Pilch Kedzierski, Robin (2016) Advanced Understanding of the Tropopause Inversion Layer: High-Resolution GPS-RO Observations and Reanalyses. (PhD/ Doctoral thesis), Christian-Albrechts-Universität Kiel, Kiel, Germany, 150 pp.

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Abstract

The upper troposphere and lower stratosphere (UTLS) is a region of the atmosphere that acts as a 'transition' between the two layers and consequently has properties from both. Within this region, a fine-scale feature is located: the Tropopause Inversion Layer (TIL), which consists of a sharp temperature inversion at the tropopause and the corresponding high static stability values aloft. The latter theoretically affects the dispersion relations of atmospheric waves like Rossby or Inertia-Gravity waves and hampers stratosphere-troposphere exchange (STE), which is why the TIL is established as an important feature of the UTLS. The present thesis aims to improve the observational knowledge about the TIL by analyzing high-resolution GPS radio-occultation (GPS-RO) data globally. The focus is on day-to-day and synoptic-scale TIL variability, a novel approach to build upon the climatological point of view from earlier TIL studies. Also, a dynamical mechanism for TIL enhancement is studied and quantified: the transient tropopause modulation by equatorial and extratropical waves, and the resulting net TIL enhancement. The role of this transient wave modulation mechanism has not been investigated in TIL literature, and its quantification from GPS-RO observations puts it among the most important TIL enhancing processes. Lastly, the paradigm that data assimilation worsens the representation of the TIL in reanalyses, valid a decade ago, has been tested in modern systems: the ERA-Interim reanalysis and the ECMWF forecasts. Both systems show TIL improvement by data assimilation increments, updating the earlier status quo. As a whole, this thesis significantly improves our knowledge about observed properties of the TIL and the mechanisms responsible for its formation and maintenance, and shows that reanalyses are a valuable tool for TIL research.

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