HR: 1340h
AN: A43B-0089    [Abstracts]
TI: Evaluation of OMPS LP algorithm with SAGE III proxy data
AU: * Qin, W
EM: wenhan_qin@ssaihq.com
AF: SSAI, 10210 Greenbelt Road, Suite 405, Lanham, MD 20706 United States
AU: Jaross, G
EM: glen_jaross@ssaihq.com
AF: SSAI, 10210 Greenbelt Road, Suite 405, Lanham, MD 20706 United States
AU: McPeters, R
EM: Richard.D.McPeters@nasa.gov
AF: Code 613.3, NASA/GSFC, Greenbelt Rd., Greenbelt, MD 20771 United States
AU: Rault, D
EM: Didier.F.Rault@nasa.gov
AF: Climate Science Branch, NASA Langley Research Center, Mailstop 475, Hampton, VA 23681 United States
AB: The UV/VIS Limb Profile Ozone Algorithm is designed to retrieve the vertical ozone profile from OMPS sensor data with an accuracy of 10% between 15 km and 60 km. Retrievals utilize scene radiances normalized to the radiances from a single Earth tangent height from 290 nm to 1000 nm to maintain this accuracy over the full altitude range. While the basic retrieval approach has been used successfully with existing limb scatter data sets, implementation specifics differ between instruments. In particular, the OMPS limb sensor design has complexities, such as multiple images, that have created challenges in the algorithm design. Consequently, testing the algorithm with realistic data is of utmost importance to demonstrating its retrieval capabilities. We have begun tests of the OMPS algorithm using SAGE III limb scatter radiances as input. SAGE III was chosen because its spectral and spatial resolution exceed that of OMPS, and can be degraded to appear OMPS-like. With the proxy data we have evaluated the performance of the OMPS limb algorithm under different atmospheric conditions (aerosol, clouds, and surface albedo) and analyzed the influence of some error sources on the accuracy and percision of the EDR production. Examples of error investigations include: spectral calibration, wavelength-dependent and -independent radiometric calibration, stray light, aerosol corrections, cloud top or surface pressure, altitude registration, and pressure and temperature profiles. Based upon our findings, we present options to improve ozone profile retrieval of the LP algorithm.
DE: 0360 Radiation: transmission and scattering
DE: 0394 Instruments and techniques
DE: 3311 Clouds and aerosols
DE: 3359 Radiative processes
DE: 3360 Remote sensing
SC: Atmospheric Sciences [A]
MN: Fall Meeting 2005