Ozone climatology, trends, and substances that control ozone

Fioletov, Vitali

doi:10.3137/ao.460103

Cited by 59 publications

(53 citation statements)

References 144 publications

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“…Near 25 km, the ozone climatology is lower at the poles than at lower latitudes. This distribution is similar to that from SAGE data (e.g., Fioletov, 2008). The mean ozone distribution from the 1970s to the 2000s at 19.5 km is shown in Fig.…”

Section: Comparison With Osiris Ozone Datasupporting

confidence: 67%

A global ozone climatology from ozone soundings via trajectory mapping: a stratospheric perspective

et al. 2013

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Abstract. This study explores a domain-filling trajectory approach to generate a global ozone climatology from relatively sparse ozonesonde data. Global ozone soundings comprising 51 898 profiles at 116 stations over 44 yr are used, from which forward and backward trajectories are calculated from meteorological reanalysis data to map ozone measurements to other locations and so fill in the spatial domain. The resulting global ozone climatology is archived monthly for five decades from the 1960s to the 2000s on a grid of 5 • × 5 • × 1 km (latitude, longitude, and altitude), from the surface to 26 km altitude. It is also archived yearly for the same period. The climatology is validated at 20 selected ozonesonde stations by comparing the actual ozone sounding profile with that derived through trajectory mapping of ozone sounding data from all stations except the one being compared. The two sets of profiles are in good agreement, both overall with correlation coefficient r = 0.991 and root mean square (RMS) of 224 ppbv and individually with r from 0.975 to 0.998 and RMS from 87 to 482 ppbv. The ozone climatology is also compared with two sets of satellite data from the Satellite Aerosol and Gas Experiment (SAGE) and the Optical Spectrography and InfraRed Imager System (OSIRIS). The ozone climatology compares well with SAGE and OSIRIS data in both seasonal and zonal means. The mean differences are generally quite small, with maximum differences of 20 % above 15 km. The agreement is better in the Northern Hemisphere, where there are more ozonesonde stations, than in the Southern Hemisphere; it is also better in the middle and high latitudes than in the tropics where reanalysis winds are less accurate. This ozone climatology captures known features in the stratosphere as well as seasonal and decadal variations of these features. The climatology clearly shows the depletion of ozone from the 1970s to the mid 1990s and ozone increases in the 2000s in the lower stratosphere. When this climatology is used as the upper boundary condition in an Environment Canada operational chemical forecast model, the forecast is improved in the vicinity of the upper troposphere-lower stratosphere (UTLS) region. This ozone climatology is latitudinally, longitudinally, and vertically resolved and it offers more complete high latitude coverage as well as a much longer record than current satellite data. As the climatology depends on neither a priori data nor photochemical modeling, it provides independent information and insight that can supplement satellite data and model simulations of stratospheric ozone.

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Section: Comparison With Osiris Ozone Datasupporting

confidence: 67%

A global ozone climatology from ozone soundings via trajectory mapping: a stratospheric perspective

et al. 2013

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“…The PHYS model uses physical variables PV, GEO, EP and DAY to describe ozone variation whereas the STAT model uses harmonic time series with periods of a year and half a year for this parameterization. This method, similar to a Fourier filter on seasonal and sub-seasonal frequencies, is widely applied in previous ozone regression studies (e.g., see Fioletov et al, 2008 for an overview). Table 3 shows an overview of the incorporated explanatory variables for both the PHYS and the STAT model.…”

Section: Regression Methodsmentioning

confidence: 99%

“…The first approach is similar to a Fourier filter on the corresponding frequencies and the latter is equivalent to performing the regressions on annual data independently for each month of the year. These different methods were discussed by Fioletov et al (2008). However, no study has attempted to model ozone variation in terms of physical explanatory variables only.…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

“…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.…”

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confidence: 99%

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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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“…13 of Fioletov, 2008), and t is the time in decimal years. It peaks in early 1999 (corresponding to a mean age of air of 3 years) and is expected to be valid until ∼ 2015.…”

Section: E Sioris Et Al: Trend and Variability In Ozone In The Tmentioning

confidence: 99%

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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Ozone climatology, trends, and substances that control ozone

Abstract: To cite this article: V.E. Fioletov (2008)

Cited by 59 publications

References 144 publications

A global ozone climatology from ozone soundings via trajectory mapping: a stratospheric perspective

A global ozone climatology from ozone soundings via trajectory mapping: a stratospheric perspective

Spatial regression analysis on 32 years of total column ozone data

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

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