Abstract/Summary

Turbulence is a significant problem for the aviation industry, costing hundreds of millions of dollars each year. Clear-air turbulence (CAT) is particularly troublesome as it is invisible and tends to occur in the vicinity of the jet stream, where eastbound aircraft fly to take advantage of the westerly tailwinds. With climate change, CAT is projected to increase. Because CAT is sub-grid scale in numerical weather prediction models and therefore cannot be explicitly simulated, diagnostics are used to indicate regions of CAT. In this thesis, using 80 serious aircraft turbulence encounters, the skill of 21 such diagnostics at forecasting injury-causing CAT is evaluated and substantial variation in diagnostic skill is found. This knowledge is then retrospectively applied to two previous future CAT projections. Using the same 21-diagnostic average, the global distribution of 197hPa CAT is calculated for the years 1979 and 2020 as well as the relative and absolute change over this period. Diagnosed CAT occurs mostly over the midlatitudes (more so in the northern hemisphere than the southern) and is more frequent over the oceans than the land with hotspots to the west of ocean basins. Since 1979, the biggest changes have been a 54% increase in severe-or-greater CAT over the north Atlantic and 41% over the continental USA. The global distribution of 197hPa CAT is examined in different phases of ENSO and the NAO. Both sources of climate variability have a substantial impact on the distribution of CAT, although the effect of ENSO is global whereas the impact of the NAO is more local to the north Atlantic and Europe. This information can be used to make a seasonal CAT forecast which should help airlines better optimise their fuel requisitioning. The work in this thesis indicates that aviation-affecting CAT is sensitive to climate conditions, both variability and trends. If the aviation industry is to successfully adapt to the changing climate, advanced preparations as well as continued progress in accurately forecasting CAT will be essential.