In order to understand the predictability aspect of chaotic systems a little better, let us expand some more on the sensitivity and divergence properties of chaotic systems: When we follow the orbit in fig.5, we can see that the motion on each of the wings of the Lorenz butterfly is fairly regular. Only close to the z-axis, where the system has to decide if it should continue on the right wing or switch to the left wing or vice versa we directly see the origin for unpredictable behavior of the Lorenz system: Small influences can determine the global large scale future of the system. The same kind of perturbation in a less sensitive region of the Lorenz attractor could go completely unnoticed. We can understand that it is very important to find tools to identify those sensitive regions where the state of the system is extremely vulnerable to external perturbations. One of those nonlinear measures, the local divergence rate has been introduced in [39]. A visualization tool that provides a good global estimate of the distribution of these sensitivity parameters is given by the recurrence diagram [19]. It allows us to anticipate in which states of the system it might be very sensitive to small fluctuations and in which domains it is relatively robust and insensitive and also where attempts to control the system would be most promising.