## 1 Introduction

[2] Global warming is expected to lead to poleward shifting, strengthening tropospheric jets, and a weakened Hadley circulation [e.g., *Yin*, 2005; *Miller et al*., 2006]. Because the tropospheric jets (the associated baroclinic eddies) and the meridional overturning circulation are all keys to controlling the transport of energy and momentum, the question arises: What are the quantitative effects of these circulation changes on tropospheric constituent transport? The climate change signature on basic state variables such as temperature, humidity, winds, and chemical composition, particularly in the ozone, has been analyzed in a vast number of studies and continues to be of great interest. In comparison, the signature of climate change on large-scale tropospheric transport has received relatively little attention despite its importance for understanding changes in composition and global air quality, which are not only driven by changes in chemistry and emissions but also by crucial changes in atmospheric flow.

[3] Here, we will use an idealized atmospheric circulation model to demonstrate how changes in tropospheric transport can be quantified in a tracer-independent manner by using synthetic Green function tracers that quantify a fundamental aspect of the atmosphere's advective-eddy-diffusive transport operator, which is independent of any particular trace species. Although *Holzer and Boer* [2001] explored the issue in terms of timescales and the large-scale structure of tracers with specified idealized emissions, our focus here is on the spatial distribution of rigorously defined air masses, which are a particularly simple tracer-independent transport diagnostic ideally suited to model investigations of climate change. Because anthropogenic and biogenic trace species originate primarily in the planetary boundary layer (PBL), and the stratosphere is a source of ozone and cosmogenic tracers for the troposphere, we define both PBL and stratospheric (STRAT) air-mass fractions. More precisely, the PBL air-mass fraction at a point **r**, whose surface origin was geographic region Ω* _{i}*, is simply defined as the mass fraction of the air at

**r**that had its last contact with the PBL in region Ω

*. An air-mass fraction can be thought of as a label of where last PBL contact occurred, allowing an assessment of the relative importance of different source regions. STRAT air-mass fractions are defined analogously.*

_{i}[4] Air-mass fractions thus defined are the atmospheric equivalent of water-mass fractions, which have a long history of being used in oceanography [e.g., *Tomczak*, 1981; *Haine and Hall*, 2002; *Holzer et al*., 2010], but have not yet been adopted by the atmospheric science community. Air-mass fractions can be computed in any atmospheric transport model as simple equilibrated tracer mixing ratios with appropriate boundary conditions. The air-mass fractions show where, and with what dilution, air from various source regions can be found. Air-mass fractions, and their changes, thus help to isolate the role of transport from that of chemistry and changing emissions in shaping the atmosphere's changing chemical composition. Here, we use a relatively simple, idealized model of the atmosphere to demonstrate the utility of air-mass fractions as a first-order tracer-independent diagnostic of tropospheric transport and its climate change.

[5] The statistical properties of transport can usefully be referred to as “transport climate” [*Holzer and Boer*, 2001]. In this paper, we quantify the change in transport climate with idealized warming by examining the difference in the climatological mean air-mass fractions between two time slice integrations with a “dynamical core” circulation model [*Wang et al*., 2012]: one for idealized current conditions and another for idealized future conditions with a specified heating in the upper tropical troposphere.

[6] We emphasize that it is our goal to demonstrate the use of air-mass fractions as a diagnostic of changes in the transport climate—it is not our aim to make detailed, high-fidelity projections of how atmospheric transport is likely to change in the future. The climate of the dynamical core circulation, and its change with prescribed heating, are ideal for this purpose because they avoid the complexities of comprehensive climate models while still capturing key dynamic large-scale changes as demonstrated by *Wang et al*. [2012].

[7] Broadly, the changes in the air-mass fractions are on the order of 10% with patterns that are interpretable in terms of changes in the mean flow and in the eddy statistics. However, unlike the flow statistics, the air-mass fractions quantify the integrated effect of advection and eddy diffusion along all possible paths from their region of origin to the point of interest.