HR: 1340h
AN: A43D-1569    [Abstracts]
TI: Validation of Ozone Measurements From the SBUV/2 and OMI Data Sets
AU: * Nazaryan, H
EM: hovakim.nazaryan@hamptonu.edu
AF: Hampton University, 23 E. Tyler Street, Hampton, VA 23668, United States
AU: McCormick, M P
EM: PAT.MCCORMICK@hamptonu.edu
AF: Hampton University, 23 E. Tyler Street, Hampton, VA 23668, United States
AU: Flynn, L E
EM: Lawrence.E.Flynn@noaa.gov
AF: NOAA/NESDIS/STAR, 5200 Auth Road, Camp Springs, MD 20746, United States
AU: Beach, E
EM: Eric.Beach@noaa.gov
AF: NOAA/NESDIS/STAR, 5200 Auth Road, Camp Springs, MD 20746, United States
AB: Ozone is an important atmospheric constituent that shields the Earth's surface from harmful ultraviolet radiation and also plays a critical role in radiation forcing, thus affecting climate change. NOAA's second generation Solar Backscatter Ultraviolet Instruments (SBUV/2) employ the nadir-viewing backscattered ultraviolet technique to measure ozone concentration profiles in the atmosphere on a global scale. The Ozone Monitoring Instrument (OMI) is an imaging spectrometer with daily global coverage that measures columns of gases like ozone, NO₂, BrO, and SO₂. A comparison of the ozone data sets from SBUV/2 and OMI is discussed for the period when data are available from those experiments. The study of consistency among the data sets of various instruments is important in developing confidence in those data records and in determining their value in trend analyses. In order to establish the validity of the ozone data records, one needs to show that different measurement techniques based on various physical principles give similar ozone estimates. We employ advanced statistical techniques to validate the NOAA-16, NOAA-17, and NOAA-18 SBUV/2 Version-8 data sets and to compare with OMI retrievals. The SBUV/2 data are from operational and preliminary reprocessing. We consider the ozone data from these experiments co-located in time and space and analyze the time series of differences. We examine the time dependence of the bias between measurements. We also present additional validation in the form of comparisons with Dobson Station overpass match up values.
DE: 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE
DE: 3360 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting