Sensitivity of age of air trends to the derivation method for non-linear increasing inert SF<sub>6</sub>

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.

Climatological impact of the Brewer–Dobson circulation on the N<sub>2</sub>O budget in WACCM, a chemical reanalysis and a CTM driven by four dynamical reanalyses

“…8a, b). The WACCM-CCMI simulations agree well with the BRAM2 chemical reanalysis, confirming the results obtained through the direct comparison with MLS observations (Froidevaux et al, 2019).…”

“…It is not recommended to use the BRAM2 N 2 O reanalysis outside of this pressure range. BRAM2 N 2 O is also affected by a small drift of around −4 % between 2005 and 2015 (see also Froidevaux et al, 2019).…”

“…WACCM has been widely used for studies of tracers' transport in the stratosphere and upper troposphere based on the TEM analysis (e.g., Abalos et al, 2017). WACCM simulations of the climatological N 2 O over the 2005-2014 period have also been evaluated favorably with satellite observations in the stratosphere (Froidevaux et al, 2019).…”

Impact of Lagrangian transport on lower-stratospheric transport timescales in a climate model

“…1) shows many qualitative similarities between the Lagrangian and Eulerian frameworks. In both representations, mean age gradually increases with distance from the tropical tropopause layer (TTL), the region from 355-425 K through which most tropospheric air entering the stratosphere passes (e.g., Holton et al, 1995;Fueglistaler et al, 2009;Butchart, 2014). At all potential temperature levels, mean age is lowest in the tropical stratosphere (tropical pipe; Plumb, 1996) and gradually increases towards high latitudes.…”

“…The upper troposphere and lower stratosphere (UTLS) is an important region for global climate as the chemical composition of radiatively active trace gas species there has crucial impacts on radiation and surface temperatures (e.g., Solomon et al, 2010). The entry of air masses into the stratosphere is controlled by the chemical and dynamical processes in the UTLS (e.g., Holton et al, 1995;Fueglistaler et al, 2009), presenting a challenge for understanding and modeling the region. To overcome, climate models must have a realistic representation of UTLS transport processes in order to provide reliable predictions and assist in robust theoretical development.…”