The Quasi-biennial Oscillation and annual variations in tropical ozone from SHADOZ and HALOE

Witte, J. C.; Schoeberl, M. R.; Douglass, A. R.; Thompson, A. M.

doi:10.5194/acp-8-3929-2008

Cited by 32 publications

(27 citation statements)

References 28 publications

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“…For ENSO, the power is largest at slightly < 4 years but there is a second period of ∼ 6 years with comparable power. For the QBO, the peak in the periodogram is at slightly longer than 2 years, as expected (Witte et al, 2008). The solar cycle has a single poorly resolved peak with an approximate period of a decade, corresponding to the well-known 11-year solar cycle.…”

Section: Eescmentioning

confidence: 65%

“…sponse to the local QBO signal (Witte et al, 2008). These pairs of QBO basis functions act similarly to the orthogonalized QBO basis functions of .…”

Section: Qbomentioning

confidence: 99%

“…5b) even if a seasonal trend had been included. Understanding what controls the year-to-year variability of the seasonal cycle (Ploeger et al, 2012;Witte et al, 2008) could lead to an improved regression model and have an impact on estimated trends and their uncertainties. It is doubtful that annual harmonics of QBO, ENSO, or the solar cycle could explain the strong annual cycles of the overlap period immediately above the tropopause, although the combined effect of annual QBO and ENSO harmonics should be investigated when an improved version of the OSIRIS ozone retrieval becomes available.…”

Section: Non-linear Sources Of Variabilitymentioning

confidence: 99%

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Trend and variability in ozone in the tropical lower stratosphere over 2.5 solar cycles observed by SAGE II and OSIRIS

et al. 2014

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Abstract.We have extended the satellite-based ozone anomaly time series to the present (December 2012) by merging SAGE II (Stratospheric Aerosol and Gas Experiment II) with OSIRIS (Optical Spectrograph and Infrared Imager System) and correcting for the small bias (∼ 0.5%) between them, determined using their temporal overlap of 4 years. Analysis of the merged data set shows a statistically significant negative trend at all altitudes in the 18-25 km range, including a trend of (−4.6 ± 2.6) % decade −1 at 19.5 km where the relative standard error is a minimum. We are also able to replicate previously reported decadal trends in the tropical lowerstratospheric ozone anomaly based on SAGE II observations. Uncertainties are smaller on the merged trend than the SAGE II trend at all altitudes. Underlying strong fluctuations in ozone anomaly due to El Niño-Southern Oscillation (ENSO), the altitude-dependent quasi-biennial oscillation, and tropopause pressure need to be taken into account to reduce trend uncertainties and, in the case of ENSO, to accurately determine the linear trend just above the tropopause. We also compare the observed ozone trend with a calculated trend that uses information on tropical upwelling and its temporal trend from model simulations, tropopause pressure trend information derived from reanalysis data, and vertical profiles from SAGE II and OSIRIS to determine the vertical gradient of ozone and its trend. We show that the observed trend agrees with the calculated trend and that the magnitude of the calculated trend is dominated by increased tropical upwelling, with minor but increasing contribution from the vertical ozone gradient trend as the tropical tropopause is approached. Improvements are suggested for future regression modelling efforts which could reduce trend uncertainties and biases in trend magnitudes, thereby allowing accurate trend detection to extend below 18 km.

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Section: Eescmentioning

confidence: 65%

“…sponse to the local QBO signal (Witte et al, 2008). These pairs of QBO basis functions act similarly to the orthogonalized QBO basis functions of .…”

Section: Qbomentioning

confidence: 99%

Section: Non-linear Sources Of Variabilitymentioning

confidence: 99%

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Trend and variability in ozone in the tropical lower stratosphere over 2.5 solar cycles observed by SAGE II and OSIRIS

et al. 2014

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“…The effect of the quasi-biennial oscillation (QBO) in easterly and westerly stratospheric winds in the tropics on stratospheric ozone is a well-established effect based on both observations and stratospheric modeling and is known to affect stratospheric ozone outside the tropics as well (McCormack et al, 2007;Witte et al, 2008;WMO 2010, chapter 2, and references therein). The QBO is represented by time series of monthly averaged wind speed measurements done by the ground station in Singapore (Baldwin et al, 2001).…”

Section: Qbomentioning

confidence: 99%

Spatial regression analysis on 32 years of total column ozone data

Knibbe

Laat

2014

Atmos. Chem. Phys.

