Tropospheric SF<sub>6</sub>: Age of air from the Northern Hemisphere midlatitude surface

Waugh, Darryn W.; Crotwell, Andrew M.; Dlugokencky, E. J.; Dutton, G. S.; Elkins, James W.; Hall, B. D.; Hintsa, E. J.; Hurst, D. F.; Montzka, S. A.; Mondeel, D. J.; Moore, F. L.; Nance, J. D.; Ray, E. A.; Steenrod, Stephen D.; Strahan, S. E.; Sweeney, C.

doi:10.1002/jgrd.50848

Cited by 46 publications

(103 citation statements)

References 34 publications

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“…The spatial distribution of the tracer age shown in Fig. 1 is similar to the distribution of idealized or realistic long-lived tracers shown in previous studies (e.g., Denning et al, 1999;Holzer and Boer, 2001;Miyazaki et al, 2008;Waugh et al, 2013) and can be related to the general circulation (e.g., Hadley cells and Intertropical Convergence Zone, ITCZ). There is rapid transport from the NH midlatitude surface into the NH extratropical troposphere, through a combination of along-isentropic and convective mixing, and as a consequence there are weak age gradients in the NH extratropics.…”

Section: Climatological Distributionssupporting

confidence: 82%

“…Alternatively, recent studies have used observed and simulated SF 6 or simulated idealized mean age tracers to estimate the mean transport time from the NH surface to locations throughout the troposphere (Holzer and Boer, 2001;Waugh et al, 2013). This approach provides a more complete description of interhemispheric transport, quantifying not only differences in transport into the tropics versus southern extratropics but also differences in transport between the lower and upper troposphere.…”

Section: Introductionmentioning

confidence: 99%

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Spatial and temporal variability of interhemispheric transport times

Yang

Waugh

et al. 2018

Atmos. Chem. Phys.

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Abstract. The seasonal and interannual variability of transport times from the northern midlatitude surface into the Southern Hemisphere is examined using simulations of three idealized "age" tracers: an ideal age tracer that yields the mean transit time from northern midlatitudes and two tracers with uniform 50-and 5-day decay. For all tracers the largest seasonal and interannual variability occurs near the surface within the tropics and is generally closely coupled to movement of the Intertropical Convergence Zone (ITCZ). There are, however, notable differences in variability between the different tracers. The largest seasonal and interannual variability in the mean age is generally confined to latitudes spanning the ITCZ, with very weak variability in the southern extratropics. In contrast, for tracers subject to spatially uniform exponential loss the peak variability tends to be south of the ITCZ, and there is a smaller contrast between tropical and extratropical variability. These differences in variability occur because the distribution of transit times from northern midlatitudes is very broad and tracers with more rapid loss are more sensitive to changes in fast transit times than the mean age tracer. These simulations suggest that the seasonalinterannual variability in the southern extratropics of trace gases with predominantly NH midlatitude sources may differ depending on the gases' chemical lifetimes.

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Section: Climatological Distributionssupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Spatial and temporal variability of interhemispheric transport times

Yang

Waugh

et al. 2018

Atmos. Chem. Phys.

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“…AoA tracers with linearly growing boundary conditions lead to different concentration gradients than tracers with surface emissions and first-order decay, such as E90. In regions with large gradients, such as the planetary boundary layer and the tropopause, differences in the nu- Our multi-model results agree qualitatively with the study of Waugh et al (2013) that focused on SF 6 and a AoA tracer in a single model (GMI-MERRA). They found "older" AoA than the age derived from SF 6 observations.…”

supporting

confidence: 82%

“…In practical model applications focussing on stratospheric age spectra, G(x, t|t 0 ) is calculated as 30 the response of a time-dependent boundary condition δ(t − t 0 ) specified in a forcing volume in the troposphere. More recently, this concept has also been applied to tropospheric studies (Holzer and Hall, 2000;Waugh et al, 2013;Holzer and Waugh, 2015). In this AoA inter-comparison, we will only analyse the mean age of air.…”

