Articles | Volume 9, issue 24
15 Dec 2009
 | 15 Dec 2009

Diagnostics of the Tropical Tropopause Layer from in-situ observations and CCM data

E. Palazzi, F. Fierli, F. Cairo, C. Cagnazzo, G. Di Donfrancesco, E. Manzini, F. Ravegnani, C. Schiller, F. D'Amato, and C. M. Volk

Abstract. A suite of diagnostics is applied to in-situ aircraft measurements and one Chemistry-Climate Model (CCM) data to characterize the vertical structure of the Tropical Tropopause Layer (TTL). The diagnostics are based on vertical tracer profiles and relative vertical tracer gradients, using tropopause-referenced coordinates, and tracer-tracer relationships in the tropical Upper Troposphere/Lower Stratosphere (UT/LS).

Observations were obtained during four tropical campaigns performed from 1999 to 2006 with the research aircraft Geophysica and have been compared to the output of the ECHAM5/MESSy CCM. The model vertical resolution in the TTL (~500 m) allows for appropriate comparison with high-resolution aircraft observations and the diagnostics used highlight common TTL features between the model and the observational data.

The analysis of the vertical profiles of water vapour, ozone, and nitrous oxide, in both the observations and the model, shows that concentration mixing ratios exhibit a strong gradient change across the tropical tropopause, due to the role of this latter as a transport barrier and that transition between the tropospheric and stratospheric regimes occurs within a finite layer. The use of relative vertical ozone and carbon monoxide gradients, in addition to the vertical profiles, helps to highlight the region where this transition occurs and allows to give an estimate of its thickness. The analysis of the CO-O3 and H2O-O3 scatter plots and of the Probability Distribution Function (PDF) of the H2O-O3 pair completes this picture as it allows to better distinguish tropospheric and stratospheric regimes that can be identified by their different chemical composition.

The joint analysis and comparison of observed and modelled data allows to state that the model can represent the background TTL structure and its seasonal variability rather accurately. The model estimate of the thickness of the interface region between tropospheric and stratospheric regimes agrees well with average values inferred from observations. On the other hand, the measurements can be influenced by regional scale variability, local transport processes as well as deep convection, that can not be captured by the model.

Final-revised paper