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An ozone climatology using space-time spectral analyses is now available as NASA Reference Publication RP-1360. This note gives a brief description of RP-1360 and examples of its graphics. The address for copies of the publication is given, along with the Internet route for obtaining tabulated data via ftp.

We provide here an estimate of the uncertainties that would result when combining multiple Total Ozone Mapping Spectrometer (TOMS) datasets to produce a long-term column ozone record. We use calibration results and various post-launch validations to estimate calibration-related uncertainties for each of the instruments. Two basic methods for combining the individual data records are examined. We assess the combined uncertainty in the global column ozone data record for the period 1978-2000 for both methods using a Monte Carlo model with basic Gaussian statistics. In the case where TOMS data are combined without relative adjustments we estimate a trend uncertainty of slightly less than 1% per decade in the column ozone time dependence. The recently re-calibrated Solar Backscattered Ultraviolet 2 (SBUV2) datasets can be utilized to bridge a gap between TOMS datasets that occurred in the mid-1990s. With our current understanding of the sensor comparisons, we estimate a small improvement in the combined TOMS trend uncertainty. A more significant improvement comes from considering an extended TOMS data record, out to 2007. We estimate an extended ozone trend uncertainty as low as 0.5% per decade. [ABSTRACT FROM AUTHOR]

The Solar Backscattered Ultraviolet (SBUV)/2 instrument on-board the National Oceanic and Atmospheric Administration (NOAA)-9 satellite monitored global total ozone and its vertical distribution from 1985 to 1998. The instrument's diffuser reflectivity calibration system failed early in the mission and an alternative calibration procedure with a time extrapolation was used for an initial processing (Version 6.1 data). The total ozone data shows a +3% drift from 1992 to 1998 as well as large seasonal variations with respect to ground based and other satellite data. Using two internal data validation techniques the total ozone data quality is significantly improved. One method, the 'D-pair Method', which is analogous to the method used for the Nimbus 7 SBUV, corrects the diffuser reflectivity calibration and eliminates the drift in total ozone for NOAA-9. The D-pair Method applied to NOAA-11 SBUV/2 data from 1989 to 1994 shows good agreement with the NOAA-11 on-board diffuser reflectivity calibration system. The second validation method, the 'PMT System Method', is a new method that corrects the Photomultiplier Tube System Nonlinearity Characterization in Range 3 thereby reducing the seasonal variation in total ozone. The PMT System Method corrects both the NOAA-9 and NOAA-11 data. [ABSTRACT FROM AUTHOR]

The Solar Backscattered Ultraviolet model 2 (SBUV/2) instrument on the National Oceanic and Atmospheric Administration (NOAA-11) satellite has measured global total ozone and its altitude profile in the stratosphere since 1989. For the ozone measurement, its monochromator scans 12 discrete wavelengths from 252-340 nm. An onboard calibration system malfunctioned in late 1994. This necessitated the development of alternative methods of characterizing sensor sensitivity change. Assuming that the seasonal variation of surface reflectivity is the same from year to year, we used radiance measurements at 340 nm over the polar snow and ice to determine long-term instrument sensitivity drift at 340 nm. The spectral dependence of sensor sensitivity change in 1993 was used as an initial estimate for the current calibration. We then refined the calibration at 313, 318 and 331 nm for the total ozone retrieval, using the D-pair validation analysis. The estimated uncertainty in the extended calibration is less than 1%. The updated calibration has been used for NOAA-11 SBUV/2 operation. The resulting NOAA-11 SBUV/2 total ozone data were compared with ozone data from the Earth Probe Total Ozone Mapping Spectrometers (TOMS). The two agree with each other to better than 2%. [ABSTRACT FROM AUTHOR]