9. Future Directions

What changes may the future bring to climate time series analysis? First, we outline (Sects. 9.1–9.3) more short-term objectives of “normal science” (Kuhn, The Structure of Scientific Revolutions, 2nd edn. University of Chicago Press, Chicago, 210 pp, 1970), extensions of previous material (Chaps. 1–8). Then we take a chance (Sects. 9.4 and 9.5) and look on paradigm changes in climate data analysis that may be effected by virtue of strongly increased computing power (and storage capacity). Whether this technological achievement comes in the form of grid computing (Allen, Nature 401(6754):642, 1999; Allen et al., Nature 407(6804):617–620, 2000; Stainforth et al., Philos Trans R Soc Lond Ser A 365(1857):2145–2161, 2007) or quantum computing (Nielsen, Chuang, Quantum Computation and Quantum Information. Cambridge University Press, Cambridge, 676pp, 2000; DiCarlo et al., Nature 460(7252):240–244, 2009; Lanyon et al., Nat Phys 5(2):134–140, 2009; Rieffel and Polak, Quantum Computing: A Gentle Introduction. MIT Press, Cambridge, MA, 372pp, 2011)—the assumption here is the availability of machines that are faster by a factor of 10 to the power of, say, 12, by a midterm period of, say, less than a few decades.