[A-AS11] Atmospheric Chemistry

[AAS11-09] Characteristics of the Digital Filter Method for the Analyses of Long-term Variations of Stratospheric Ozone and Other Species with AURA/MLS Satellite Data

*Tianliang Yang^1,2, Tomoo Nagahama², Tac Nakajima^1,2 (1.Department of Electrical Engineering, Graduate School of Engineering, Nagoya University, 2.Institute for Space-Earth Environmental Research, Nagoya University)

Keywords:Ozone, Digital filter, QBO, Long-term trend

Research on the long-term trend of stratospheric ozone has been highly attractive since the discovery of huge loss of ozone over Antarctica in 1985 [1].Abundant observational and simulation studies agree on the point that the stratospheric ozone begins to recover with turnover between 1997 and 2000 [2]. As for the ozone trend, various results from linear regression analysis, named multi-linear regression (MLR) analysis, on multiple natural indices independent of each other, are consistent with differences within 5%. However, the mechanisms by which these indices of the natural variability affect the long-term variation of ozone are not yet fully understood. We designed a new method, Digital Filter (DF), to extract out the long-term component of stratospheric ozone variation. The new DF is based on the DF methods of other meteorological models, such as the CO₂ concentration [3] and tropospheric ozone [4]. The DF output patterns of stratospheric equatorial ozone data from AURA/MLS satellite were found to be consistent with previous results of the QBO patterns [5]. The QBO-like signal of polar ozone from the DF method shows consistent results for both hemispheres after 2018, whereas there are irregular time variability and hemispheric asymmetry in the earlier periods. In this presentation, we show the scheme of the DF method we used and report its long-term output of variations in ozone and other minor constituents.

References
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