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The influence of the stratospheric Quasi-Biennial Oscillation on trace gas levels at the Earth’s surface

Nature Geoscience volume 13, pages 22–27 (2020)Cite this article

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Abstract

The Quasi-Biennial Oscillation (QBO) of tropical zonal wind is one of the most important modes of interannual variability in the stratosphere. It is well established that the QBO influences the distribution of trace gases throughout the global stratosphere. What has not been clearly shown thus far is whether the stratospheric QBO has a consistent and significant impact on tropospheric trace gases. Here we clearly demonstrate that the effects of QBO variability in stratospheric transport and trace gas distributions regularly and persistently extend into the troposphere, which influences the interannual variability of long-lived trace gas mole fractions at the Earth’s surface. We show that the variability in the surface mole fractions on one- to five-year timescales is primarily driven by the QBO. The QBO influence on tropospheric constituent mole fractions arises from the modulation of the stratosphere to troposphere mass flux and is apparent in surface measurements, as well as throughout the stratosphere and troposphere in chemistry–climate model simulations of chlorofluorocarbon-11, chlorofluorocarbon-12 and nitrous oxide. The global total emissions estimated from measured changes in the global mean surface mole fractions of these ozone-depleting species, as well as other long-lived trace gases, will be improved by accurately accounting for the QBO-driven variability.

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Fig. 1: Surface annual growth rates of CFC-11, CFC-12 and N2O from measurements and model output.
Fig. 2: Modelled CFC-11 interannual partial pressure anomalies.
Fig. 3: Model input and derived emissions of CFC-11, CFC-12 and N2O.

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Data availability

Any of the data or model output that support the findings of this study are available from the corresponding author upon reasonable request. Trace gas mole fraction measurements are available at https://www.esrl.noaa.gov/gmd/hats/. The ERA-Interim dynamical variables were obtained from the Centre for Environmental Data Analysis archive (https://catalogue.ceda.ac.uk/uuid/b241a7f536a244749662360bd7839312). We have not produced any new data and WACCM is a community climate model so the model run used in this study can be reproduced by any model user. For this reason, we have not deposited any of the data or model output used in this study into a data repository. Any of the model output used in this study is available from the corresponding author upon reasonable request.

Code availability

Any of the code used to analyse the data or model output shown in this study is available from the corresponding author upon reasonable request.

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Acknowledgements

The CESM project is supported by the NSF and the Office of Science (BER) of the US Department of Energy. We acknowledge the NOAA Research and Development High Performance Computing Program for computing and storage resources. S.A.M., B.D.H. and G.S.D. are indebted to other scientists within NOAA/GMD and at collaborating organizations for flask sampling and analysis, and for instrument maintenance at both NOAA and the cooperative sampling sites around the world. These measurements were supported in part by the NOAA Climate Program Office’s AC4 programme.

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Authors and Affiliations

  1. Chemical Sciences Division, Earth Systems Research Laboratory, NOAA, Boulder, CO, USA

    Eric A. Ray, Robert W. Portmann, Pengfei Yu, John Daniel & Karen H. Rosenlof

  2. Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA

    Eric A. Ray, Pengfei Yu, Geoffrey S. Dutton & Fred L. Moore

  3. Global Monitoring Division, Earth Systems Research Laboratory, NOAA, Boulder, CO, USA

    Stephen A. Montzka, Geoffrey S. Dutton, Brad D. Hall & Fred L. Moore

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  1. Eric A. Ray
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Contributions

E.A.R. wrote the manuscript. E.A.R. and R.W.P. conceived the study and led the data processing. R.W.P. and P.Y. performed the model runs. S.A.M., G.S.D. and B.D.H. provided the measurement data and analysis. All the authors discussed the results and contributed to the manuscript.

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Correspondence to Eric A. Ray.

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Extended data

Extended Data Fig. 1 CFC-11 growth rate anomalies.

CFC-11 growth rate anomalies based on global (purple), SH (blue) and NH (sky blue) average mole fractions from the NOAA GMD network. The growth rates anomalies were calculated as described in Fig. 2. Measured tropical zonal winds at 50 hPa shifted forward by 8–12 months are shown as the thick orange lines to represent QBO variability. The SH anomalies are more consistently phased with the QBO variability compared to the NH anomalies, particularly in the late 1990s and 2003–2007 periods.

Extended Data Fig. 2 CFC-11 loss region and mean circulation.

