Handout (11.2 MB)
view on the predictability of weather by revealing sensitivity of solutions to initial conditions,
which is so-called butterfly effect and also known as chaos. Over 50 years since Lorenz’s 1963
study, the statement of ``weather is chaotic’’ has been well accepted. Such a view turns our
attention from regularity associated with the Laplace’s view of determinism to irregularity
associated with the chaos. Stated alternatively, while Lorenz (1993) documented that “as with
Poincare and Birkhoff, everything centers around periodic solutions,” he himself and chaos
advocates focused the existence of non-periodic solutions and their complexities. Two
interesting questions are: (1) whether two types of regular and irregular solutions appear
exclusively? (2) whether the statement of ``weather is chaotic’’ completely excludes periodic
processes within weather. To answer the two questions, a refined statement on the nature of
weather is proposed based on recent advances in high-dimensional Lorenz models and real world
global models. In this study, we provide a report to: (1) Illustrate two kinds of attractor
coexistence within Lorenz models. Each kind contains two of three attractors including regular
point and periodic, and irregular chaotic attractors corresponding to steady-state, limit cycle,
and chaotic solutions, respectively. (2) Suggest that the entirety of weather possesses the dual
nature of order and chaos associated with regular and irregular processes, respectively. Specific
weather systems may appear chaotic or non-chaotic within their finite lifetime. While chaotic
systems contain a finite practical predictability, non-chaotic systems (e.g., dissipative
processes) could have better predictability (e.g., up to their lifetime). The refined view on the
nature of weather is neither too optimistic nor pessimistic as compared to the Laplacian view
of deterministic unlimited predictability and the Lorenz view of deterministic chaos with finite
predictability. A new focus is on the frequency of stability, instability and chaos.
Supplementary URL: http://doi.org/10.13140/RG.2.2.21811.07204