Abstract

Abstract. The Solar Backscattered Ultraviolet (SBUV) observing system consists of a series of instruments that have been measuring both total ozone and the ozone profile since 1970. SBUV measures the profile in the upper stratosphere with a resolution that is adequate to resolve most of the important features of that region. In the lower stratosphere the limited vertical resolution of the SBUV system means that there are components of the profile variability that SBUV cannot measure. The smoothing error, as defined in the optimal estimation retrieval method, describes the components of the profile variability that the SBUV observing system cannot measure. In this paper we provide a simple visual interpretation of the SBUV smoothing error by comparing SBUV ozone anomalies in the lower tropical stratosphere associated with the quasi-biennial oscillation (QBO) to anomalies obtained from the Aura Microwave Limb Sounder (MLS). We describe a methodology for estimating the SBUV smoothing error for monthly zonal mean (mzm) profiles. We construct covariance matrices that describe the statistics of the inter-annual ozone variability using a 6 yr record of Aura MLS and ozonesonde data. We find that the smoothing error is of the order of 1% between 10 and 1 hPa, increasing up to 15–20% in the troposphere and up to 5% in the mesosphere. The smoothing error for total ozone columns is small, mostly less than 0.5%. We demonstrate that by merging the partial ozone columns from several layers in the lower stratosphere/troposphere into one thick layer, we can minimize the smoothing error. We recommend using the following layer combinations to reduce the smoothing error to about 1%: surface to 25 hPa (16 hPa) outside (inside) of the narrow equatorial zone 20° S–20° N.

Highlights

  • Comparisons of Solar Backscattered Ultraviolet (SBUV) ozone amounts in the lower stratosphere/troposphere layer with Aura Microwave Limb Sounder (MLS) (Kramarova et al, 2013) showed that the standard deviations of the differences between SBUV and MLS mzm measurements in the tropics decreased from 3–4 % for the 250–25 hPa layer to 1 % for the 250–1 %: surface to hPa (16 hPa) layer

  • In this study we present the methodology used to estimate the smoothing error for SBUV ozone monthly zonal mean profiles

  • The smoothing error represents the error in the vertical profile due to the limited vertical resolution of the observing system

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Summary

Methods and Data Systems

Merging the partial ozone columns from several layers in the nique remain the same (Bhartia et al, 2012), lending furlower stratosphere/troposphere into one thick layer, we can ther consistency to the SBUV long-term record compared minimize the smoothing error. We recommend using the fol- to those based on measurements using different instrument lowing layer combinations to reduce the smoothing error to types and making the SBUV data preferable for long-term about 1 %: surface to 25 hPa (16 hPa) outside (inside) of the narrow equatorial zone 20◦ S–20◦ N. trend istics oafnathlyesSisB. Kramarova et al.: Interpreting SBUV smoothing errors of this paper is to demonstrate the benefits and limitations of the SBUV retrieval algorithm and provide clear recommendations for SBUV data users.

Smoothing error
QBO Detection: a smoothing error example
Mathematical definition of smoothing error
SBUV A matrix
SBUV averaging kernels
Ozone mzm covariance matrix
Application of smoothing error concept to SBUV data analysis
Profile and total ozone smoothing error
Recommendations for reducing the smoothing error
QBO detection: interpretation of the SBUV smoothing error
Findings
Conclusions
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