Abstract
Abstract. Mean age of air (AoA) is a diagnostic of transport along the stratospheric Brewer–Dobson circulation. While models consistently show negative trends, long-term time series (1975–2016) of AoA derived from observations show non-significant positive trends in mean AoA in the Northern Hemisphere. This discrepancy between observed and modelled mean AoA trends is still not resolved. There are uncertainties and assumptions required when deriving AoA from trace gas observations. At the same time, AoA from climate models is subject to uncertainties, too. In this paper, we focus on the uncertainties due to the parameter selection in the method that is used to derive mean AoA from SF6 measurements in Engel et al. (2009, 2017). To correct for the non-linear increase in SF6 concentrations, a quadratic fit to the time series at the reference location, i.e. the tropical surface, is used. For this derivation, the width of the AoA distribution (age spectrum) has to be assumed. In addition, to choose the number of years the quadratic fit is performed for, the fraction of the age spectrum to be considered has to be assumed. Even though the uncertainty range due to all different aspects has already been taken into account for the total errors in the AoA values, the systematic influence of the parameter selection on AoA trends is described for the first time in the present study. For this, we use the EMAC (ECHAM MESSy Atmospheric Chemistry) climate model as a test bed, where AoA derived from a linear tracer is available as a reference and modelled age spectra exist to diagnose the actual spatial age spectra widths. The comparison of mean AoA from the linear tracer with mean AoA from a SF6 tracer shows systematic deviations specifically in the trends due to the selection of the parameters. However, for an appropriate parameter selection, good agreement for both mean AoA and its trend can be found, with deviations of about 1 % in mean AoA and 12 % in AoA trend. In addition, a method to derive mean AoA is evaluated that applies a convolution to the reference time series. The resulting mean AoA and its trend only depend on an assumption about the ratio of moments. Also in that case, it is found that the larger the ratio of moments, the more the AoA trend gravitates towards the negative. The linear tracer and SF6 AoA are found to agree within 0.3 % in the mean and 6 % in the trend. The different methods and parameter selections were then applied to the balloon-borne SF6 and CO2 observations. We found the same systematic changes in mean AoA trend dependent on the specific selection. When applying a parameter choice that is suggested by the model results, the AoA trend is reduced from 0.15 to 0.07 years per decade. It illustrates that correctly constraining those parameters is crucial for correct mean AoA and trend estimates and still remains a challenge in the real atmosphere.
Highlights
The Brewer–Dobson circulation (BDC) is the slow, overturning Equator-to-pole mass circulation in the stratosphere (Butchart, 2014)
Since the derivation of mean age of air (AoA) from measurements requires an assumption about the AoA spectrum, we derived spectra for EMAC in a transient simulation
We find that the sensitivity of the AoA trends derived from SF6 to the parameter choice arises predominantly from deviations in mean AoA in earlier years (1970s and 1980s)
Summary
The Brewer–Dobson circulation (BDC) is the slow, overturning Equator-to-pole mass circulation in the stratosphere (Butchart, 2014). From a conceptual point of view, AoA can be illustrated as a number of parcels that constitute an air mass, and each of those parcels takes a different pathway from one reference point to an observation point. This idea was first introduced by Kida (1983). Those different pathways lead to a distribution of transport times, which is called the age spectrum of the specific air mass. The first moment of this age spectrum is the mean AoA
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.