NRL Ocean Surface Estimates of Turbulent Flux Parameters

Accurate representation of surface fluxes at the air-sea interface is an important aspect of atmospheric, ocean, and coupled air-sea forecast modeling. In ocean models, surface heat and momentum fluxes are often estimated from near-surface atmospheric state parameters. Present and planned satellite platforms and sensors are an important source of information about the near-surface state that has not been fully exploited.

The Naval Research Laboratory Ocean Surface Flux (NFLUX) system includes three primary components. The first component consists of satellite retrievals of near-surface state parameters using observed brightness temperatures from sensors including the Special Sensor Microwave Imager/Sounder (SSMIS) onboard Department of Defense (DoD) platforms and the Advanced Microwave Sounding Unit (AMSU) onboard National Oceanic and Atmospheric Administration (NOAA) and European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) platforms. Retrievals of surface scalar wind speed from the Windsat sensor are also processed. The second component applies an automated quality control to all in situ and satellite observations. The third component performs variational analyses of in situ and satellite observations with atmospheric model forecasts to produce gridded global and regional estimates of atmospheric state parameters at the ocean surface.

We use a two-year analysis cycle (January 2010 through December 2011) to assess NFLUX analyses of surface air temperature, surface specific humidity, and 10-meter wind speed in comparison with in situ observations and atmospheric forecast models including the Navy Operational Global Atmospheric Predication System (NOGAPS) and the Coupled Ocean Atmosphere Prediction System (COAMPS). Model performance was evaluated using both assimilated and unassimilated observations globally, regionally, by latitude band, by season, and separately for coastal and open-ocean observations.

The 2-year global open-ocean assessment of NFLUX analyses and NOGAPS forecasts compared to unassimilated in situ observations shows NFLUX has a lower bias for each of the surface parameters. NFLUX global air temperature analyses show lower root mean square error (RMSE) and higher correlation. NFLUX global specific humidity analyses show higher RMSE and lower correlation. NFLUX global wind speed analyses show lower RMSE and similar correlation. We obtained similar results for evaluations of western and eastern Pacific regional NFLUX analyses.