A New Stratospheric Mixing Diagnostic Based on Satellite Observations of Pairs of Trace Gases: First Real-Data Results

The stratospheric circulation transports a variety of interesting trace substances such as ozone and aerosols. The transport can be conceptually split into two parts: the diabatic (overturning, Brewer-Dobson) circulation and isentropic mixing by eddies. Existing climate models disagree about the strength of the isentropic mixing in particular, which motivates efforts to constrain the mixing using observations.

We are developing a new method to estimate stratospheric isentropic mixing from zonally averaged satellite trace gas observations, which leverages the fact that the mixing ratios of long-lived stratospheric trace gases are compactly and sometimes nonlinearly related. We posit that the isentropic mixing is diffusive and then leverage nonlinear relationships between pairs of gases to solve for an (eddy) diffusivity, which is our mixing metric. The diagnosed diffusivities vary with latitude (unlike mixing parameters fit in coarse-meridional-resolution box models) and are defined on conventional physical latitudes (instead of the equivalent latitudes used in modified Lagrangian mean diffusivity analyses). Furthermore, the method has only minimal dependence on reanalyses—these are needed only to drive atmospheric chemistry models that supply trace gas production and loss rates needed for the diffusivity calculation.

Because our method should be applicable in very similar ways to both gridded zonally-averaged satellite observations and zonally-averaged chemistry-climate model output, it is a promising approach for comparing mixing in chemistry climate models to observations. In a first attempt to apply the method to real data, we will diagnose stratospheric isentropic diffusivities using N2O, CFC-11, and CFC-12 retrievals from MIPAS (the Michelson Interferometer for Passive Atmospheric Sounding on ENVISAT, [1]) and HIRDLS (the High Resolution Dynamics Limb Sounder on Aura, [2]).

By analyzing three different gases each observed by two instruments, we will be able to investigate the sensitivity of our results to the exact pair of gases used as well as the possible effects of instrument-specific coverage limitations or biases. Furthermore, we will investigate the possibility of improving estimates of the relationships between the various gases by using additional data from ACE-FTS (the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer, [3]). Finally, in a first step towards model evaluation we will perform a similar diffusivity analysis of the MERRA-2 GMI chemistry-climate model simulation [4] which will also be used as the source of the requisite chemical loss information for the satellite data analyses.

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