LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Lorenz, Edward N. (2005)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
Subjects:
Because of the errors entailed in observing certain systems, the states that one might believe to be the true states form an ensemble, as do the states obtained from these states by forward extrapolation in time.We identify the uncertainty with the root-mean-square distance in state space of the ensemble members from their mean. We enumerate the properties of a special three-variable system that behaves chaotically, and we use the system to evaluate a logarithmic measure α (t1, t0) of the ratio of the uncertainty at a ‘verifying time’ t1 to that at an ‘observing time’ t0. With t0 and t1 as coordinates, we construct diagrams displaying contours of α (t1, t0).We find that the details of the diagrams tend to line up in the horizontal and vertical directions, rather than parallel to the diagonal where t1 = t0, as they would if α (t1, t0) depended mainly on the forecast range t1 − t0. The implication is that states at certain times t1 are highly predictable, i.e. α (t1, t0) < α (t, t0) if t occurs somewhat before or after t1, and that states at certain times t0 are highly predictive, i.e. α (t1, t0)< α (t1, t) if t occurs somewhat before or after t0. When observations at times preceding t0 are combined with those at t0, the greatest resulting reductions in uncertainty at t1 occur when the states at the additional times are highly predictive. We speculate as to the applicability of these findings to larger systems.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Aires, F. and Rossow, W. B. 2003. Inferring instantaneous, multivariate and nonlinear sensitivities for the analysis of feedback processes in a dynamical system: Lorenz model case-study. Q. J. R. Meteorol. Soc. 129, 239-275.
    • Charney, J. G., Fjo¨rtoft, R. and von Neumann, J. 1950. Numerical integration of the barotropic vorticity equation. Tellus 2, 237-254.
    • Charney, J. G., Fleagle, R. G., Lally, V. E., Riehl, H. and Wark, D. Q. 1966. The feasibility of a global observation and analysis experiment. Bull. Am. Meteorol. Soc. 47, 200-220.
    • Eady, E. T. 1951. The quantitative theory of cyclone development. In: Compendium of Meteorology. Am. Meteorol. Soc., Boston, MA, 464- 469.
    • Farmer, J. D. and Sidorowich, J. J. 1991. Optimal shadowing and noise reduction. Physica D 47, 373-392.
    • Farrell, B. F. 1990. Small error dynamics and the predictability of atmospheric flows. J. Atmos. Sci. 47, 2409-2416.
    • Hansen, J. A. and Smith, L. A. 2001. Probabilistic noise reduction. Tellus 53A, 585-598.
    • Ikeda, K. 1979. Multiple-valued stationary state and its instability of the transmitted light by a ring cavity system. Opt. Commun. 30, 257.
    • Lacarra, J. and Talagrand, O. 1988. Short-range evolution of small perturbations in a barotropic model. Tellus 40A, 81-95.
    • Lorenz, E. N. 1965. A study of the predictability of a 28-variable atmospheric model. Tellus 17, 321-333.
    • Lorenz, E. N. 1984. Irregularity: a fundamental property of the atmosphere. Tellus 36A, 98-110 (L84).
    • Lorenz, E. N. 1990. Can chaos and intransitivity lead to interannual variability? Tellus 42A, 378-389.
    • Palmer, T. N. 1988. Medium and extended range predictability of the Pacific/North American mode. Q. J. R. Meteorol. Soc. 114, 691-713.
    • Phillips, N. 1956. The general circulation of the atmosphere: a numerical experiment. Q. J. R. Meteorol. Soc. 82, 123-164.
    • Poincare´, H. 1912. Science et me´thode. Flammarion, Paris.
    • Trevisan, A. 1993. Impact of transient error growth on global average predictability measures. J. Atmos. Sci. 50, 1016-1025.
  • No related research data.
  • No similar publications.

Share - Bookmark

Funded by projects

  • NSF | Model Bending: Towards Deal...

Cite this article

Collected from