HR: 11:50h
AN: IN22A-07    [Abstracts]
TI: SOAR: A System for the Analysis of Atmospheric Radiances
AU: * Halem, M
EM: halem@umbc.edu
AF: University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, United States
AU: Yesha, Y
EM: yeyesha@umbc.edu
AF: University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, United States
AU: Tilmes, C
EM: Curt.Tilmes@nasa.gov
AF: NASA Goddard Space Flight Center, Code 614.5, Greenbelt, MD 20771, United States
AU: Chapman, D
EM: dchapm2@umbc.edu
AF: University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, United States
AU: Most, N
EM: Neal.Most@nasa.gov
AF: Innovim, 1250 Connecticut Ave NW, Washington, DC 20036, United States
AU: Bertolli, A
EM: Angelo.Bertolli@nasa.gov
AF: Innovim, 1250 Connecticut Ave NW, Washington, DC 20036, United States
AB: We have used a Service Oriented Architecture (SOA) approach to develop a system to produce multi-year, multi-sensor gridded atmospheric radiances on-demand. NASA's Aqua spacecraft launched in 2002 and has provided 5 years of calibrated atmospheric radiances from the AIRS, AMSU and MODIS instruments that are available through SOAR. The system utilizes an IBM power pc compute cluster consisting of a 44 dual and quad blade system. The high resolution spatial, temporal and hyperspectral arrays required to process multiple years of these radiance data from the three sensors required large volumes of local processor memory. In order to reduce virtual memory swapping, leading to large disk I/O times, the observational data was distributed onto multiple processor memories thus making on-demand processing feasible. The on-demand SOAR system processing includes rigorous configuration management and captures the complete data provenance information to ensure scientific reproducibility of the ephemeral on-demand datasets. The system can be used to overlay multi sensor data fields to analyze, explore and visualize the consistency of these multi year radiance data records. In particular, the data were converted to a set of canonical units based on the Brightness Temperature of the radiance fields at correlated wavelengths. This capability greatly simplifies intercomparison across the various sensors. NASA's scientific emphasis has been moving from a "mission" based focus to "measurement" based focus. SOAR crosses the mission boundaries to analyze multiple sensors that capture similar measurements. NASA and NOAA have over 30 years of atmospheric radiance data from various missions. In conjunction with the DoD, the next generation of Earth Observing satellites in the National Polar-orbiting Operational Environmental Satellite System (NPOESS), will acquire similar data for the next 30 years. Applying our techniques to the complete data record is an important first step toward the development of consistent, long term Climate Data Record (CDR) based on the Atmospheric Radiance measurement. The service oriented approach of this system also allows it to be used as a building block layer in other applications by appropriate researchers.
DE: 0520 Data analysis: algorithms and implementation
DE: 0525 Data management
DE: 0530 Data presentation and visualization
SC: Earth and Space Science Informatics [IN]
MN: 2007 Fall Meeting