TuRTLES

The tropical Upper Troposphere-Lower Stratosphere (TUTLS, from 14 to 30 km above sea level) is the gateway to the stratosphere for tropospheric constituents, including water vapour, pollutants, aerosols and their gaseous precursors. By shaping the distribution of chemicals and particles in the whole stratosphere, transport in the TUTLS influences the ozone layer and the Earth’s radiative balance. Circulation alterations in the TUTLS, such as the recent disruptions of the Quasi-biennal oscillation or the predicted (but yet unobserved) increase in tropical upwelling, bear critical implications for global atmospheric composition and climate. Nevertheless, the mechanisms of air mass transport from the troposphere to the stratosphere in the tropics remain poorly understood and a formidable challenge for chemistry-climate models. In particular, recent studies have emphasized substantial uncertainties in the contribution of vertical diffusion and mixing to the tracer budget. This is especially detrimental to investigations of the effects of anthropogenic activities (e.g. pollution, stratospheric geoengineering) which, in light of the inherently non-linear chemical and microphysical processes involved, rely strongly upon a realistic representation of mixing. Thus, the diffusive term, while previously overshadowed by advection errors and by numerical diffusion, is now the new frontier for next-generation transport models. Part of the difficulty comes from diffusion’s dual character, since it may arise from either small-scale turbulent mixing or diabatic dispersion caused by heterogeneities in radiative heating rates. Furthermore, both processes are intermittent, triggered by various phenomena (clouds, gravity waves) occurring on an extremely wide range of temporal and spatial scales, so that they remain essentially inaccessible to pure model investigations. In this context, the proposed research addresses the problem of vertical diffusion and its effects from an observational perspective. High-resolution observations of fine-scale dynamics, based on unprecedented new measurements but also including rich datasets from long-lasting observational efforts, will be analyzed and merged into a reference product on turbulent mixing in the TUTLS. With the help of Machine Learning approaches, the new dataset will be combined with global meteorological information available from latest-generation reanalysis and geostationary satellites into a novel data-driven parametrization of turbulent mixing. In parallel, precise radiative transfer calculations using observed trace gas fluctuations will shed new light on radiative heating rate variability. These advances will serve to improve the representation of mixing in state-of-the-art chemistry transport simulations and to revisit conceptual transport models, in order to provide the first consolidated estimate of diffusion’s role in transport at the tropical troposphere-stratosphere interface. This outcome will constitute a breakthrough towards an improved understanding of transport in the TUTLS and enable accurate quantification of the associated uncertainties, a key for reliable and believable chemistry-climate model predictions.