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Abstract. Multiple-regression analyses have been performed on 32 years of total ozone column data that was spatially gridded with a 1 × 1.5 • resolution. The total ozone data consist of the MSR (Multi Sensor Reanalysis; 1979-2008 and 2 years of assimilated SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) ozone data (2009)(2010). The two-dimensionality in this data set allows us to perform the regressions locally and investigate spatial patterns of regression coefficients and their explanatory power. Seasonal dependencies of ozone on regressors are included in the analysis.A new physically oriented model is developed to parameterize stratospheric ozone. Ozone variations on nonseasonal timescales are parameterized by explanatory variables describing the solar cycle, stratospheric aerosols, the quasibiennial oscillation (QBO), El Niño-Southern Oscillation (ENSO) and stratospheric alternative halogens which are parameterized by the effective equivalent stratospheric chlorine (EESC). For several explanatory variables, seasonally adjusted versions of these explanatory variables are constructed to account for the difference in their effect on ozone throughout the year. To account for seasonal variation in ozone, explanatory variables describing the polar vortex, geopotential height, potential vorticity and average day length are included. Results of this regression model are compared to that of a similar analysis based on a more commonly applied statistically oriented model. The physically oriented model provides spatial patterns in the regression results for each explanatory variable. The EESC has a significant depleting effect on ozone at midand high latitudes, the solar cycle affects ozone positively mostly in the Southern Hemisphere, stratospheric aerosols affect ozone negatively at high northern latitudes, the effect of QBO is positive and negative in the tropics and mid-to high latitudes, respectively, and ENSO affects ozone negatively between 30 • N and 30 • S, particularly over the Pacific. The contribution of explanatory variables describing seasonal ozone variation is generally large at mid-to high latitudes. We observe ozone increases with potential vorticity and day length and ozone decreases with geopotential height and variable ozone effects due to the polar vortex in regions to the north and south of the polar vortices.Recovery of ozone is identified globally. However, recovery rates and uncertainties strongly depend on choices that can be made in defining the explanatory variables. The application of several trend models, each with their own pros and cons, yields a large range of recovery rate estimates. Overall these results suggest that care has to be taken in determining ozone recovery rates, in particular for the Antarctic ozone hole.

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“…SHADOZ datasets are well known and increasingly used for climatological studies (Lamsal et al, 2004;McPeters et al, 2007), variability studies (Logan et al, 2003;Witte et al, 2008) or comparison studies (Liu et al, 2006;Sivakumar et al, 2007), for case studies such as ozone isentropic transport in the lower stratosphere (Semane et al, 2006;Bencherif et al, 2007), and for trend analyses (Clain et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Climatology and comparison of ozone from ENVISAT/GOMOS and SHADOZ/balloon-sonde observations in the southern tropics

Mzé¹,

Hauchecorne

Benchérif³

et al. 2010

Atmos. Chem. Phys.

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Abstract. In this paper, the stellar occultation instrument GOMOS is compared with ozonesondes from the SHADOZ network. We only used nighttime O 3 profiles and selected 8 Southern Hemisphere stations. 7 years of GOMOS datasets (GOPR 6.0cf and IPF 5.0) and 11 years of balloon-sondes are used in this study. A monthly distribution of GOMOS O 3 mixing ratios was performed in the upper-troposphere and in the stratosphere (15-50 km). A comparison with SHADOZ was made in the altitude range between 15 km and 30 km.In the 21-30 km altitude range, a satisfactory agreement was observed between GOMOS and SHADOZ, although some differences were observed depending on the station. The range for monthly differences generally decreases with increasing height and is within ±15%. It was found that the agreement between GOMOS and SHADOZ declines below ∼20 km. The median differences are almost within ±5%, particularly above 23 km. But a large positive bias was found below 21 km, in comparison to SHADOZ.

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The Quasi-biennial Oscillation and annual variations in tropical ozone from SHADOZ and HALOE

Cited by 32 publications

References 28 publications

Trend and variability in ozone in the tropical lower stratosphere over 2.5 solar cycles observed by SAGE II and OSIRIS

Trend and variability in ozone in the tropical lower stratosphere over 2.5 solar cycles observed by SAGE II and OSIRIS

Spatial regression analysis on 32 years of total column ozone data

Climatology and comparison of ozone from ENVISAT/GOMOS and SHADOZ/balloon-sonde observations in the southern tropics

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