Search from over 60,000 research works

Advanced Search

On the statistical modeling of persistence in total ozone anomalies

[thumbnail of Vyushin2010.pdf]
Preview
Vyushin2010.pdf - Published Version (279kB) | Preview
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Vyushin, D. I., Shepherd, T. G. orcid id iconORCID: https://orcid.org/0000-0002-6631-9968 and Fioletov, V. E. (2010) On the statistical modeling of persistence in total ozone anomalies. Journal of Geophysical Research, 115. D16306. ISSN 0148-0227 doi: 10.1029/2009JD013105

Abstract/Summary

Geophysical time series sometimes exhibit serial correlations that are stronger than can be captured by the commonly used first‐order autoregressive model. In this study we demonstrate that a power law statistical model serves as a useful upper bound for the persistence of total ozone anomalies on monthly to interannual timescales. Such a model is usually characterized by the Hurst exponent. We show that the estimation of the Hurst exponent in time series of total ozone is sensitive to various choices made in the statistical analysis, especially whether and how the deterministic (including periodic) signals are filtered from the time series, and the frequency range over which the estimation is made. In particular, care must be taken to ensure that the estimate of the Hurst exponent accurately represents the low‐frequency limit of the spectrum, which is the part that is relevant to long‐term correlations and the uncertainty of estimated trends. Otherwise, spurious results can be obtained. Based on this analysis, and using an updated equivalent effective stratospheric chlorine (EESC) function, we predict that an increase in total ozone attributable to EESC should be detectable at the 95% confidence level by 2015 at the latest in southern midlatitudes, and by 2020–2025 at the latest over 30°–45°N, with the time to detection increasing rapidly with latitude north of this range.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/31567
Item Type Article
Refereed Yes
Divisions No Reading authors. Back catalogue items
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher American Geophysical Union
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar