450 Data Processing in the NRL Ocean Surface Flux System

Monday, 7 January 2013
Exhibit Hall 3 (Austin Convention Center)
Neil Van de Voorde, Qinetiq - North America, Stennis Space Center, MS; and J. May and C. D. Rowley

The Naval Research Laboratory Ocean Surface Flux (NFLUX) project was initiated to allow ocean models used by the U.S. Navy to leverage additional ocean surface information that can be obtained from existing and planned satellites systems to estimate heat and momentum fluxes at the ocean surface.

NRL Stennis Space Center has developed the NFLUX system to read, process, and quality control satellite observations based on anticipated ranges in channel brightness temperatures as well as a monthly background climate and associated variability. NFLUX currently uses passive microwave sensors onboard Polar Orbiting Environment Satellite (POES), Metop, and Defense Meteorological Satellite Program (DMSP) platforms to retrieve surface air temperature, specific humidity, and scalar wind speed. In situ observations are similarly quality controlled. The remotely sensed and in situ data are then assimilated into regional and global 2D variational analyses of the surface state parameters.

The Advanced Technology Microwave Sensor (ATMS) currently flying on the National Environmental Satellite (NPP) has recently been incorporated into the processing stream of NFLUX. Global algorithms were developed specifically for the ATMS sensor using prior Advanced Microwave Sounding Unit (AMSU) algorithms and ATMS Level 1b corrected data. The system developed has been demonstrated to provide a rapid means for algorithm development based on multiyear Voluntary Observing Ship (VOS) data coupled with a random resampling of the brightness temperature records to produce a robust set of coefficients for each of the state variable algorithms.

Near future plans include utilizing the infrared data from the Cross Track Infrared Sounder (CrIS) instrument to improve the current retrieval algorithms as well as assess the utility of using the Environmental Data Records. Atmospheric profiles will be used to support radiative transfer modeling as well as to identify temperature inversions that are problematic in the current passive microwave algorithms.

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