The stratospheric mean meridional circulation calculated from ERA-Interim reanalysis products averaged over 1995–2015. The arrow lengths represent the strength of the horizontal and vertical components of the mean circulation, and the arrow shading indicates the magnitude of the standard deviation of the vertical component of the circulation on time scales longer than seasonal. The shaded regions represent where the time average CFC-11 photochemical loss occurred from a WACCM run. The loss contour interval is 2.5 × 10−5 ppt/s. The average tropopause pressure from ERA-Interim is shown by the orange line. The red symbols represent the latitudes and average pressures of SH surface measurement sites within the NOAA GMD network.

Extended Data Fig. 3 Model QBO anomalous circulation.

Composite of modeled residual mean circulation anomalies during the peak positive CFC-11 partial pressure anomalies at 20 hPa as shown in Fig. 2. Filled contours represent the anomalies of the vertical component of the residual circulation (w*) and the arrows represent both the meridional and vertical components of the anomalous residual circulation. The open contours show the composite of the zonal mean zonal wind anomalies with positive (westerly) winds in pink, negative (easterly) winds in green (5 m/s contour interval) and the zero contour in purple. The anomalous circulation created by the QBO winds causes a tendency in the partial pressure anomalies, while the absolute values of the partial pressure anomalies, as shown in Fig. 2, will be shifted in time relative to the peak circulation anomalies. This explains the coincidence of positive partial pressure anomalies in a region of westerly shear and downward anomalous circulation above 30 hPa. The tendency of the partial pressure anomalies is negative but positive anomalies remain from the previous months when the descending QBO peak easterly winds were at a higher level. The partial pressure anomalies will be peak positive or negative at the level where the zonal wind anomalies are peak easterly or westerly, respectively.

Extended Data Fig. 4 Modeled CFC-12 interannual partial pressure anomalies.

Same as Fig. 2 but for CFC-12. a, WACCM global average CFC-12 partial pressure anomalies as a function of pressure. The equatorial zonal winds (0, −15 and 15 m/s contours in purple, lime green and pink) are shown for pressures less than 80 hPa. b, Latitude vs pressure composite of the CFC-12 partial pressure anomalies (note different scale from a) from the months of maximum positive CFC-12 partial pressure anomalies at 20 hPa, as indicated by the dashed black lines in a. The unfilled contours represent the composite of the zonal wind anomalies (negative in green, positive in pink (5 m/s contour interval) and zero in purple). The average tropopause pressure is shown by the solid plum line and the annually averaged 90 day local photochemical lifetime of CFC-12 is shown by the dotted line. Since the loss region of CFC-12 is higher in the stratosphere than for CFC-11 (Extended Data Fig. 2), the QBO anomaly pattern of CFC-12 extends higher in the stratosphere compared to CFC-11.

Extended Data Fig. 5 Model QBO circulation and CFC-11 variability.

Time series of modeled extratropical average (poleward of 30°) residual mean vertical velocities regressed on the QBO zonal wind at 30 hPa (orange) and CFC-11 global mean partial pressure anomalies at 100 hPa (sky blue) and the surface (blue). The 100 hPa w* variability corresponds with the composite in Extended Data Fig. 3 that shows easterly (negative) zonal winds at 30 hPa and negative (more downward) w* in the extratropics around 100 hPa. A negative anomaly in w* (enhanced downwelling) will act on the vertical gradient of a trace gas such as CFC-11 and cause a negative tendency, and vice versa for a positive w* anomaly. The CFC-11 partial pressure anomalies at 100 hPa are positively correlated with the 100 hPa w* with a lag of ~ 6 months, consistent with the expected relationship.

Extended Data Fig. 6 Model CFC-11 with and without QBO nudging.

Modeled global mean CFC-11 partial pressure anomalies at 20 hPa (sky blue) and the surface (blue) as well as tropical average (5°S-5°N) zonal winds at 20 hPa from two different WACCM simulations. (a) is from the QBO nudged run described in the main text and (b) is from a free-running simulation with no nudging. The free-running simulation had no connection to specific past years so the x-axis refers to the year of the model run starting from zero. The free-running simulation produced a QBO in zonal wind but with reduced amplitude compared to the nudged run. For the nudged QBO run r = 0.83 with an 11 month lag between the 50 hPa tropical zonal winds and surface CFC-11 partial pressure anomalies, while for the free running model r = 0.15 with a 13 month lag.

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Ray, E.A., Portmann, R.W., Yu, P. et al. The influence of the stratospheric Quasi-Biennial Oscillation on trace gas levels at the Earth’s surface. Nat. Geosci. 13, 22–27 (2020). https://doi.org/10.1038/s41561-019-0507-3

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