mentioning

confidence: 99%

Age of Air as a diagnostic for transport time-scales in global models

Krol¹,

Bruine²,

Killaars³

et al. 2017

Preprint

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Abstract. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, three global circulation models and three chemistry transport models simulated five tracers with boundary conditions that grow linearly in time. This allows for an evaluation of the AoA and transport times associated with inter-hemispheric transport, vertical mixing in the troposphere, transport to and in the stratosphere, and transport of air masses between land and ocean. Since AoA is not a directly measurable quantity in the atmosphere, simulations of 222 Rn and SF 6 were also requested. 5We focus this first analysis on averages over the period 2000-2010, taken from longer simulations covering the 1988 -2014 period. We find that two models, NIES and TOMCAT, show substantially slower vertical mixing in the troposphere compared to other models (LMDZ, TM5, EMAC, and ACTM). However, while the TOMCAT model, as used here, has slow transport between the hemispheres and between land and ocean, the NIES model shows efficient horizontal mixing and a smaller latitudinal gradient in SF 6 compared to the other models and observations. We find consistent differences between models concerning 10 vertical mixing of the troposphere, expressed as AoA differences and modeled 222Rn gradients between 950 and 500 hPa.All models agree, however, on an interesting asymmetry in inter-hemispheric mixing, with faster transport from the Northern hemisphere surface to the Southern hemisphere than vice versa. This is attributed to a rectifier caused by a stronger seasonal cycle in boundary layer venting over Northern hemispheric landmasses, and possibly to a related asymmetric position of the inter-tropical convergence zone. The calculated AoA in the upper stratosphere varies considerably among the models (4 -7 15 years). Finally, we find that the inter-model differences are generally larger than differences in AoA that result from using the same model with a different resolution or convective parameterisation. Taken together, the AoA model inter-comparison provides a useful addition to traditional approaches to evaluate transport time scales. Results highlight that inter-model differences 1 Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-262 Manuscript under review for journal Geosci. Model Dev. Discussion started: 7 November 2017 c Author(s) 2017. CC BY 4.0 License. associated with resolved transport (advection) and parameterised transport (convection, boundary layer mixing) are still large, and require further analysis. For this purpose, all model output and analysis software is available.

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“…The annual growth of FTIR measurements is 0.265 ± 0.013 pptv year −1 from 2004 to 2016, which is slightly weaker than the trend in the SMO in situ measurements (0.285 ± 0.002 pptv year −1 ) for the same time period. Waugh et al (2013) pointed out that the age of nearsurface SF 6 at SMO (14 • S) is about 0.4 years higher than that on Reunion Island (21 • S). In addition, the global surface in situ measurement network (https://www.esrl.noaa.…”

Section: Methodsmentioning

confidence: 96%

Ground-based FTIR retrievals of SF<sub>6</sub> on Reunion Island

et al. 2018

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Abstract. SF 6 total columns were successfully retrieved from FTIR (Fourier transform infrared) measurements (Saint Denis and Maïdo) on Reunion Island (21 • S, 55 • E) between 2004 and 2016 using the SFIT4 algorithm: the retrieval strategy and the error budget were presented. The FTIR SF 6 retrieval has independent information in only one individual layer, covering the whole of the troposphere and the lower stratosphere. The trend in SF 6 was analysed based on the FTIR-retrieved dry-air column-averaged mole fractions (X SF 6 ) on Reunion Island, the in situ measurements at America Samoa (SMO) and the collocated satellite measurements (Michelson Interferometer for Passive Atmospheric Sounding, MIPAS, and Atmospheric Chemistry Experiment Fourier Transform Spectrometer, ACE-FTS) in the southern tropics. The SF 6 annual growth rate from FTIR retrievals is 0.265 ± 0.013 pptv year −1 for 2004-2016, which is slightly weaker than that from the SMO in situ measurements (0.285 ± 0.002 pptv year −1 ) for the same time period. The SF 6 trend in the troposphere from MIPAS and ACE-FTS observations is also close to the ones from the FTIR retrievals and the SMO in situ measurements.

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Tropospheric SF₆: Age of air from the Northern Hemisphere midlatitude surface

Cited by 46 publications

References 34 publications

Spatial and temporal variability of interhemispheric transport times

Spatial and temporal variability of interhemispheric transport times

Age of Air as a diagnostic for transport time-scales in global models

Ground-based FTIR retrievals of SF<sub>6</sub> on Reunion Island

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Tropospheric SF6: Age of air from the Northern Hemisphere midlatitude surface

Cited by 46 publications

References 34 publications

Spatial and temporal variability of interhemispheric transport times

Spatial and temporal variability of interhemispheric transport times

Age of Air as a diagnostic for transport time-scales in global models

Ground-based FTIR retrievals of SF&lt;sub&gt;6&lt;/sub&gt; on Reunion Island

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Product

Resources

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Tropospheric SF₆: Age of air from the Northern Hemisphere midlatitude surface

Ground-based FTIR retrievals of SF<sub>6</sub> on Reunion Island