemical, and optical activity. The latter directly affects field operations and remote sensing capabilities from space. A unified approach is necessary for data quality control (QC), access, and storage, considering the vast amount of data collected from gliders continuously deployed across large areas and over long durations. The Binary Universal Form for the Representation of meteorological data (BUFR) maintained by the World Meteorological Organization (WMO) is adapted to include physical and optical parameters from a variety of sensor suites onboard underwater vehicles. The provisional BUFR template and related BUFR descriptors and table entries have been developed by the U.S. Navy for ocean glider profile data and QC results. Software written in FORTRAN using the ECMWF BUFRDC library has been implemented to perform both the encoding and decoding of BUFR files from and to Network Common Data Form (NetCDF) files. This presentation also discusses data collected from sensors on gliders deployed both in deep water and shallow water environments, including issues specific to optical sensors at various depths.