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The performance of tomographic adaptive optics systems is intrinsicallylinked to the vertical profile of optical turbulence. Firstly, a sufficientnumber of discrete turbulent layers must be reconstructed to model the truecontinuous turbulence profile. Secondly over the course of an observation, theprofile as seen by the telescope changes and the tomographic reconstructor mustbe updated. These changes can be due to the unpredictable evolution ofturbulent layers on meteorological timescales as short as minutes. Here weinvestigate the effect of changing atmospheric conditions on the quality oftomographic reconstruction by coupling fast analytical adaptive opticssimulation to a large database of 10 691 high resolution turbulence profilesmeasured over two years by the Stereo-SCIDAR instrument at ESO Paranal, Chile.This work represents the first investigation of these effects with a large,statistically significant sample of turbulence profiles. The statistical natureof the study allows us to assess not only the degradation and variability intomographic error with a set of system parameters (e.g. number of layers,temporal update period) but also the required parameters to meet some errorthreshold. In the most challenging conditions where the profile is rapidlychanging, these parameters must be far more tightly constrained in order tomeet this threshold. By providing estimates of these constraints for a widerange of system geometries as well as the impact of different temporaloptimisation strategies we may assist the designers of tomographic AO for theELT to dimension their systems.

Limitations imposed by optical turbulence profile structure and evolution on tomographic reconstruction for the ELT