Solar Backscatter UV (SBUV) total ozone and profile algorithm

Abstract

We describe the algorithm that has been applied to develop a 42 yr record of total ozone and ozone profiles from eight Solar Backscatter UV (SBUV) instruments launched on NASA and NOAA satellites since April 1970. The Version 8 (V8) algorithm was released more than a decade ago and has been in use since then at NOAA to produce their operational ozone products. The current algorithm (V8.6) is basically the same as V8, except for updates to instrument calibration, incorporation of new ozone absorption cross-sections, and new ozone and cloud height climatologies. Since the V8 algorithm has been optimized for deriving monthly zonal mean (MZM) anomalies for ozone assessment and model comparisons, our emphasis in this paper is primarily on characterizing the sources of errors that are relevant for such studies. When data are analyzed this way the effect of some errors, such as vertical smoothing of short-term variability, and noise due to clouds and aerosols diminish in importance, while the importance of others, such as errors due to vertical smoothing of the quasi-biennial oscillation (QBO) and other periodic and aperiodic variations, become more important. With V8.6 zonal mean data we now provide smoothing kernels that can be used to compare anomalies in SBUV profile and partial ozone columns with models. In this paper we show how to use these kernels to compare SBUV data with Microwave Limb Sounder (MLS) ozone profiles. These kernels are particularly useful for comparisons in the lower stratosphere where SBUV profiles have poor vertical resolution but partial column ozone values have high accuracy. We also provide our best estimate of the smoothing errors associated with SBUV MZM profiles. Since smoothing errors are the largest source of uncertainty in these profiles, they can be treated as error bars in deriving interannual variability and trends using SBUV data and for comparing with other measurements. In the V8 and V8.6 algorithms we derive total column ozone by integrating the SBUV profiles, rather than from a separate set of wavelengths, as was done in previous algorithm versions. This allows us to extend the total ozone retrieval to 88° solar zenith angle (SZA). Since the quality of total column data is affected by reduced sensitivity to ozone in the lower atmosphere by cloud and Rayleigh attenuation, which gets worse with increasing SZA, we provide our best estimate of these errors, as well as the kernels that can be used to test the sensitivity of the derived columns to long-term changes in ozone in the lower atmosphere

Estimating uncertainties in the SBUV Version 8.6 merged profile ozone data set

“…The SBUV instrument series and most recent Version 8.6 data processing have been described in detail in a series of publications (DeLand et al, 2012;McPeters et al, 2013;Bhartia et al, 2013). The data have been assessed and compared to independent measurements by Labow et al (2013) and Kramarova et al (2013b).…”

“…We recently reported on our updated Merged Ozone Data (MOD) record of integrated total column SBUV measurements . Here we extend the record by considering the ozone profile measurements in layers from 25 to 1 hPa, where SBUV provides the best vertical resolution (Kramarova et al, 2013a;Bhartia et al, 2013). The SBUV record comprises data from nine instruments (Nimbus 4 backscatter ultraviolet (BUV), Nimbus 7 SBUV and SBUV/2s on NOAA 9,11,14,16,17,18,19), providing ozone measurements over an era of changing chlorine levels and changing stratospheric climate.…”

Comparison of profile total ozone from SBUV (v8.6) with GOME-type and ground-based total ozone for a 16-year period (1996 to 2011)

“…The only exception is the exclusion outside the ECT (Equator crossing time) range of 8 a.m. to 4 p.m. and nearly all NOAA-9 data. Discussion of SBUV v8.6 algorithm is presented by Bhartia et al (2013). An overview of the version 8.6 SBUV ozone data record is discussed by McPeters et al (2013).…”

Postlaunch performance of the Suomi National Polar‐orbiting Partnership Ozone Mapping and Profiler Suite (OMPS) nadir sensors

“…The retrieval algorithms designed to work with the OMPS nadir sensors utilize a normalized radiance (NR), which is the ratio of measured Earth radiance to measured solar irradiance [Bhartia et al, 2013;Rodriguez et al, 2003]. Radiometric requirements that allow OMPS to meet its ozone accuracy and precision specifications are based on NR also referred to as top-of-the-atmosphere reflectance.…”